no code implementations • Findings (NAACL) 2022 • Qiushi Guo, Xin Wang, Dehong Gao
Leveraging the dependency tree of the input sentence is able to improve the model performance for relation extraction.
no code implementations • ACL 2022 • Xin Wang, Minlong Peng, Mingming Sun, Ping Li
OIE@OIA follows the methodology of Open Information eXpression (OIX): parsing a sentence to an Open Information Annotation (OIA) Graph and then adapting the OIA graph to different OIE tasks with simple rules.
no code implementations • EMNLP 2020 • Mingming Sun, Wenyue Hua, Zoey Liu, Xin Wang, Kangjie Zheng, Ping Li
Based on the same platform of OIX, the OIE strategies are reusable, and people can select a set of strategies to assemble their algorithm for a specific task so that the adaptability may be significantly increased.
1 code implementation • 24 Sep 2023 • Xin Wang, Ziwei Luo, Jing Hu, Chengming Feng, Shu Hu, Bin Zhu, Xi Wu, Siwei Lyu
The key feature in the RL-I2IT framework is to decompose a monolithic learning process into small steps with a lightweight model to progressively transform a source image successively to a target image.
no code implementations • 22 Sep 2023 • Doris Antensteiner, Marah Halawa, Asra Aslam, Ivaxi Sheth, Sachini Herath, Ziqi Huang, Sunnie S. Y. Kim, Aparna Akula, Xin Wang
In this paper, we present the details of Women in Computer Vision Workshop - WiCV 2023, organized alongside the hybrid CVPR 2023 in Vancouver, Canada.
no code implementations • 21 Sep 2023 • Zongqian Zhan, Rui Xia, Yifei Yu, Yibo Xu, Xin Wang
Over the last decades, ample achievements have been made on Structure from motion (SfM).
no code implementations • 14 Sep 2023 • Yang Li, Fan Zhong, Xin Wang, Shuangbing Song, Jiachen Li, Xueying Qin, Changhe Tu
The limitations of previous scoring methods and error metrics are analyzed, based on which we introduce our improved evaluation methods.
1 code implementation • 12 Sep 2023 • Xin Wang, Junichi Yamagishi
While many datasets use spoofed data generated by speech synthesis systems, it was recently found that data vocoded by neural vocoders were also effective as the spoofed training data.
1 code implementation • 10 Sep 2023 • Shu Hu, Zhenhuan Yang, Xin Wang, Yiming Ying, Siwei Lyu
Theoretically, we show that the learning objective of ORAT satisfies the $\mathcal{H}$-consistency in binary classification, which establishes it as a proper surrogate to adversarial 0/1 loss.
no code implementations • 8 Sep 2023 • Xin Wang, Bumsoo Park, Robert G. Landers, Sandipan Mishra, Douglas A. Bristow
However, due to inherent process variability, it is still very costly and time consuming to certify the process and the part.
no code implementations • 4 Sep 2023 • Feng Zhu, Jingjing Zhang, Shengyun Liu, Xin Wang
Local stochastic gradient descent (SGD) is a fundamental approach in achieving communication efficiency in Federated Learning (FL) by allowing individual workers to perform local updates.
1 code implementation • 31 Aug 2023 • Qiang Huang, Jiawei Jiang, Xi Susie Rao, Ce Zhang, Zhichao Han, Zitao Zhang, Xin Wang, Yongjun He, Quanqing Xu, Yang Zhao, Chuang Hu, Shuo Shang, Bo Du
To handle graphs in which features or connectivities are evolving over time, a series of temporal graph neural networks (TGNNs) have been proposed.
1 code implementation • 28 Aug 2023 • Ziwei Zhang, Haoyang Li, Zeyang Zhang, Yijian Qin, Xin Wang, Wenwu Zhu
Large models have emerged as the most recent groundbreaking achievements in artificial intelligence, and particularly machine learning.
no code implementations • 20 Aug 2023 • Yingji Li, Mengnan Du, Rui Song, Xin Wang, Ying Wang
Then, for large-scale LLMs, we introduce recent fairness research, including fairness evaluation, reasons for bias, and debiasing methods.
