1 code implementation • 26 May 2025 • Rihui Xin, Han Liu, Zecheng Wang, Yupeng Zhang, Dianbo Sui, Xiaolin Hu, Bingning Wang
The resulting GRPO approach, leveraging format-length surrogate signals, not only matches but surpasses the performance of the standard GRPO algorithm relying on ground truth answers in certain scenarios, achieving 40. 0\% accuracy on AIME2024 with a 7B base model.
no code implementations • 26 May 2025 • Jerry Yao-Chieh Hu, Xiwen Zhang, Maojiang Su, Zhao Song, Han Liu
We study the computational limits of learning $k$-bit Boolean functions (specifically, $\mathrm{AND}$, $\mathrm{OR}$, and their noisy variants), using a minimalist single-head softmax-attention mechanism, where $k=\Theta(d)$ relevant bits are selected from $d$ inputs.
no code implementations • 22 May 2025 • Ziqing Wang, Kexin Zhang, Zihan Zhao, Yibo Wen, Abhishek Pandey, Han Liu, Kaize Ding
Large language models (LLMs) are introducing a paradigm shift in molecular discovery by enabling text-guided interaction with chemical spaces through natural language, symbolic notations, with emerging extensions to incorporate multi-modal inputs.
no code implementations • 21 May 2025 • Ao Liu, Botong Zhou, Can Xu, Chayse Zhou, Chenchen Zhang, Chengcheng Xu, Chenhao Wang, Decheng Wu, Dengpeng Wu, Dian Jiao, Dong Du, Dong Wang, Feng Zhang, Fengzong Lian, Guanghui Xu, Guanwei Zhang, Hai Wang, Haipeng Luo, Han Hu, Huilin Xu, Jiajia Wu, Jianchen Zhu, Jianfeng Yan, Jiaqi Zhu, Jinbao Xue, Jun Xia, Junqiang Zheng, Kai Liu, Kai Zhang, Kai Zheng, Kejiao Li, Keyao Wang, Lan Jiang, Lixin Liu, Lulu Wu, Mengyuan Huang, Peijie Yu, Peiqi Wang, Qian Wang, Qianbiao Xiang, Qibin Liu, Qingfeng Sun, Richard Guo, Ruobing Xie, Saiyong Yang, Shaohua Chen, Shihui Hu, Shuai Li, Shuaipeng Li, Shuang Chen, Suncong Zheng, Tao Yang, Tian Zhang, TingHao Yu, Weidong Han, Weijie Liu, Weijin Zhou, Weikang Wang, Wesleye Chen, Xiao Feng, Xiaoqin Ren, Xingwu Sun, Xiong Kuang, Xuemeng Huang, Xun Cao, Yanfeng Chen, Yang Du, Yang Zhen, Yaping Deng, Yi Shen, Yigeng Hong, Yiqi Chen, Yiqing Huang, Yuchi Deng, Yue Mao, Yulong Wang, Yuyuan Zeng, Zenan Xu, Zhanhui Kang, Zhenxiang Yan, Zheng Fang, Zhichao Hu, Zhongzhi Chen, Zhuoyu Li, Zongwei Li, Alex Yan, Ande Liang, Baitong Liu, Beiping Pan, Bin Xing, Binghong Wu, Bingxin Qu, Bolin Ni, Boyu Wu, Chen Li, Cheng Jiang, Cheng Zhang, Chengjun Liu, Chengxu Yang, Chiyu Wang, Chong Zha, Daisy Yi, Di Wang, Fanyang Lu, Fei Chen, Feifei Liu, Feng Zheng, Guanghua Yu, Guiyang Li, Guohua Wang, Haisheng Lin, Han Liu, Han Wang, Hao Fei, Hao Lu, Haoqing Jiang, Haoran Sun, Haotian Zhu, Huangjin Dai, Huankui Chen, Huawen Feng, Huihui Cai, Huxin Peng, Jackson Lv, Jiacheng Shi, Jiahao Bu, Jianbo Li, Jianglu Hu, Jiangtao Guan, Jianing Xu, Jianwei Cai, Jiarong Zhang, Jiawei Song, Jie Jiang, Jie Liu, Jieneng Yang, Jihong Zhang, Jin lv, Jing Zhao, Jinjian Li, JinXing Liu, Jun Zhao, Juntao Guo, Kai Wang, Kan Wu, Lei Fu, Lei He, Lei Wang, Li Liu, Liang Dong, Liya Zhan, Long Cheng, Long Xu, Mao Zheng, Meng Liu, Mengkang Hu, Nanli Chen, Peirui Chen, Peng He, Pengju Pan, Pengzhi Wei, Qi Yang, Qi Yi, Roberts Wang, Rongpeng Chen, Rui Sun, Rui Yang, Ruibin Chen, Ruixu Zhou, Shaofeng Zhang, Sheng Zhang, Shihao Xu, Shuaishuai Chang, Shulin Liu, Siqi Wang, Songjia Feng, Songling Yuan, Tao Zhang, Tianjiao Lang, Tongkai Li, Wei Deng, Wei Li, Weichao Wang, Weigang Zhang, Weixuan Sun, Wen Ouyang, Wenxiang Jiao, Wenzhi Sun, Wenzhuo Jia, Xiang Zhang, Xiangyu He, Xianshun Ren, Xiaoying Zhu, Xiaolong Guo, Xiaoxue Li, Xiaoyu Ma, Xican Lu, Xinhua Feng, Xinting Huang, Xinyu Guan, Xirui Li, Xu Zhang, Xudong Gao, Xun Luo, Xuxiang Qi, Yangkun Chen, Yangyu Tao, Yanling Xiao, Yantao Mai, Yanze Chen, Yao Ding, Yeting Yang, YiFan Song, Yifan Yang, Yijiao Zhu, Yinhe Wu, Yixian Liu, Yong Yang, Yuanjun Cai, Yuanlin Tu, Yue Zhang, Yufei Huang, YuHang Zhou, Yuhao Jiang, Yuhong Liu, Yuhui Hu, YuJin Lin, Yun Yang, Yunhao Wang, Yusong Zhang, Zekun Wu, Zelong Zhang, Zhan Yu, Zhaoliang Yang, Zhe Zhao, Zheng Li, Zhenyu Huang, Zhiguang Liu, Zhiqing Kui, Zhiyin Zeng, Zhiyuan Xiong, Zhuo Han, Zifan Wu, Zigang Geng, Zilong Zhao, Ziyan Tang, Ziyuan Zhu, Zonglei Zhu, Zhijiang Xu
As Large Language Models (LLMs) rapidly advance, we introduce Hunyuan-TurboS, a novel large hybrid Transformer-Mamba Mixture of Experts (MoE) model.
1 code implementation • 16 May 2025 • Haozheng Luo, Chenghao Qiu, Yimin Wang, Shang Wu, Jiahao Yu, Han Liu, Binghui Wang, Yan Chen
We propose the first unified adversarial attack benchmark for Genomic Foundation Models (GFMs), named GenoArmory.
no code implementations • 13 May 2025 • Badhan Kumar Das, Ajay Singh, Gengyan Zhao, Han Liu, Thomas J. Re, Dorin Comaniciu, Eli Gibson, Andreas Maier
Self-supervised pretrain techniques have been widely used to improve the downstream tasks' performance.
1 code implementation • 1 May 2025 • Haozheng Luo, Chenghao Qiu, Maojiang Su, Zhihan Zhou, Zoe Mehta, Guo Ye, Jerry Yao-Chieh Hu, Han Liu
Unlike existing GFM benchmarks, GERM offers the first comprehensive evaluation framework to systematically assess the vulnerability of GFMs to adversarial attacks.
no code implementations • 28 Apr 2025 • Hude Liu, Jerry Yao-Chieh Hu, Zhao Song, Han Liu
We establish the universal approximation capability of single-layer, single-head self- and cross-attention mechanisms with minimal attached structures.
1 code implementation • 22 Apr 2025 • Jerry Yao-Chieh Hu, Hude Liu, Hong-Yu Chen, Weimin Wu, Han Liu
We prove that with linear transformations, both (i) two-layer self-attention and (ii) one-layer self-attention followed by a softmax function are universal approximators for continuous sequence-to-sequence functions on compact domains.
no code implementations • 4 Apr 2025 • Badhan Kumar Das, Gengyan Zhao, Han Liu, Thomas J. Re, Dorin Comaniciu, Eli Gibson, Andreas Maier
Pretrain techniques, whether supervised or self-supervised, are widely used in deep learning to enhance model performance.
1 code implementation • 24 Mar 2025 • Zhenyu Pan, Han Liu
We present MetaSpatial, the first reinforcement learning (RL)-based framework designed to enhance 3D spatial reasoning in vision-language models (VLMs), enabling real-time 3D scene generation without the need for hard-coded optimizations.
1 code implementation • 13 Mar 2025 • Han Liu, Riqiang Gao, Sasa Grbic
However, due to the lack of early and disease-specific symptoms, most patients with PDAC are diagnosed at an advanced disease stage.
no code implementations • 28 Feb 2025 • Youngjin Yoo, Bogdan Georgescu, Yanbo Zhang, Sasa Grbic, Han Liu, Gabriela D. Aldea, Thomas J. Re, Jyotipriya Das, Poikavila Ullaskrishnan, Eva Eibenberger, Andrei Chekkoury, Uttam K. Bodanapally, Savvas Nicolaou, Pina C. Sanelli, Thomas J. Schroeppel, Yvonne W. Lui, Eli Gibson
Recent advancements in AI and medical imaging offer transformative potential in emergency head CT interpretation for reducing assessment times and improving accuracy in the face of an increasing request of such scans and a global shortage in radiologists.
no code implementations • 18 Feb 2025 • Bingning Wang, Haizhou Zhao, Huozhi Zhou, Liang Song, Mingyu Xu, Wei Cheng, Xiangrong Zeng, Yupeng Zhang, Yuqi Huo, Zecheng Wang, Zhengyun Zhao, Da Pan, Fei Kou, Fei Li, Fuzhong Chen, Guosheng Dong, Han Liu, Hongda Zhang, Jin He, Jinjie Yang, Kangxi Wu, Kegeng Wu, Lei Su, Linlin Niu, Linzhuang Sun, Mang Wang, Pengcheng Fan, Qianli Shen, Rihui Xin, Shunya Dang, Songchi Zhou, WeiPeng Chen, Wenjing Luo, Xin Chen, Xin Men, Xionghai Lin, Xuezhen Dong, Yan Zhang, Yifei Duan, Yuyan Zhou, Zhi Ma, Zhiying Wu
The current generation of large language models (LLMs) is typically designed for broad, general-purpose applications, while domain-specific LLMs, especially in vertical fields like medicine, remain relatively scarce.
no code implementations • 3 Feb 2025 • Chacha Chen, Han Liu, Jiamin Yang, Benjamin M. Mervak, Bora Kalaycioglu, Grace Lee, Emre Cakmakli, Matteo Bonatti, Sridhar Pudu, Osman Kahraman, Gul Gizem Pamuk, Aytekin Oto, Aritrick Chatterjee, Chenhao Tan
Building on existing tools for teaching prostate cancer diagnosis, we develop an interface and conduct two experiments to study how AI assistance and performance feedback shape the decision making of domain experts.
1 code implementation • 21 Jan 2025 • Riqiang Gao, Mamadou Diallo, Han Liu, Anthony Magliari, Jonathan Sackett, Wilko Verbakel, Sandra Meyers, Rafe McBeth, Masoud Zarepisheh, Simon Arberet, Martin Kraus, Florin C. Ghesu, Ali Kamen
Radiotherapy (RT) planning is complex, subjective, and time-intensive.
no code implementations • 15 Jan 2025 • Badhan Kumar Das, Gengyan Zhao, Han Liu, Thomas J. Re, Dorin Comaniciu, Eli Gibson, Andreas Maier
To address this limitation, we propose a 3D Adaptive Masked Autoencoders (AMAE) architecture that accommodates a variable number of 3D input contrasts per subject.
1 code implementation • 13 Jan 2025 • Han Liu, Yinwei Wei, Fan Liu, Wenjie Wang, Liqiang Nie, Tat-Seng Chua
In this paper, we develop a novel meta-learning-based multimodal fusion framework called Meta Multimodal Fusion (MetaMMF), which dynamically assigns parameters to the multimodal fusion function for each micro-video during its representation learning.
no code implementations • 9 Jan 2025 • Shuo Tong, Han Liu, Runyuan Guo, Xueqiong Tian, Wenqing Wang, Ding Liu, Youmin Zhang
To address these challenges, we propose a general framework named LLM-TKESS (large language model for text-based knowledge-embedded soft sensing), harnessing the powerful general problem-solving capabilities, cross-modal knowledge transfer abilities, and few-shot capabilities of LLM for enhanced soft sensing modeling.
no code implementations • 8 Jan 2025 • Zhenyu Pan, Xuefeng Song, Yunkun Wang, Rongyu Cao, Binhua Li, Yongbin Li, Han Liu
Code Large Language Models (LLMs) demonstrate great versatility in adapting to various downstream tasks, including code generation and completion, as well as bug detection and fixing.
no code implementations • 6 Jan 2025 • Shuo Tong, Han Liu, Runyuan Guo, Wenqing Wang, Xueqiong Tian, Lingyun Wei, Lin Zhang, Huayong Wu, Ding Liu, Youmin Zhang
To achieve this, we propose a novel framework called the Few-shot Uncertainty-aware and self-Explaining Soft Sensor (LLM-FUESS), which includes the Zero-shot Auxiliary Variable Selector (LLM-ZAVS) and the Uncertainty-aware Few-shot Soft Sensor (LLM-UFSS).
no code implementations • 5 Jan 2025 • Yuan Cao, Yihan He, Dennis Wu, Hong-Yu Chen, Jianqing Fan, Han Liu
We demonstrate that there exists a simple transformer model that can (i) estimate the conditional probabilities of the Bayesian network according to the context, and (ii) autoregressively generate a new sample according to the Bayesian network with estimated conditional probabilities.
no code implementations • 2 Jan 2025 • Yihan He, Yuan Cao, Hong-Yu Chen, Dennis Wu, Jianqing Fan, Han Liu
In this work, we study the capacities of Transformers in performing unsupervised learning.
no code implementations • CVPR 2025 • Han Liu, Peng Cui, Bingning Wang, WeiPeng Chen, Yupeng Zhang, Jun Zhu, Xiaolin Hu
Deep Neural Networks (DNNs) have achieved remarkable success in a variety of tasks, particularly in terms of prediction accuracy.
no code implementations • 30 Dec 2024 • Yibo Wen, Chenwei Xu, Jerry Yao-Chieh Hu, Han Liu
We present a three-stage framework for training deep learning models specializing in antibody sequence-structure co-design.
no code implementations • 30 Dec 2024 • Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu, Han Liu, Mladen Kolar
Despite this dilemma, the common practice of choosing batch sizes in language model training often prioritizes training efficiency -- employing either constant large sizes with data parallelism or implementing batch size warmup schedules.
1 code implementation • 20 Dec 2024 • Yixiong Huo, Guangfeng Jiang, Hongyang Wei, Ji Liu, Song Zhang, Han Liu, Xingliang Huang, Mingjie Lu, Jinzhang Peng, Dong Li, Lu Tian, Emad Barsoum
To address these issues, we propose EGSRAL, a 3D GS-based method that relies solely on training images without extra annotations.
no code implementations • 16 Dec 2024 • Zekai Li, Jintu Zheng, Ji Liu, Han Liu, Haowei Zhu, Zeping Li, Fuwei Yang, Haiduo Huang, Jinzhang Peng, Dong Li, Lu Tian, Emad Barsoum
To address these issues, we propose a fine-grained token-wise pruning approach for the LLMs, which presents a learnable router to adaptively identify the less important tokens and skip them across model blocks to reduce computational cost during inference.
no code implementations • 26 Nov 2024 • Jerry Yao-Chieh Hu, Weimin Wu, Yi-Chen Lee, Yu-Chao Huang, Minshuo Chen, Han Liu
We investigate the approximation and estimation rates of conditional diffusion transformers (DiTs) with classifier-free guidance.
no code implementations • 25 Nov 2024 • Weimin Wu, Maojiang Su, Jerry Yao-Chieh Hu, Zhao Song, Han Liu
We investigate the transformer's capability for in-context learning (ICL) to simulate the training process of deep models.
no code implementations • 25 Nov 2024 • Jerry Yao-Chieh Hu, Wei-Po Wang, Ammar Gilani, Chenyang Li, Zhao Song, Han Liu
Our key contributions are prompt tuning on \textit{single-head} transformers with only a \textit{single} self-attention layer: (i) is universal, and (ii) supports efficient (even almost-linear time) algorithms under the Strong Exponential Time Hypothesis (SETH).
no code implementations • 16 Nov 2024 • Zihao Li, Yuan Cao, Cheng Gao, Yihan He, Han Liu, Jason M. Klusowski, Jianqing Fan, Mengdi Wang
Transformers have achieved great success in recent years.
no code implementations • 8 Nov 2024 • Jerry Yao-Chieh Hu, Erzhi Liu, Han Liu, Zhao Song, Lichen Zhang
Given a database of bit strings $A_1,\ldots, A_m\in \{0, 1\}^n$, a fundamental data structure task is to estimate the distances between a given query $B\in \{0, 1\}^n$ with all the strings in the database.
3 code implementations • 4 Nov 2024 • Xingwu Sun, Yanfeng Chen, Yiqing Huang, Ruobing Xie, Jiaqi Zhu, Kai Zhang, Shuaipeng Li, Zhen Yang, Jonny Han, Xiaobo Shu, Jiahao Bu, Zhongzhi Chen, Xuemeng Huang, Fengzong Lian, Saiyong Yang, Jianfeng Yan, Yuyuan Zeng, Xiaoqin Ren, Chao Yu, Lulu Wu, Yue Mao, Jun Xia, Tao Yang, Suncong Zheng, Kan Wu, Dian Jiao, Jinbao Xue, Xipeng Zhang, Decheng Wu, Kai Liu, Dengpeng Wu, Guanghui Xu, Shaohua Chen, Shuang Chen, Xiao Feng, Yigeng Hong, Junqiang Zheng, Chengcheng Xu, Zongwei Li, Xiong Kuang, Jianglu Hu, Yiqi Chen, Yuchi Deng, Guiyang Li, Ao Liu, Chenchen Zhang, Shihui Hu, Zilong Zhao, Zifan Wu, Yao Ding, Weichao Wang, Han Liu, Roberts Wang, Hao Fei, Peijie Yu, Ze Zhao, Xun Cao, Hai Wang, Fusheng Xiang, Mengyuan Huang, Zhiyuan Xiong, Bin Hu, Xuebin Hou, Lei Jiang, Jianqiang Ma, Jiajia Wu, Yaping Deng, Yi Shen, Qian Wang, Weijie Liu, Jie Liu, Meng Chen, Liang Dong, Weiwen Jia, Hu Chen, Feifei Liu, Rui Yuan, Huilin Xu, Zhenxiang Yan, Tengfei Cao, Zhichao Hu, Xinhua Feng, Dong Du, TingHao Yu, Yangyu Tao, Feng Zhang, Jianchen Zhu, Chengzhong Xu, Xirui Li, Chong Zha, Wen Ouyang, Yinben Xia, Xiang Li, Zekun He, Rongpeng Chen, Jiawei Song, Ruibin Chen, Fan Jiang, Chongqing Zhao, Bo wang, Hao Gong, Rong Gan, Winston Hu, Zhanhui Kang, Yong Yang, Yuhong Liu, Di Wang, Jie Jiang
In this paper, we introduce Hunyuan-Large, which is currently the largest open-source Transformer-based mixture of experts model, with a total of 389 billion parameters and 52 billion activation parameters, capable of handling up to 256K tokens.
no code implementations • 1 Nov 2024 • Zhi Zhang, Chris Chow, Yasi Zhang, Yanchao Sun, Haochen Zhang, Eric Hanchen Jiang, Han Liu, Furong Huang, Yuchen Cui, Oscar Hernan Madrid Padilla
Lifelong reinforcement learning (RL) has been developed as a paradigm for extending single-task RL to more realistic, dynamic settings.
no code implementations • 31 Oct 2024 • Cheng Gao, Yuan Cao, Zihao Li, Yihan He, Mengdi Wang, Han Liu, Jason Matthew Klusowski, Jianqing Fan
First, we construct the mean-field limit of large-scale Transformers, showing that as the model width and depth go to infinity, gradient flow converges to the Wasserstein gradient flow, which is represented by a partial differential equation.
no code implementations • 30 Oct 2024 • Jerry Yao-Chieh Hu, Dennis Wu, Han Liu
We show that the optimal capacity of KHMs occurs when the feature space allows memories to form an optimal spherical code.