1 code implementation • 3 Aug 2023 • Liang Peng, Xin Wang, Xiaofeng Zhu
Unsupervised multiplex graph learning (UMGL) has been shown to achieve significant effectiveness for different downstream tasks by exploring both complementary information and consistent information among multiple graphs.
no code implementations • 18 Jul 2023 • Guiyu Zhao, Zhentao Guo, Xin Wang, Hongbin Ma
However, most methods are susceptible to noise and have poor generalization ability on unseen datasets.
no code implementations • 11 Jul 2023 • Zihao Deng, Xin Wang, Sayeh Sharify, Michael Orshansky
Quantization assigning the same bit-width to all layers leads to large accuracy degradation at low precision and is wasteful at high precision settings.
no code implementations • 6 Jul 2023 • Xin Wang, Tao Tan, Yuan Gao, Luyi Han, Tianyu Zhang, Chunyao Lu, Regina Beets-Tan, Ruisheng Su, Ritse Mann
The question of 'what the symmetrical Bi-MG would look like when the asymmetrical abnormalities have been removed ?'
no code implementations • 4 Jul 2023 • Zhenwei Zhang, Xin Wang, Jingyuan Xie, Heling Zhang, Yuantao Gu
Peak-Hour Series Forecasting (PHSF) is a crucial yet underexplored task in various domains.
no code implementations • 4 Jul 2023 • Yingji Li, Mengnan Du, Xin Wang, Ying Wang
Meanwhile, experimental results on the GLUE benchmark show that CCPA retains the language modeling capability of PLMs.
no code implementations • 4 Jul 2023 • Zhenwei Zhang, Xin Wang, Yuantao Gu
Multivariate time series forecasting plays a critical role in diverse domains.
no code implementations • 3 Jul 2023 • Bingnan Xiao, Xichen Yu, Wei Ni, Xin Wang, H. Vincent Poor
The development of applications based on artificial intelligence and implemented over wireless networks is increasingly rapidly and is expected to grow dramatically in the future.
1 code implementation • 3 Jul 2023 • Luyi Han, Tianyu Zhang, Yunzhi Huang, Haoran Dou, Xin Wang, Yuan Gao, Chunyao Lu, Tan Tao, Ritse Mann
Multi-sequence MRI is valuable in clinical settings for reliable diagnosis and treatment prognosis, but some sequences may be unusable or missing for various reasons.
no code implementations • 3 Jul 2023 • Tianyu Zhang, Luyi Han, Anna D'Angelo, Xin Wang, Yuan Gao, Chunyao Lu, Jonas Teuwen, Regina Beets-Tan, Tao Tan, Ritse Mann
DWIs with different b-values are fused to efficiently utilize the difference features of DWIs.
no code implementations • 20 Jun 2023 • Suriya Gunasekar, Yi Zhang, Jyoti Aneja, Caio César Teodoro Mendes, Allie Del Giorno, Sivakanth Gopi, Mojan Javaheripi, Piero Kauffmann, Gustavo de Rosa, Olli Saarikivi, Adil Salim, Shital Shah, Harkirat Singh Behl, Xin Wang, Sébastien Bubeck, Ronen Eldan, Adam Tauman Kalai, Yin Tat Lee, Yuanzhi Li
Despite this small scale, phi-1 attains pass@1 accuracy 50. 6% on HumanEval and 55. 5% on MBPP.
Ranked #12 on
Code Generation
on HumanEval
no code implementations • 16 Jun 2023 • Akshay K. Burusa, Joost Scholten, David Rapado Rincon, Xin Wang, Eldert J. van Henten, Gert Kootstra
To automate harvesting and de-leafing of tomato plants using robots, it is important to search and detect the relevant plant parts, namely tomatoes, peduncles, and petioles.
1 code implementation • 30 May 2023 • Sung Hwan Mun, Hye-jin Shim, Hemlata Tak, Xin Wang, Xuechen Liu, Md Sahidullah, Myeonghun Jeong, Min Hyun Han, Massimiliano Todisco, Kong Aik Lee, Junichi Yamagishi, Nicholas Evans, Tomi Kinnunen, Nam Soo Kim, Jee-weon Jung
Second, competitive performance should be demonstrated compared to the fusion of automatic speaker verification (ASV) and countermeasure (CM) embeddings, which outperformed single embedding solutions by a large margin in the SASV2022 challenge.
no code implementations • 29 May 2023 • Tianjun Zhang, Yi Zhang, Vibhav Vineet, Neel Joshi, Xin Wang
Control-GPT works by querying GPT-4 to write TikZ code, and the generated sketches are used as references alongside the text instructions for diffusion models (e. g., ControlNet) to generate photo-realistic images.