1 code implementation • MM '24: Proceedings of the 32nd ACM International Conference on Multimedia 2024 • Jian Chen, Wei Wang, Yuzhu Hu, Junxin Chen, Han Liu, Xiping Hu
Our approach encompasses a novel topic-guided context-aware module and a topic-guided attention mechanism, enabling the extraction of comprehensive topic context features from stickers sharing the same topic ID, significantly enhancing emotion recognition accuracy.
no code implementations • 15 Oct 2024 • Han Liu, Xianfeng Tang, Tianlang Chen, Jiapeng Liu, Indu Indu, Henry Peng Zou, Peng Dai, Roberto Fernandez Galan, Michael D Porter, Dongmei Jia, Ning Zhang, Lian Xiong
The fashion industry is one of the leading domains in the global e-commerce sector, prompting major online retailers to employ recommendation systems for product suggestions and customer convenience.
no code implementations • 9 Oct 2024 • Zhengyu Hu, Yichuan Li, Zhengyu Chen, Jingang Wang, Han Liu, Kyumin Lee, Kaize Ding
Textual Attributed Graphs (TAGs) are crucial for modeling complex real-world systems, yet leveraging large language models (LLMs) for TAGs presents unique challenges due to the gap between sequential text processing and graph-structured data.
1 code implementation • 6 Oct 2024 • Dewei Hu, Hao Li, Han Liu, Jiacheng Wang, Xing Yao, Daiwei Lu, Ipek Oguz
Subsequently, we sample on the target domain with binary vessel masks from the source domain to get paired data, i. e., target domain synthetic images conditioned on the binary vessel map.
no code implementations • 4 Oct 2024 • Aofei Chang, Jiaqi Wang, Han Liu, Parminder Bhatia, Cao Xiao, Ting Wang, Fenglong Ma
Parameter Efficient Fine-Tuning (PEFT) offers an efficient solution for fine-tuning large pretrained language models for downstream tasks.
1 code implementation • 2 Oct 2024 • Zhenyu Pan, Rongyu Cao, Yongchang Cao, Yingwei Ma, Binhua Li, Fei Huang, Han Liu, Yongbin Li
Code completion, a key downstream task in code generation, is one of the most frequent and impactful methods for enhancing developer productivity in software development.
no code implementations • 20 Sep 2024 • Jaeyeon Jang, Diego Klabjan, Han Liu, Nital S. Patel, Xiuqi Li, Balakrishnan Ananthanarayanan, Husam Dauod, Tzung-Han Juang
Real-time dynamic scheduling is a crucial but notoriously challenging task in modern manufacturing processes due to its high decision complexity.
Multi-agent Reinforcement Learning
reinforcement-learning
+3
no code implementations • 11 Sep 2024 • Yuanhaur Chang, Han Liu, Chenyang Lu, Ning Zhang
The integration of artificial intelligence (AI) and machine learning (ML) into healthcare systems holds great promise for enhancing patient care and care delivery efficiency; however, it also exposes sensitive data and system integrity to potential cyberattacks.
1 code implementation • 6 Sep 2024 • Lucas W. Remedios, Han Liu, Samuel W. Remedios, Lianrui Zuo, Adam M. Saunders, Shunxing Bao, Yuankai Huo, Alvin C. Powers, John Virostko, Bennett A. Landman
We trained a collection of basic UNets with different fusion points, spanning from early to late, to assess how early through late fusion influenced segmentation performance on imperfectly aligned images.
no code implementations • 3 Sep 2024 • Erzhi Liu, Jerry Yao-Chieh Hu, Alex Reneau, Zhao Song, Han Liu
In this paper, we improve the best previous result [Backurs, Lin, Mahabadi, Silwal, and Tarnawski, ICLR 2024] in three aspects: - We reduce query time by a factor of $\alpha^{-1} \log n$.
no code implementations • 8 Aug 2024 • Hao Li, Han Liu, Heinrich von Busch, Robert Grimm, Henkjan Huisman, Angela Tong, David Winkel, Tobias Penzkofer, Ivan Shabunin, Moon Hyung Choi, Qingsong Yang, Dieter Szolar, Steven Shea, Fergus Coakley, Mukesh Harisinghani, Ipek Oguz, Dorin Comaniciu, Ali Kamen, Bin Lou
This method translates diffusion-weighted imaging (DWI) acquisitions, including apparent diffusion coefficient (ADC) and individual DW images acquired using various b-values, to align with the style of images acquired using b-values recommended by Prostate Imaging Reporting and Data System (PI-RADS) guidelines.
no code implementations • 24 Jul 2024 • Kaixuan Li, Jian Zhang, Sen Chen, Han Liu, Yang Liu, Yixiang Chen
In this paper, we propose PatchFinder, a two-phase framework with end-to-end correlation learning for better-tracing security patches.
no code implementations • 1 Jul 2024 • Jerry Yao-Chieh Hu, Weimin Wu, Zhao Song, Han Liu
For backward computation, we leverage the low-rank structure within the gradient computation of DiTs training for possible algorithmic speedup.
1 code implementation • 22 Jun 2024 • Han Liu, Hao Li, Jiacheng Wang, Yubo Fan, Zhoubing Xu, Ipek Oguz
Recently, in silico labeling has emerged as a promising alternative, aiming to use machine learning models to directly predict the fluorescently labeled images from label-free microscopy.
no code implementations • 20 Jun 2024 • Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu, Han Liu, Mladen Kolar
Despite an understanding of their convergence and the importance of batch sizes for training efficiency and generalization, optimal batch sizes for local gradient methods are difficult to determine.
no code implementations • 18 Jun 2024 • Xin Yu, Qi Yang, Han Liu, Ho Hin Lee, Yucheng Tang, Lucas W. Remedios, Michael E. Kim, Rendong Zhang, Shunxing Bao, Yuankai Huo, Ann Zenobia Moore, Luigi Ferrucci, Bennett A. Landman
2D single-slice abdominal computed tomography (CT) enables the assessment of body habitus and organ health with low radiation exposure.
no code implementations • 17 Jun 2024 • Han Liu, Yupeng Zhang, Bingning Wang, WeiPeng Chen, Xiaolin Hu
Deep Neural Networks (DNNs) excel in various domains but face challenges in providing accurate uncertainty estimates, which are crucial for high-stakes applications.
no code implementations • 8 Jun 2024 • Chengyuan Deng, Yiqun Duan, Xin Jin, Heng Chang, Yijun Tian, Han Liu, Yichen Wang, Kuofeng Gao, Henry Peng Zou, Yiqiao Jin, Yijia Xiao, Shenghao Wu, Zongxing Xie, Weimin Lyu, Sihong He, Lu Cheng, Haohan Wang, Jun Zhuang
Large Language Models (LLMs) have achieved unparalleled success across diverse language modeling tasks in recent years.
no code implementations • 5 Jun 2024 • Jerry Yao-Chieh Hu, Maojiang Su, En-Jui Kuo, Zhao Song, Han Liu
We study the computational limits of Low-Rank Adaptation (LoRA) for finetuning transformer-based models using fine-grained complexity theory.
no code implementations • 3 Jun 2024 • Haozheng Luo, Jiahao Yu, Wenxin Zhang, Jialong Li, Jerry Yao-Chieh Hu, Xinyu Xing, Han Liu
We introduce a low-resource safety enhancement method for aligning large language models (LLMs) without the need for supervised fine-tuning (SFT) or reinforcement learning from human feedback (RLHF).
no code implementations • 31 May 2024 • Jiahao Yu, Haozheng Luo, Jerry Yao-Chieh Hu, Wenbo Guo, Han Liu, Xinyu Xing
Attackers carefully craft jailbreaking prompts such that a target LLM will respond to the harmful question.
no code implementations • 30 May 2024 • Han Liu, Peng Cui, Bingning Wang, Jun Zhu, Xiaolin Hu
Deep Neural Networks (DNNs) have achieved remarkable success in a variety of tasks, especially when it comes to prediction accuracy.
no code implementations • 28 May 2024 • Zhenyu Pan, Haozheng Luo, Manling Li, Han Liu
Methodologically, we propose a resource-efficiency Hopfield retriever to enhance the efficiency and accuracy of conversational information retrieval within our actions.
no code implementations • 22 May 2024 • Zhenyu Pan, Yoonsung Jeong, Xiaoda Liu, Han Liu
We propose a heterogeneous graph mamba network (HGMN) as the first exploration in leveraging the selective state space models (SSSMs) for heterogeneous graph learning.
no code implementations • 11 May 2024 • QingGuo Qi, Hongyang Chen, Minhao Cheng, Han Liu
Additionally, for link prediction tasks on discrete dynamic graphs, the requirement of substantial GPU memory to store embeddings of all nodes hinders the scalability of existing models.
no code implementations • 6 May 2024 • Han Liu, Siyang Zhao, Xiaotong Zhang, Feng Zhang, Wei Wang, Fenglong Ma, Hongyang Chen, Hong Yu, Xianchao Zhang
Few-shot and zero-shot text classification aim to recognize samples from novel classes with limited labeled samples or no labeled samples at all.
no code implementations • 25 Apr 2024 • Han Liu, Yinwei Wei, Xuemeng Song, Weili Guan, Yuan-Fang Li, Liqiang Nie
Multimodal recommendation aims to recommend user-preferred candidates based on her/his historically interacted items and associated multimodal information.
2 code implementations • 23 Apr 2024 • Hao Li, Han Liu, Dewei Hu, Jiacheng Wang, Ipek Oguz
(3) Corrective learning.
no code implementations • 13 Apr 2024 • Henry Peng Zou, Gavin Heqing Yu, Ziwei Fan, Dan Bu, Han Liu, Peng Dai, Dongmei Jia, Cornelia Caragea
To address these issues, we introduce EIVEN, a data- and parameter-efficient generative framework that pioneers the use of multimodal LLM for implicit attribute value extraction.
1 code implementation • 5 Apr 2024 • Jerry Yao-Chieh Hu, Bo-Yu Chen, Dennis Wu, Feng Ruan, Han Liu
We present a nonparametric construction for deep learning compatible modern Hopfield models and utilize this framework to debut an efficient variant.
1 code implementation • 4 Apr 2024 • Jerry Yao-Chieh Hu, Pei-Hsuan Chang, Robin Luo, Hong-Yu Chen, Weijian Li, Wei-Po Wang, Han Liu
We introduce an Outlier-Efficient Modern Hopfield Model (termed $\mathrm{OutEffHop}$) and use it to address the outlier inefficiency problem of {training} gigantic transformer-based models.
Ranked #1 on
Quantization
on Wiki-40B
1 code implementation • 4 Apr 2024 • Dennis Wu, Jerry Yao-Chieh Hu, Teng-Yun Hsiao, Han Liu
Specifically, we accomplish this by constructing a separation loss $\mathcal{L}_\Phi$ that separates the local minima of kernelized energy by separating stored memory patterns in kernel space.
1 code implementation • 4 Apr 2024 • Chenwei Xu, Yu-Chao Huang, Jerry Yao-Chieh Hu, Weijian Li, Ammar Gilani, Hsi-Sheng Goan, Han Liu
We introduce the \textbf{B}i-Directional \textbf{S}parse \textbf{Hop}field Network (\textbf{BiSHop}), a novel end-to-end framework for deep tabular learning.
1 code implementation • 26 Mar 2024 • Zhenyu Pan, Haozheng Luo, Manling Li, Han Liu
We present a Chain-of-Action (CoA) framework for multimodal and retrieval-augmented Question-Answering (QA).
Ranked #1 on
Question Answering
on TruthfulQA
(EM metric)
1 code implementation • 20 Mar 2024 • Zhihan Zhou, Qixiang Fang, Leonardo Neves, Francesco Barbieri, Yozen Liu, Han Liu, Maarten W. Bos, Ron Dotsch
Furthermore, we introduce a novel training objective named future W-behavior prediction to transcend the limitations of next-token prediction by forecasting a broader horizon of upcoming user behaviors.
no code implementations • 26 Feb 2024 • Han Liu, Liantang Li
Language model intelligence is revolutionizing the way we program materials simulations.
no code implementations • 17 Feb 2024 • Tim Tsz-Kit Lau, Han Liu, Mladen Kolar
The choice of batch sizes in minibatch stochastic gradient optimizers is critical in large-scale model training for both optimization and generalization performance.
no code implementations • 16 Feb 2024 • Ziyi Yin, Muchao Ye, Tianrong Zhang, Jiaqi Wang, Han Liu, Jinghui Chen, Ting Wang, Fenglong Ma
Correspondingly, we propose a novel VQAttack model, which can iteratively generate both image and text perturbations with the designed modules: the large language model (LLM)-enhanced image attack and the cross-modal joint attack module.
2 code implementations • 13 Feb 2024 • Zhihan Zhou, Weimin Wu, Harrison Ho, Jiayi Wang, Lizhen Shi, Ramana V Davuluri, Zhong Wang, Han Liu
We introduce DNABERT-S, a tailored genome model that develops species-aware embeddings to naturally cluster and segregate DNA sequences of different species in the embedding space.
no code implementations • 7 Feb 2024 • Jerry Yao-Chieh Hu, Thomas Lin, Zhao Song, Han Liu
Specifically, we establish an upper bound criterion for the norm of input query patterns and memory patterns.
1 code implementation • NeurIPS 2023 • Han Liu, Zhi Xu, Xiaotong Zhang, Feng Zhang, Fenglong Ma, Hongyang Chen, Hong Yu, Xianchao Zhang
Black-box hard-label adversarial attack on text is a practical and challenging task, as the text data space is inherently discrete and non-differentiable, and only the predicted label is accessible.
no code implementations • 30 Jan 2024 • Linyao Yang, Hongyang Chen, Xiao Wang, Jing Yang, Fei-Yue Wang, Han Liu
The final prediction of the equivalent entity is derived from the LLM's output.
no code implementations • 29 Jan 2024 • Yuqiang Sun, Daoyuan Wu, Yue Xue, Han Liu, Wei Ma, Lyuye Zhang, Yang Liu, Yingjiu Li
In this paper, we aim to decouple LLMs' vulnerability reasoning from other capabilities, such as vulnerability knowledge adoption, context information retrieval, and advanced prompt schemes.
1 code implementation • 20 Jan 2024 • Suhan Cui, Jiaqi Wang, Yuan Zhong, Han Liu, Ting Wang, Fenglong Ma
The widespread adoption of Electronic Health Record (EHR) systems in healthcare institutes has generated vast amounts of medical data, offering significant opportunities for improving healthcare services through deep learning techniques.
1 code implementation • 28 Dec 2023 • Dennis Wu, Jerry Yao-Chieh Hu, Weijian Li, Bo-Yu Chen, Han Liu
We present STanHop-Net (Sparse Tandem Hopfield Network) for multivariate time series prediction with memory-enhanced capabilities.
no code implementations • 28 Dec 2023 • Chenwei Xu, Jerry Yao-Chieh Hu, Aakaash Narayanan, Mattson Thieme, Vladimir Nagaslaev, Mark Austin, Jeremy Arnold, Jose Berlioz, Pierrick Hanlet, Aisha Ibrahim, Dennis Nicklaus, Jovan Mitrevski, Jason Michael St. John, Gauri Pradhan, Andrea Saewert, Kiyomi Seiya, Brian Schupbach, Randy Thurman-Keup, Nhan Tran, Rui Shi, Seda Ogrenci, Alexis Maya-Isabelle Shuping, Kyle Hazelwood, Han Liu
We introduce a novel Proximal Policy Optimization (PPO) algorithm aimed at addressing the challenge of maintaining a uniform proton beam intensity delivery in the Muon to Electron Conversion Experiment (Mu2e) at Fermi National Accelerator Laboratory (Fermilab).
no code implementations • NeurIPS 2014 • Quanquan Gu, Zhaoran Wang, Han Liu
In particular, under a weak assumption on the magnitude of the population projection matrix, one estimator within this family exactly recovers the true support with high probability, has exact rank-$k$, and attains a $\sqrt{s/n}$ statistical rate of convergence with $s$ being the subspace sparsity level and $n$ the sample size.
1 code implementation • 21 Nov 2023 • Han Liu, Yubo Fan, Zhoubing Xu, Benoit M. Dawant, Ipek Oguz
In this paper, we present our solution to tackle the multi-institutional unsupervised domain adaptation for the crossMoDA 2023 challenge.
1 code implementation • 13 Nov 2023 • Hao Li, Han Liu, Dewei Hu, Jiacheng Wang, Ipek Oguz
In this paper, we assess the test-time variability for interactive medical image segmentation with diverse point prompts.
1 code implementation • 30 Oct 2023 • Hao Li, Han Liu, Dewei Hu, Jiacheng Wang, Ipek Oguz
To address prevalent issues in medical imaging, such as data acquisition challenges and label availability, transfer learning from natural to medical image domains serves as a viable strategy to produce reliable segmentation results.
no code implementations • 29 Oct 2023 • Han Liu, Xingshuo Huang, Xiaotong Zhang, Qimai Li, Fenglong Ma, Wei Wang, Hongyang Chen, Hong Yu, Xianchao Zhang
Decision-based methods have shown to be effective in black-box adversarial attacks, as they can obtain satisfactory performance and only require to access the final model prediction.
1 code implementation • NeurIPS 2023 • Ziyi Yin, Muchao Ye, Tianrong Zhang, Tianyu Du, Jinguo Zhu, Han Liu, Jinghui Chen, Ting Wang, Fenglong Ma
In this paper, we aim to investigate a new yet practical task to craft image and text perturbations using pre-trained VL models to attack black-box fine-tuned models on different downstream tasks.
1 code implementation • 28 Sep 2023 • Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen
The increasing capabilities of large language models (LLMs) raise opportunities for artificial general intelligence but concurrently amplify safety concerns, such as potential misuse of AI systems, necessitating effective AI alignment.
1 code implementation • NeurIPS 2023 • Jerry Yao-Chieh Hu, Donglin Yang, Dennis Wu, Chenwei Xu, Bo-Yu Chen, Han Liu
Building upon this, we derive the sparse memory retrieval dynamics from the sparse energy function and show its one-step approximation is equivalent to the sparse-structured attention.
1 code implementation • 20 Aug 2023 • Xing Yao, Han Liu, Dewei Hu, Daiwei Lu, Ange Lou, Hao Li, Ruining Deng, Gabriel Arenas, Baris Oguz, Nadav Schwartz, Brett C Byram, Ipek Oguz
The method couples multi-box prompt augmentation and an aleatoric uncertainty-based false-negative (FN) and false-positive (FP) correction (FNPC) strategy.
2 code implementations • 11 Aug 2023 • Hao Li, Han Liu, Dewei Hu, Xing Yao, Jiacheng Wang, Ipek Oguz
We fuse the information from the convolutional encoder and the transformer at the skip connections of different resolutions to form the final segmentation.