1 code implementation • 28 May 2023 • Lin Zhang, Xin Wang, Erica Cooper, Nicholas Evans, Junichi Yamagishi
To properly measure misclassified ranges and better evaluate spoof localization performance, we upgrade point-based EER to range-based EER.
1 code implementation • 26 May 2023 • Zheng Li, Caili Guo, Xin Wang, Zerun Feng, Yanjun Wang
Given a query caption, the goal is to rank candidate images by relevance, from large to small.
no code implementations • 24 May 2023 • Fan Dong, Ali Abbasi, Steve Drew, Henry Leung, Xin Wang, Jiayu Zhou
Federated learning provides a promising privacy-preserving way for utilizing large-scale private edge data from massive Internet-of-Things (IoT) devices.
1 code implementation • 24 May 2023 • Baifeng Shi, Siyu Gai, Trevor Darrell, Xin Wang
We introduce Top-Down Attention Steering (TOAST), a novel transfer learning algorithm that keeps the pre-trained backbone frozen, selects task-relevant features in the output, and feeds those features back to the model to steer the attention to the task-specific features.
1 code implementation • 24 May 2023 • Shishir G. Patil, Tianjun Zhang, Xin Wang, Joseph E. Gonzalez
Large Language Models (LLMs) have seen an impressive wave of advances recently, with models now excelling in a variety of tasks, such as mathematical reasoning and program synthesis.
1 code implementation • Interspeech 2023 • Chang Zeng, Xin Wang, Xiaoxiao Miao, Erica Cooper, Junichi Yamagishi
The ability of countermeasure models to generalize from seen speech synthesis methods to unseen ones has been investigated in the ASVspoof challenge.
no code implementations • 6 May 2023 • Yifei Chen, Zhan Yu, Chenghong Zhu, Xin Wang
The rapid advancement of quantum computing has led to an extensive demand for effective techniques to extract classical information from quantum systems, particularly in fields like quantum machine learning and quantum chemistry.
no code implementations • 5 May 2023 • Xingyu Zhu, Xin Wang, Jonathan Freer, Hyung Jin Chang, Yixing Gao
These methods often utilize physics engines to synthesize depth images to reduce the cost of real labeled data collection.
no code implementations • 5 May 2023 • Hong Chen, YiPeng Zhang, Xin Wang, Xuguang Duan, Yuwei Zhou, Wenwu Zhu
To tackle the problems, we propose DisenBooth, an identity-preserving disentangled tuning framework for subject-driven text-to-image generation in this paper.
no code implementations • 3 May 2023 • Chen Zhu, Liang Du, Hong Chen, Shuang Zhao, Zixun Sun, Xin Wang, Wenwu Zhu
To tackle this problem, inspired by the Global Workspace Theory in conscious processing, which posits that only a specific subset of the product features are pertinent while the rest can be noisy and even detrimental to human-click behaviors, we propose a CTR model that enables Dynamic Embedding Learning with Truncated Conscious Attention for CTR prediction, termed DELTA.
1 code implementation • 29 Apr 2023 • Kai Xu, Ziwei Yu, Xin Wang, Michael Bi Mi, Angela Yao
Video super-resolution commonly uses a frame-wise alignment to support the propagation of information over time.
Ranked #1 on
Video Super-Resolution
on REDS4- 4x upscaling
1 code implementation • 27 Apr 2023 • Joo Hyung Lee, Wonpyo Park, Nicole Mitchell, Jonathan Pilault, Johan Obando-Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart Bik, Woohyun Han, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann Dauphin, Gintare Karolina Dziugaite, Pablo Samuel Castro, Utku Evci
This paper introduces JaxPruner, an open-source JAX-based pruning and sparse training library for machine learning research.
no code implementations • 23 Apr 2023 • Yicheng Fan, Dana Alon, Jingyue Shen, Daiyi Peng, Keshav Kumar, Yun Long, Xin Wang, Fotis Iliopoulos, Da-Cheng Juan, Erik Vee
For a model architecture with $L$ layers, we perform layerwise-search for each layer, selecting from a set of search options $\mathbb{S}$.
no code implementations • 19 Apr 2023 • Hao Chen, Peng Zheng, Xin Wang, Shu Hu, Bin Zhu, Jinrong Hu, Xi Wu, Siwei Lyu
As growing usage of social media websites in the recent decades, the amount of news articles spreading online rapidly, resulting in an unprecedented scale of potentially fraudulent information.