1 code implementation • 7 Aug 2023 • Yuqiang Sun, Daoyuan Wu, Yue Xue, Han Liu, Haijun Wang, Zhengzi Xu, Xiaofei Xie, Yang Liu
Instead of relying solely on GPT to identify vulnerabilities, which can lead to high false positives and is limited by GPT's pre-trained knowledge, we utilize GPT as a versatile code understanding tool.
1 code implementation • 22 Jul 2023 • Han Liu, Hao Li, Xing Yao, Yubo Fan, Dewei Hu, Benoit Dawant, Vishwesh Nath, Zhoubing Xu, Ipek Oguz
Cold-start AL is highly relevant in many practical scenarios but has been under-explored, especially for 3D medical segmentation tasks requiring substantial annotation effort.
no code implementations • 15 Jul 2023 • Guanlin Liu, Zhihan Zhou, Han Liu, Lifeng Lai
Robust reinforcement learning (RL) aims to find a policy that optimizes the worst-case performance in the face of uncertainties.
no code implementations • 13 Jul 2023 • Jaeyeon Jang, Diego Klabjan, Han Liu, Nital S. Patel, Xiuqi Li, Balakrishnan Ananthanarayanan, Husam Dauod, Tzung-Han Juang
This paper proposes a novel multi-agent reinforcement learning (MARL) method to learn multiple coordinated agents under directed acyclic graph (DAG) constraints.
no code implementations • 1 Jul 2023 • Dewei Hu, Hao Li, Han Liu, Xing Yao, Jiacheng Wang, Ipek Oguz
We map the intensity image and the tensor field to a latent space for feature extraction.
1 code implementation • 1 Jul 2023 • Yongshang Li, Ronggui Ma, Han Liu, Gaoli Cheng
Deep learning plays an important role in crack segmentation, but most work utilize off-the-shelf or improved models that have not been specifically developed for this task.
6 code implementations • 26 Jun 2023 • Zhihan Zhou, Yanrong Ji, Weijian Li, Pratik Dutta, Ramana Davuluri, Han Liu
Decoding the linguistic intricacies of the genome is a crucial problem in biology, and pre-trained foundational models such as DNABERT and Nucleotide Transformer have made significant strides in this area.
Ranked #1 on
Core Promoter Detection
on GUE
1 code implementation • 9 Jun 2023 • Alex Reneau, Jerry Yao-Chieh Hu, Chenwei Xu, Weijian Li, Ammar Gilani, Han Liu
We introduce the concept of programmable feature engineering for time series modeling and propose a feature programming framework.
1 code implementation • 25 May 2023 • Tim Tsz-Kit Lau, Han Liu, Thomas Pock
We study the problem of approximate sampling from non-log-concave distributions, e. g., Gaussian mixtures, which is often challenging even in low dimensions due to their multimodality.
no code implementations • 27 Apr 2023 • Han Liu, Zhoubing Xu, Riqiang Gao, Hao Li, Jianing Wang, Guillaume Chabin, Ipek Oguz, Sasa Grbic
We revisit the problem from a perspective of partial label supervision signals and identify two signals derived from ground truth and one from pseudo labels.
no code implementations • 26 Mar 2023 • Han Liu, Feng Zhang, Xiaotong Zhang, Siyang Zhao, Fenglong Ma, Xiao-Ming Wu, Hongyang Chen, Hong Yu, Xianchao Zhang
Distribution estimation has been demonstrated as one of the most effective approaches in dealing with few-shot image classification, as the low-level patterns and underlying representations can be easily transferred across different tasks in computer vision domain.
Few-Shot Image Classification
Few-Shot Text Classification
+2
no code implementations • 9 Mar 2023 • Jiacheng Wang, Hao Li, Han Liu, Dewei Hu, Daiwei Lu, Keejin Yoon, Kelsey Barter, Francesca Bagnato, Ipek Oguz
A potential solution is to leverage the information available in large public datasets in conjunction with a target dataset which only has limited labeled data.
1 code implementation • 6 Mar 2023 • Han Liu, Yizhou Tian, Chacha Chen, Shi Feng, Yuxin Chen, Chenhao Tan
Despite the promising performance of supervised learning, representations learned by supervised models may not align well with human intuitions: what models consider as similar examples can be perceived as distinct by humans.
1 code implementation • 4 Feb 2023 • Yuxin Zhang, Mingbao Lin, Xunchao Li, Han Liu, Guozhi Wang, Fei Chao, Shuai Ren, Yafei Wen, Xiaoxin Chen, Rongrong Ji
In this paper, we launch the first study on accelerating demoireing networks and propose a dynamic demoireing acceleration method (DDA) towards a real-time deployment on mobile devices.
1 code implementation • 13 Jan 2023 • Han Liu, Yinwei Wei, Jianhua Yin, Liqiang Nie
Towards this end, existing methods tend to code users by modeling their Hamming similarities with the items they historically interact with, which are termed as the first-order similarities in this work.
1 code implementation • CVPR 2023 • Han Liu, Yuhao Wu, Zhiyuan Yu, Yevgeniy Vorobeychik, Ning Zhang
LiDAR-based perception is a central component of autonomous driving, playing a key role in tasks such as vehicle localization and obstacle detection.
1 code implementation • CVPR 2023 • Han Liu, Yuhao Wu, Shixuan Zhai, Bo Yuan, Ning Zhang
The field of text-to-image generation has made remarkable strides in creating high-fidelity and photorealistic images.
no code implementations • 16 Dec 2022 • Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Fabian Isensee, Tim J. Adler, Patrick Godau, Veronika Cheplygina, Michal Kozubek, Sharib Ali, Anubha Gupta, Jan Kybic, Alison Noble, Carlos Ortiz de Solórzano, Samiksha Pachade, Caroline Petitjean, Daniel Sage, Donglai Wei, Elizabeth Wilden, Deepak Alapatt, Vincent Andrearczyk, Ujjwal Baid, Spyridon Bakas, Niranjan Balu, Sophia Bano, Vivek Singh Bawa, Jorge Bernal, Sebastian Bodenstedt, Alessandro Casella, Jinwook Choi, Olivier Commowick, Marie Daum, Adrien Depeursinge, Reuben Dorent, Jan Egger, Hannah Eichhorn, Sandy Engelhardt, Melanie Ganz, Gabriel Girard, Lasse Hansen, Mattias Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Hyunjeong Kim, Bennett Landman, Hongwei Bran Li, Jianning Li, Jun Ma, Anne Martel, Carlos Martín-Isla, Bjoern Menze, Chinedu Innocent Nwoye, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Carole Sudre, Kimberlin Van Wijnen, Armine Vardazaryan, Tom Vercauteren, Martin Wagner, Chuanbo Wang, Moi Hoon Yap, Zeyun Yu, Chun Yuan, Maximilian Zenk, Aneeq Zia, David Zimmerer, Rina Bao, Chanyeol Choi, Andrew Cohen, Oleh Dzyubachyk, Adrian Galdran, Tianyuan Gan, Tianqi Guo, Pradyumna Gupta, Mahmood Haithami, Edward Ho, Ikbeom Jang, Zhili Li, Zhengbo Luo, Filip Lux, Sokratis Makrogiannis, Dominik Müller, Young-tack Oh, Subeen Pang, Constantin Pape, Gorkem Polat, Charlotte Rosalie Reed, Kanghyun Ryu, Tim Scherr, Vajira Thambawita, Haoyu Wang, Xinliang Wang, Kele Xu, Hung Yeh, Doyeob Yeo, Yixuan Yuan, Yan Zeng, Xin Zhao, Julian Abbing, Jannes Adam, Nagesh Adluru, Niklas Agethen, Salman Ahmed, Yasmina Al Khalil, Mireia Alenyà, Esa Alhoniemi, Chengyang An, Talha Anwar, Tewodros Weldebirhan Arega, Netanell Avisdris, Dogu Baran Aydogan, Yingbin Bai, Maria Baldeon Calisto, Berke Doga Basaran, Marcel Beetz, Cheng Bian, Hao Bian, Kevin Blansit, Louise Bloch, Robert Bohnsack, Sara Bosticardo, Jack Breen, Mikael Brudfors, Raphael Brüngel, Mariano Cabezas, Alberto Cacciola, Zhiwei Chen, Yucong Chen, Daniel Tianming Chen, Minjeong Cho, Min-Kook Choi, Chuantao Xie Chuantao Xie, Dana Cobzas, Julien Cohen-Adad, Jorge Corral Acero, Sujit Kumar Das, Marcela de Oliveira, Hanqiu Deng, Guiming Dong, Lars Doorenbos, Cory Efird, Sergio Escalera, Di Fan, Mehdi Fatan Serj, Alexandre Fenneteau, Lucas Fidon, Patryk Filipiak, René Finzel, Nuno R. Freitas, Christoph M. Friedrich, Mitchell Fulton, Finn Gaida, Francesco Galati, Christoforos Galazis, Chang Hee Gan, Zheyao Gao, Shengbo Gao, Matej Gazda, Beerend Gerats, Neil Getty, Adam Gibicar, Ryan Gifford, Sajan Gohil, Maria Grammatikopoulou, Daniel Grzech, Orhun Güley, Timo Günnemann, Chunxu Guo, Sylvain Guy, Heonjin Ha, Luyi Han, Il Song Han, Ali Hatamizadeh, Tian He, Jimin Heo, Sebastian Hitziger, SeulGi Hong, Seungbum Hong, Rian Huang, Ziyan Huang, Markus Huellebrand, Stephan Huschauer, Mustaffa Hussain, Tomoo Inubushi, Ece Isik Polat, Mojtaba Jafaritadi, SeongHun Jeong, Bailiang Jian, Yuanhong Jiang, Zhifan Jiang, Yueming Jin, Smriti Joshi, Abdolrahim Kadkhodamohammadi, Reda Abdellah Kamraoui, Inha Kang, Junghwa Kang, Davood Karimi, April Khademi, Muhammad Irfan Khan, Suleiman A. Khan, Rishab Khantwal, Kwang-Ju Kim, Timothy