1 code implementation • 16 Apr 2023 • Hanlei Zhang, Hua Xu, Xin Wang, Fei Long, Kai Gao
New intent discovery is of great value to natural language processing, allowing for a better understanding of user needs and providing friendly services.
no code implementations • 16 Apr 2023 • Xin Wang, Zhenrong Shen, Zhiyun Song, Sheng Wang, Mengjun Liu, Lichi Zhang, Kai Xuan, Qian Wang
Magnetic resonance (MR) images collected in 2D scanning protocols typically have large inter-slice spacing, resulting in high in-plane resolution but reduced through-plane resolution.
no code implementations • CVPR 2023 • Beini Xie, Heng Chang, Ziwei Zhang, Xin Wang, Daixin Wang, Zhiqiang Zhang, Rex Ying, Wenwu Zhu
To tackle these challenges, we propose a novel Robust Neural Architecture search framework for GNNs (G-RNA).
no code implementations • CVPR 2023 • Ming Yan, Xin Wang, Yudi Dai, Siqi Shen, Chenglu Wen, Lan Xu, Yuexin Ma, Cheng Wang
The core of this dataset is a blending optimization process, which corrects for the pose as it drifts and is affected by the magnetic conditions.
no code implementations • 29 Mar 2023 • Yaqian Guo, Xin Wang, Ce Li, Shihui Ying
Second, we utilize OT to achieve a more robust alignment of source and target domains in output space, where the OT plan defines a well attention mechanism to improve the adaptation of the model.
no code implementations • 23 Mar 2023 • Xin Wang, Yi Zhuo, Shunlong Li
This paper proposes a damage detection method based on the train-induced responses of high-speed railway box girder.
1 code implementation • CVPR 2023 • Baifeng Shi, Trevor Darrell, Xin Wang
In this paper, we consider top-down attention from a classic Analysis-by-Synthesis (AbS) perspective of vision.
no code implementations • 13 Mar 2023 • Xuansheng Wu, Kaixiong Zhou, Mingchen Sun, Xin Wang, Ninghao Liu
In particular, we introduce the basic concepts of graph prompt learning, organize the existing work of designing graph prompting functions, and describe their applications and future challenges.
no code implementations • 6 Mar 2023 • Chenhao Yang, Xin Wang, Wei Ni, Yi Jiang
Under this approach, we reveal that the optimal receive beamforming is given by the classic MMSE one and the optimal transmit beamforming design amounts to solving an orthogonal Procrustes problem, thereby allowing for closed-form solutions to subproblems in each BCD step and fast convergence of the proposed algorithm to a high-quality (near-optimal) overall beamforming design.
no code implementations • 1 Mar 2023 • Zheng Li, Caili Guo, Xin Wang, Zerun Feng, Zhongtian Du
To alleviate the gradient vanishing problem, we propose a Selectively Hard Negative Mining (SelHN) strategy, which chooses whether to mine hard negative samples according to the gradient vanishing condition.
no code implementations • 10 Feb 2023 • Shuyan Hu, Xin Yuan, Wei Ni, Xin Wang, Abbas Jamalipour
This paper presents a new deep reinforcement learning (DRL)-based approach to the trajectory planning and jamming rejection of an unmanned aerial vehicle (UAV) for the Internet-of-Things (IoT) applications.
no code implementations • 7 Feb 2023 • Ya Liu, Yingjie Zhou, Kai Yang, Xin Wang
IoT time series analysis has found numerous applications in a wide variety of areas, ranging from health informatics to network security.
no code implementations • 6 Feb 2023 • Haoyang Li, Xin Wang, Wenwu Zhu
To the best of our knowledge, this paper is the first survey for curriculum graph machine learning.
no code implementations • 3 Feb 2023 • Tianyu Zhang, Tao Tan, Luyi Han, Xin Wang, Yuan Gao, Jonas Teuwen, Regina Beets-Tan, Ritse Mann
Then the multi-parameter fusion with attention module enables the interaction of the encoded information from different parameters through a set of algorithmic strategies, and applies different weights to the information through the attention mechanism after information fusion to obtain refined representation information.