Kline, Satoshi Kondo, Elina Kontio, Adrian Krenzer, Artem Kroviakov, Hugo Kuijf, Satyadwyoom Kumar, Francesco La Rosa, Abhi Lad, Doohee Lee, Minho Lee, Chiara Lena, Hao Li, Ling Li, Xingyu Li, Fuyuan Liao, Kuanlun Liao, Arlindo Limede Oliveira, Chaonan Lin, Shan Lin, Akis Linardos, Marius George Linguraru, Han Liu, Tao Liu, Di Liu, Yanling Liu, João Lourenço-Silva, Jingpei Lu, Jiangshan Lu, Imanol Luengo, Christina B. Lund, Huan Minh Luu, Yi Lv, Uzay Macar, Leon Maechler, Sina Mansour L., Kenji Marshall, Moona Mazher, Richard McKinley, Alfonso Medela, Felix Meissen, Mingyuan Meng, Dylan Miller, Seyed Hossein Mirjahanmardi, Arnab Mishra, Samir Mitha, Hassan Mohy-ud-Din, Tony Chi Wing Mok, Gowtham Krishnan Murugesan, Enamundram Naga Karthik, Sahil Nalawade, Jakub Nalepa, Mohamed Naser, Ramin Nateghi, Hammad Naveed, Quang-Minh Nguyen, Cuong Nguyen Quoc, Brennan Nichyporuk, Bruno Oliveira, David Owen, Jimut Bahan Pal, Junwen Pan, Wentao Pan, Winnie Pang, Bogyu Park, Vivek Pawar, Kamlesh Pawar, Michael Peven, Lena Philipp, Tomasz Pieciak, Szymon Plotka, Marcel Plutat, Fattaneh Pourakpour, Domen Preložnik, Kumaradevan Punithakumar, Abdul Qayyum, Sandro Queirós, Arman Rahmim, Salar Razavi, Jintao Ren, Mina Rezaei, Jonathan Adam Rico, ZunHyan Rieu, Markus Rink, Johannes Roth, Yusely Ruiz-Gonzalez, Numan Saeed, Anindo Saha, Mostafa Salem, Ricardo Sanchez-Matilla, Kurt Schilling, Wei Shao, Zhiqiang Shen, Ruize Shi, Pengcheng Shi, Daniel Sobotka, Théodore Soulier, Bella Specktor Fadida, Danail Stoyanov, Timothy Sum Hon Mun, Xiaowu Sun, Rong Tao, Franz Thaler, Antoine Théberge, Felix Thielke, Helena Torres, Kareem A. Wahid, Jiacheng Wang, Yifei Wang, Wei Wang, Xiong Wang, Jianhui Wen, Ning Wen, Marek Wodzinski, Ye Wu, Fangfang Xia, Tianqi Xiang, Chen Xiaofei, Lizhan Xu, Tingting Xue, Yuxuan Yang, Lin Yang, Kai Yao, Huifeng Yao, Amirsaeed Yazdani, Michael Yip, Hwanseung Yoo, Fereshteh Yousefirizi, Shunkai Yu, Lei Yu, Jonathan Zamora, Ramy Ashraf Zeineldin, Dewen Zeng, Jianpeng Zhang, Bokai Zhang, Jiapeng Zhang, Fan Zhang, Huahong Zhang, Zhongchen Zhao, Zixuan Zhao, Jiachen Zhao, Can Zhao, Qingshuo Zheng, Yuheng Zhi, Ziqi Zhou, Baosheng Zou, Klaus Maier-Hein, Paul F. Jäger, Annette Kopp-Schneider, Lena Maier-Hein
Of these, 84% were based on standard architectures.
no code implementations • 6 Dec 2022 • Tong Xie, Yuwei Wan, Weijian Li, Qingyuan Linghu, Shaozhou Wang, Yalun Cai, Han Liu, Chunyu Kit, Clara Grazian, Bram Hoex
The material science literature contains up-to-date and comprehensive scientific knowledge of materials.
no code implementations • 30 Nov 2022 • Chunyu Ma, Zhihan Zhou, Han Liu, David Koslicki
We believe it can effectively reduce "black-box" concerns and increase prediction confidence for drug repurposing based on predicted path-based explanations, and further accelerate the process of drug discovery for emerging diseases.
no code implementations • 29 Oct 2022 • Victor Dibia, Adam Fourney, Gagan Bansal, Forough Poursabzi-Sangdeh, Han Liu, Saleema Amershi
Large language models have demonstrated great potential to assist programmers in generating code.
no code implementations • 27 Oct 2022 • Yetao Wu, Han Liu, Jie Yan, Xiaolin Hu
After training, the model is used for virtual screening to find potential drugs for Alzheimer's disease (AD) treatment.
1 code implementation • 26 Oct 2022 • Han Liu, Michelle K. Sigona, Thomas J. Manuel, Li Min Chen, Benoit M. Dawant, Charles F. Caskey
Among 20 targets, differences in simulated peak pressure between rCT and sCT were largest without phase correction (12. 4$\pm$8. 1%) and smallest with Kranion phases (7. 3$\pm$6. 0%).
1 code implementation • 16 Oct 2022 • Ho Hin Lee, Yucheng Tang, Han Liu, Yubo Fan, Leon Y. Cai, Qi Yang, Xin Yu, Shunxing Bao, Yuankai Huo, Bennett A. Landman
We evaluate our proposed approach on multi-organ segmentation with both non-contrast CT (NCCT) datasets and the MICCAI 2015 BTCV Challenge contrast-enhance CT (CECT) datasets.
no code implementations • 23 Sep 2022 • Han Liu, Yubo Fan, Ipek Oguz, Benoit M. Dawant
Automatic segmentation of vestibular schwannoma (VS) and cochlea from magnetic resonance imaging can facilitate VS treatment planning.
no code implementations • 24 Aug 2022 • Hao Li, Dewei Hu, Han Liu, Jiacheng Wang, Ipek Oguz
We fuse the information from the convolutional encoder and the transformer, and pass it to the decoder to obtain the results.
no code implementations • 23 Jul 2022 • Ji Liu, Dong Li, Zekun Li, Han Liu, Wenjing Ke, Lu Tian, Yi Shan
Sample assignment plays a prominent part in modern object detection approaches.
1 code implementation • IFAC-PapersOnLine 2022 • Mengna Li, Youmin Zhang, Lingxia Mu, Jing Xin, Ziquan Yu, Shangbin Jiao, Han Liu, Guo Xie, Yi Yingmin
Different from deeplabv3+, in order to improve the segmentation speed, this paper uses the lightweight network mobilenetv3 to build a new deep convolutional neural network and does not use atrous convolution, but it will affect the segmentation accuracy.
Ranked #1 on
Real-Time Semantic Segmentation
on FLAME
1 code implementation • 10 Jul 2022 • Tim Tsz-Kit Lau, Han Liu
The proposed algorithms extend existing Langevin Monte Carlo algorithms in two aspects -- the ability to sample nonsmooth distributions with mirror descent-like algorithms, and the use of the more general Bregman--Moreau envelope in place of the Moreau envelope as a smooth approximation of the nonsmooth part of the potential.
no code implementations • 14 Jun 2022 • Han Liu, Feng Zhang, Xiaotong Zhang, Siyang Zhao, Junjie Sun, Hong Yu, Xianchao Zhang
Multi-label aspect category detection allows a given review sentence to contain multiple aspect categories, which is shown to be more practical in sentiment analysis and attracting increasing attention.
no code implementations • 11 Jun 2022 • Han Liu, Bingning Wang, Ting Yao, Haijin Liang, Jianjin Xu, Xiaolin Hu
Large-scale pre-trained language models have achieved great success on natural language generation tasks.
no code implementations • 5 Jun 2022 • Han Liu, Siyang Zhao, Xiaotong Zhang, Feng Zhang, Junjie Sun, Hong Yu, Xianchao Zhang
Zero-shot intent classification is a vital and challenging task in dialogue systems, which aims to deal with numerous fast-emerging unacquainted intents without annotated training data.
no code implementations • 1 May 2022 • Ning Wang, Han Liu, Diego Klabjan
We develop an abstractive summarization framework independent of labeled data for multiple heterogeneous documents.
no code implementations • 23 Mar 2022 • Tim Tsz-Kit Lau, Han Liu
On the other hand, in distributionally robust optimization, we seek data-driven decisions which perform well under the most adverse distribution from a nominal distribution constructed from data samples within a certain discrepancy of probability distributions.
no code implementations • 15 Mar 2022 • Guo Ye, Han Liu, Biswa Sengupta
In multi-agent collaboration problems with communication, an agent's ability to encode their intention and interpret other agents' strategies is critical for planning their future actions.
no code implementations • 14 Mar 2022 • Qinjie Lin, Han Liu, Biswa Sengupta
Our results also demonstrate the advantage of the switch transformer model for absorbing expert knowledge and the importance of value distribution in evaluating the trajectory.
no code implementations • 8 Mar 2022 • Can Cui, Han Liu, Quan Liu, Ruining Deng, Zuhayr Asad, Yaohong WangShilin Zhao, Haichun Yang, Bennett A. Landman, Yuankai Huo
Thus, there are still open questions on how to effectively predict brain cancer survival from the incomplete radiological, pathological, genomic, and demographic data (e. g., one or more modalities might not be collected for a patient).
1 code implementation • 7 Mar 2022 • Han Liu, Yubo Fan, Hao Li, Jiacheng Wang, Dewei Hu, Can Cui, Ho Hin Lee, Huahong Zhang, Ipek Oguz
Previously, a training strategy termed Modality Dropout (ModDrop) has been applied to MS lesion segmentation to achieve the state-of-the-art performance with missing modality.
no code implementations • 4 Mar 2022 • Han Liu, Xiaoyu Song, Ge Gao, Hehua Zhang, Yu-Shen Liu, Ming Gu
Semantic rule checking on RDFS/OWL data has been widely used in the construction industry.
1 code implementation • 21 Feb 2022 • Han Liu, Michelle K. Sigona, Thomas J. Manuel, Li Min Chen, Charles F. Caskey, Benoit M. Dawant
Transcranial MRI-guided focused ultrasound (TcMRgFUS) is a therapeutic ultrasound method that focuses sound through the skull to a small region noninvasively under MRI guidance.
no code implementations • 26 Jan 2022 • Han Liu, Kathryn L. Holloway, Dario J. Englot, Benoit M. Dawant
Epilepsy is the fourth most common neurological disorder and affects people of all ages worldwide.
no code implementations • 25 Jan 2022 • Han Liu, Yubo Fan, Can Cui, Dingjie Su, Andrew McNeil, Benoit M. Dawant
Automatic methods to segment the vestibular schwannoma (VS) tumors and the cochlea from magnetic resonance imaging (MRI) are critical to VS treatment planning.
3 code implementations • 8 Jan 2022 • Reuben Dorent, Aaron Kujawa, Marina Ivory, Spyridon Bakas, Nicola Rieke, Samuel Joutard, Ben Glocker, Jorge Cardoso, Marc Modat, Kayhan Batmanghelich, Arseniy Belkov, Maria Baldeon Calisto, Jae Won Choi, Benoit M. Dawant, Hexin Dong, Sergio Escalera, Yubo Fan, Lasse Hansen, Mattias P. Heinrich, Smriti Joshi, Victoriya Kashtanova, Hyeon Gyu Kim, Satoshi Kondo, Christian N. Kruse, Susana K. Lai-Yuen, Hao Li, Han Liu, Buntheng Ly, Ipek Oguz, Hyungseob Shin, Boris Shirokikh, Zixian Su, Guotai Wang, Jianghao Wu, Yanwu Xu, Kai Yao, Li Zhang, Sebastien Ourselin, Jonathan Shapey, Tom Vercauteren
The aim was to automatically perform unilateral VS and bilateral cochlea segmentation on hrT2 as provided in the testing set (N=137).
no code implementations • 3 Nov 2021 • Xinlei Zhou, Han Liu, Farhad Pourpanah, Tieyong Zeng, XiZhao Wang
This paper provides a comprehensive review of epistemic uncertainty learning techniques in supervised learning over the last five years.
no code implementations • Findings (EMNLP) 2021 • Han Liu, Feng Zhang, Xiaotong Zhang, Siyang Zhao, Xianchao Zhang
Intent classification (IC) and slot filling (SF) are critical building blocks in task-oriented dialogue systems.
no code implementations • 29 Sep 2021 • Mattson Thieme, Ammar Gilani, Han Liu
In this work, we introduce a general methodology for approximating offline algorithms in online settings.
no code implementations • ICLR 2022 • Zhi Zhang, Zhuoran Yang, Han Liu, Pratap Tokekar, Furong Huang
This paper proposes a new algorithm for learning the optimal policies under a novel multi-agent predictive state representation reinforcement learning model.
no code implementations • 13 Sep 2021 • Han Liu, Yubo Fan, Can Cui, Dingjie Su, Andrew McNeil, Benoit M. Dawant
Automatic methods to segment the vestibular schwannoma (VS) tumors and the cochlea from magnetic resonance imaging (MRI) are critical to VS treatment planning.
no code implementations • CVPR 2021 • Xianchao Zhang, Ziyang Cheng, Xiaotong Zhang, Han Liu
In this paper, we propose a novel variant of GAN, Posterior Promoted GAN (P2GAN), which promotes generator with the real information in the posterior distribution produced by discriminator.
1 code implementation • 8 Jun 2021 • Han Liu, Yangyang Guo, Jianhua Yin, Zan Gao, Liqiang Nie
To be specific, in this model, positive and negative reviews are separately gathered and utilized to model the user-preferred and user-rejected aspects, respectively.
1 code implementation • Findings (ACL) 2021 • Zhihan Zhou, Liqian Ma, Han Liu
In this paper, we introduce an event-driven trading strategy that predicts stock movements by detecting corporate events from news articles.
no code implementations • 21 Mar 2021 • Li Wang, Dong Li, Han Liu, Jinzhang Peng, Lu Tian, Yi Shan
Our goal is to train a unified model for improving the performance in each dataset by leveraging information from all the datasets.
no code implementations • 4 Mar 2021 • Bin Wang, Han Liu, Chao Liu, Zhiqiang Yang, Qian Ren, Huixuan Zheng, Hong Lei
We applied BLOCKEYE in several popular DeFi projects and managed to discover potential security attacks that are unreported before.
Cryptography and Security Computers and Society
1 code implementation • 4 Feb 2021 • Han Liu, Caixia Yuan, Xiaojie Wang, Yushu Yang, Huixing Jiang, Zhongyuan Wang
We propose a novel task, Multi-Document Driven Dialogue (MD3), in which an agent can guess the target document that the user is interested in by leading a dialogue.
no code implementations • 13 Jan 2021 • Han Liu, Vivian Lai, Chenhao Tan
Although AI holds promise for improving human decision making in societally critical domains, it remains an open question how human-AI teams can reliably outperform AI alone and human alone in challenging prediction tasks (also known as complementary performance).
1 code implementation • 11 Dec 2020 • Hyunji Hayley Park, Katherine J. Zhang, Coleman Haley, Kenneth Steimel, Han Liu, Lane Schwartz
We fill in missing typological data for several languages and consider corpus-based measures of morphological complexity in addition to expert-produced typological features.
no code implementations • 3 Nov 2020 • Han Liu, Can Cui, Dario J. Englot, Benoit M. Dawant
Atlas-based methods are the standard approaches for automatic targeting of the Anterior Nucleus of the Thalamus (ANT) for Deep Brain Stimulation (DBS), but these are known to lack robustness when anatomic differences between atlases and subjects are large.
1 code implementation • 15 Aug 2020 • Han Liu, Caixia Yuan, Xiaojie Wang
A major challenge of multi-label text classification (MLTC) is to stimulatingly exploit possible label differences and label correlations.
Ranked #1 on
Multi-Label Text Classification
on AAPD
(Micro F1 metric)
1 code implementation • ACL 2020 • Guangfeng Yan, Lu Fan, Qimai Li, Han Liu, Xiaotong Zhang, Xiao-Ming Wu, Albert Y. S. Lam
User intent classification plays a vital role in dialogue systems.
1 code implementation • 27 Jun 2020 • Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao
We describe a new library named picasso, which implements a unified framework of pathwise coordinate optimization for a variety of sparse learning problems (e. g., sparse linear regression, sparse logistic regression, sparse Poisson regression and scaled sparse linear regression) combined with efficient active set selection strategies.
no code implementations • 27 Jun 2020 • Xingguo Li, Tuo Zhao, Xiaoming Yuan, Han Liu
This paper describes an R package named flare, which implements a family of new high dimensional regression methods (LAD Lasso, SQRT Lasso, $\ell_q$ Lasso, and Dantzig selector) and their extensions to sparse precision matrix estimation (TIGER and CLIME).
no code implementations • 26 Jun 2020 • Tuo Zhao, Han Liu, Kathryn Roeder, John Lafferty, Larry Wasserman
We describe an R package named huge which provides easy-to-use functions for estimating high dimensional undirected graphs from data.
2 code implementations • ACL 2020 • Yutai Hou, Wanxiang Che, Yongkui Lai, Zhihan Zhou, Yijia Liu, Han Liu, Ting Liu
In this paper, we explore the slot tagging with only a few labeled support sentences (a. k. a.
no code implementations • 16 May 2020 • Fraser Young, L. Zhang, Richard Jiang, Han Liu, Conor Wall
With the recent booming of artificial intelligence (AI), particularly deep learning techniques, digital healthcare is one of the prevalent areas that could gain benefits from AI-enabled functionality.
no code implementations • 11 May 2020 • Lane Schwartz, Francis Tyers, Lori Levin, Christo Kirov, Patrick Littell, Chi-kiu Lo, Emily Prud'hommeaux, Hyunji Hayley Park, Kenneth Steimel, Rebecca Knowles, Jeffrey Micher, Lonny Strunk, Han Liu, Coleman Haley, Katherine J. Zhang, Robbie Jimmerson, Vasilisa Andriyanets, Aldrian Obaja Muis, Naoki Otani, Jong Hyuk Park, Zhisong Zhang
In the literature, languages like Finnish or Turkish are held up as extreme examples of complexity that challenge common modelling assumptions.
1 code implementation • 9 May 2020 • Yanran Guan, Han Liu, Kun Liu, Kangxue Yin, Ruizhen Hu, Oliver van Kaick, Yan Zhang, Ersin Yumer, Nathan Carr, Radomir Mech, Hao Zhang
Our tool supports constrained modeling, allowing users to restrict or steer the model evolution with functionality labels.
Graphics
no code implementations • LREC 2020 • Han Liu, Pete Burnap, Wafa Alorainy, Matthew Williams
This paper presents a system developed during our participation (team name: scmhl5) in the TRAC-2 Shared Task on aggression identification.
no code implementations • 19 Mar 2020 • Han Liu, Shantao Liu
EQL, also named as Extremely Simple Query Language, can be widely used in the field of knowledge graph, precise search, strong artificial intelligence, database, smart speaker , patent search and other fields.
no code implementations • 14 Jan 2020 • Vivian Lai, Han Liu, Chenhao Tan
To support human decision making with machine learning models, we often need to elucidate patterns embedded in the models that are unsalient, unknown, or counterintuitive to humans.
no code implementations • 11 Dec 2019 • Hong Luo, Han Liu, Kejun Li, Bo Zhang
An essential criterion for FS image quality control is that all the essential anatomical structures in the section should appear full and remarkable with a clear boundary.
1 code implementation • IJCNLP 2019 • Han Liu, Xiaotong Zhang, Lu Fan, Xu Fu, i, Qimai Li, Xiao-Ming Wu, Albert Y. S. Lam
With the burgeoning of conversational AI, existing systems are not capable of handling numerous fast-emerging intents, which motivates zero-shot intent classification.
no code implementations • 27 Sep 2019 • Han Liu, Xianchao Zhang, Xiaotong Zhang, Qimai Li, Xiao-Ming Wu
However, there are two issues in existing possible world based algorithms: (1) They rely on all the possible worlds and treat them equally, but some marginal possible worlds may cause negative effects.
1 code implementation • 26 Sep 2019 • Qimai Li, Xiaotong Zhang, Han Liu, Quanyu Dai, Xiao-Ming Wu
Graph convolutional neural networks (GCN) have been the model of choice for graph representation learning, which is mainly due to the effective design of graph convolution that computes the representation of a node by aggregating those of its neighbors.
no code implementations • 25 Sep 2019 • Boxin Wang, Hengzhi Pei, Han Liu, Bo Li
In particular, we propose a tree based autoencoder to encode discrete text data into continuous vector space, upon which we optimize the adversarial perturbation.
no code implementations • 25 Sep 2019 • Yunhui Long, Suxin Lin, Zhuolin Yang, Carl A. Gunter, Han Liu, Bo Li
We present a novel approach named G-PATE for training differentially private data generator.
no code implementations • 25 Sep 2019 • Qimai Li, Xiaotong Zhang, Han Liu, Xiao-Ming Wu
Graph convolutional neural networks have demonstrated promising performance in attributed graph learning, thanks to the use of graph convolution that effectively combines graph structures and node features for learning node representations.
1 code implementation • NeurIPS 2019 • Han Liu, Zhizhong Han, Yu-Shen Liu, Ming Gu
Low-rank metric learning aims to learn better discrimination of data subject to low-rank constraints.
no code implementations • NeurIPS 2016 • Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu
We consider the weakly supervised binary classification problem where the labels are randomly flipped with probability $1- {\alpha}$.
no code implementations • 20 Jun 2019 • Yutai Hou, Zhihan Zhou, Yijia Liu, Ning Wang, Wanxiang Che, Han Liu, Ting Liu
It calculates emission score with similarity based methods and obtains transition score with a specially designed transfer mechanism.
1 code implementation • 4 Jun 2019 • Xiaotong Zhang, Han Liu, Qimai Li, Xiao-Ming Wu
Attributed graph clustering is challenging as it requires joint modelling of graph structures and node attributes.
Ranked #3 on
Graph Clustering
on Cora
1 code implementation • ICLR 2020 • Harsh Shrivastava, Xinshi Chen, Binghong Chen, Guanghui Lan, Srinvas Aluru, Han Liu, Le Song
Recently, there is a surge of interest to learn algorithms directly based on data, and in this case, learn to map empirical covariance to the sparse precision matrix.
no code implementations • 28 May 2019 • Kean Ming Tan, Junwei Lu, Tong Zhang, Han Liu
To address this issue, neuroscientists have been measuring brain activity under natural viewing experiments in which the subjects are given continuous stimuli, such as watching a movie or listening to a story.
1 code implementation • ICLR 2020 • Binghong Chen, Bo Dai, Qinjie Lin, Guo Ye, Han Liu, Le Song
We propose a meta path planning algorithm named \emph{Neural Exploration-Exploitation Trees~(NEXT)} for learning from prior experience for solving new path planning problems in high dimensional continuous state and action spaces.
1 code implementation • CVPR 2019 • Qimai Li, Xiao-Ming Wu, Han Liu, Xiaotong Zhang, Zhichao Guan
However, existing graph-based methods either are limited in their ability to jointly model graph structures and data features, such as the classical label propagation methods, or require a considerable amount of labeled data for training and validation due to high model complexity, such as the recent neural-network-based methods.
no code implementations • 6 Dec 2018 • Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Başar
This work appears to be the first finite-sample analysis for batch MARL, a step towards rigorous theoretical understanding of general MARL algorithms in the finite-sample regime.
Multi-agent Reinforcement Learning
reinforcement-learning
+2
no code implementations • NeurIPS 2018 • Wei Sun, Junwei Lu, Han Liu
In order to test the hypotheses on their topological structures, we propose two adjacency matrix sketching frameworks: neighborhood sketching and subgraph sketching.
1 code implementation • NeurIPS 2018 • Qing Wang, Jiechao Xiong, Lei Han, Peng Sun, Han Liu, Tong Zhang
We consider deep policy learning with only batched historical trajectories.
no code implementations • 31 Oct 2018 • Yi Zhen, Lei Wang, Han Liu, Jian Zhang, Jiantao Pu
Among these CNNs, the DenseNet had the highest classification accuracy (i. e., 75. 50%) based on pre-trained weights when using global ROIs, as compared to 65. 50% when using local ROIs.
no code implementations • 30 Oct 2018 • Han Liu, Lei Wang, Yandong Nan, Faguang Jin, Qi. Wang, Jiantao Pu
Two CNN-based classification models were then used as feature extractors to obtain the discriminative features of the entire CXR images and the cropped lung region images.
no code implementations • 19 Oct 2018 • Han Liu, Dan Zeng, Qi Tian
Secondly, super-pixel level database is used to train our cloud detection models based on CNN and deep forest.
5 code implementations • 10 Oct 2018 • Jiechao Xiong, Qing Wang, Zhuoran Yang, Peng Sun, Lei Han, Yang Zheng, Haobo Fu, Tong Zhang, Ji Liu, Han Liu
Most existing deep reinforcement learning (DRL) frameworks consider either discrete action space or continuous action space solely.
no code implementations • 25 Sep 2018 • Chaobing Song, Ji Liu, Han Liu, Yong Jiang, Tong Zhang
Regularized online learning is widely used in machine learning applications.
no code implementations • 21 Sep 2018 • Yuan Cao, Matey Neykov, Han Liu
The goal is to distinguish whether the underlying graph is empty, i. e., the model consists of independent Rademacher variables, versus the alternative that the underlying graph contains a subgraph of a certain structure.
2 code implementations • 19 Sep 2018 • Peng Sun, Xinghai Sun, Lei Han, Jiechao Xiong, Qing Wang, Bo Li, Yang Zheng, Ji Liu, Yongsheng Liu, Han Liu, Tong Zhang
Both TStarBot1 and TStarBot2 are able to defeat the built-in AI agents from level 1 to level 10 in a full game (1v1 Zerg-vs-Zerg game on the AbyssalReef map), noting that level 8, level 9, and level 10 are cheating agents with unfair advantages such as full vision on the whole map and resource harvest boosting.
no code implementations • 17 Sep 2018 • Kean Ming Tan, Zhaoran Wang, Tong Zhang, Han Liu, R. Dennis Cook
Sliced inverse regression is a popular tool for sufficient dimension reduction, which replaces covariates with a minimal set of their linear combinations without loss of information on the conditional distribution of the response given the covariates.
no code implementations • 11 Sep 2018 • Yong Chen, Ming Zhou, Ying Wen, Yaodong Yang, Yufeng Su, Wei-Nan Zhang, Dell Zhang, Jun Wang, Han Liu
Deep Q-learning has achieved a significant success in single-agent decision making tasks.
Multiagent Systems
no code implementations • NeurIPS 2016 • Chris Junchi Li, Zhaoran Wang, Han Liu
Despite the empirical success of nonconvex statistical optimization methods, their global dynamics, especially convergence to the desirable local minima, remain less well understood in theory.
no code implementations • NeurIPS 2017 • Chris Junchi Li, Mengdi Wang, Han Liu, Tong Zhang
In this paper, we propose to adopt the diffusion approximation tools to study the dynamics of Oja's iteration which is an online stochastic gradient descent method for the principal component analysis.
no code implementations • 21 Aug 2018 • Jianqing Fan, Han Liu, Zhaoran Wang, Zhuoran Yang
We study the fundamental tradeoffs between statistical accuracy and computational tractability in the analysis of high dimensional heterogeneous data.
no code implementations • ICML 2018 • Qiang Sun, Kean Ming Tan, Han Liu, Tong Zhang
Our proposal is computationally tractable and produces an estimator that achieves the oracle rate of convergence.
no code implementations • ICML 2018 • Hao Lu, Yuan Cao, Zhuoran Yang, Junwei Lu, Han Liu, Zhaoran Wang
We study the hypothesis testing problem of inferring the existence of combinatorial structures in undirected graphical models.
1 code implementation • ICLR 2019 • Carson Eisenach, Haichuan Yang, Ji Liu, Han Liu
In the former, an agent learns a policy over $\mathbb{R}^d$ and in the latter, over a discrete set of actions each of which is parametrized by a continuous parameter.
2 code implementations • 1 Jun 2018 • Carson Eisenach, Han Liu
Compared to the naive interior point method, our method reduces the computational complexity of solving the SDP from $\tilde{O}(d^7\log\epsilon^{-1})$ to $\tilde{O}(d^{6}K^{-2}\epsilon^{-1})$ arithmetic operations for an $\epsilon$-optimal solution.
no code implementations • ICML 2018 • Daniel R. Jiang, Emmanuel Ekwedike, Han Liu
Inspired by recent successes of Monte-Carlo tree search (MCTS) in a number of artificial intelligence (AI) application domains, we propose a model-based reinforcement learning (RL) technique that iteratively applies MCTS on batches of small, finite-horizon versions of the original infinite-horizon Markov decision process.
1 code implementation • 6 May 2018 • Han Liu, Xiangnan He, Fuli Feng, Liqiang Nie, Rui Liu, Hanwang Zhang
In this paper, we develop a generic feature-based recommendation model, called Discrete Factorization Machine (DFM), for fast and accurate recommendation.
5 code implementations • ICML 2018 • Kaiqing Zhang, Zhuoran Yang, Han Liu, Tong Zhang, Tamer Başar
To this end, we propose two decentralized actor-critic algorithms with function approximation, which are applicable to large-scale MARL problems where both the number of states and the number of agents are massively large.
Multi-agent Reinforcement Learning
reinforcement-learning
+2
no code implementations • 23 Jan 2018 • Wafa Alorainy, Pete Burnap, Han Liu, Matthew Williams
Offensive or antagonistic language targeted at individuals and social groups based on their personal characteristics (also known as cyber hate speech or cyberhate) has been frequently posted and widely circulated viathe World Wide Web.