1 code implementation • 1 Feb 2023 • Luyi Han, Tao Tan, Tianyu Zhang, Yunzhi Huang, Xin Wang, Yuan Gao, Jonas Teuwen, Ritse Mann
Multi-sequence MRIs can be necessary for reliable diagnosis in clinical practice due to the complimentary information within sequences.
no code implementations • 31 Jan 2023 • Cenk Baykal, Dylan J Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang
One way of introducing sparsity into deep networks is by attaching an external table of parameters that is sparsely looked up at different layers of the network.
no code implementations • 30 Jan 2023 • Cenk Baykal, Dylan Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang
We introduce Alternating Updates (AltUp), a simple-to-implement method to increase a model's capacity without the computational burden.
no code implementations • 26 Jan 2023 • Yunxu Xie, Shu Hu, Xin Wang, Quanyu Liao, Bin Zhu, Xi Wu, Siwei Lyu
Existing adversarial attacks on object detection focus on attacking anchor-based detectors, which may not work well for anchor-free detectors.
no code implementations • CVPR 2023 • Huiyuan Fu, Wenkai Zheng, Xiangyu Meng, Xin Wang, Chuanming Wang, Huadong Ma
The Retinex-based methods require decomposing the image into reflectance and illumination components, which is a highly ill-posed problem and there is no available ground truth.
1 code implementation • 14 Dec 2022 • Chengzhi Mao, Scott Geng, Junfeng Yang, Xin Wang, Carl Vondrick
We apply this training loss to two adaption methods, model finetuning and visual prompt tuning.
1 code implementation • CVPR 2023 • Chengzhi Mao, Revant Teotia, Amrutha Sundar, Sachit Menon, Junfeng Yang, Xin Wang, Carl Vondrick
We propose a ``doubly right'' object recognition benchmark, where the metric requires the model to simultaneously produce both the right labels as well as the right rationales.
1 code implementation • 29 Nov 2022 • Paul-Gauthier Noé, Xiaoxiao Miao, Xin Wang, Junichi Yamagishi, Jean-François Bonastre, Driss Matrouf
The use of modern vocoders in an analysis/synthesis pipeline allows us to investigate high-quality voice conversion that can be used for privacy purposes.
1 code implementation • 24 Nov 2022 • Xin Yang, Michael Bi Mi, Yuan Yuan, Xin Wang, Robby T. Tan
In our DA framework, we retain the depth and background information during the domain feature alignment.
no code implementations • 21 Nov 2022 • Xin Wang, Hong Chen, Si'ao Tang, Zihao Wu, Wenwu Zhu
Disentangled Representation Learning (DRL) aims to learn a model capable of identifying and disentangling the underlying factors hidden in the observable data in representation form.
no code implementations • 17 Nov 2022 • Ming Yang, Yanhan Wang, Xin Wang, Zhenyong Zhang, Xiaoming Wu, Peng Cheng
Federated learning is a distributed learning that allows each client to keep the original data locally and only upload the parameters of the local model to the server.
no code implementations • 16 Nov 2022 • Xin Wang, Jing-Ke Yan, Jing-Ye Cai, Jian-Hua Deng, Qin Qin, Qin Wang, Heng Xiao, Yao Cheng, Peng-Fei Ye
Therefore, it is often challenging to meet the requirements of High-quality sampling, fast Sampling, and diversity of details and texture after Sampling simultaneously in a SISR task. It leads to model collapse, lack of details and texture features after Sampling, and too long Sampling time in High Resolution (HR) image reconstruction methods.
no code implementations • 14 Nov 2022 • Xin Wang
Traditional GANs fall prey to the mode collapse problem, which means that they are unable to generate the different variations of data present in the input dataset.
1 code implementation • 11 Nov 2022 • Zeyu Hu, Xuyang Bai, Runze Zhang, Xin Wang, Guangyuan Sun, Hongbo Fu, Chiew-Lan Tai
We propose LiDAL, a novel active learning method for 3D LiDAR semantic segmentation by exploiting inter-frame uncertainty among LiDAR frames.
no code implementations • 9 Nov 2022 • Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michal Lukasik, Andreas Veit, Felix Yu, Sanjiv Kumar
By contrast, when the context is irrelevant to the task, the model should ignore it and fall back on its internal knowledge.
no code implementations • 31 Oct 2022 • Yiming Cui, Jiajia Guo, Zheng Cao, Huaze Tang, Chao-Kai Wen, Shi Jin, Xin Wang, Xiaolin Hou
Firstly, an autoencoder KD-based method is introduced by training a student autoencoder to mimic the reconstructed CSI of a pretrained teacher autoencoder.
no code implementations • 21 Oct 2022 • Hui Guo, Xin Wang, Siwei Lyu
Specifically, we authenticate video calls by displaying a distinct pattern on the screen and using the corneal reflection extracted from the images of the call participant's face.
1 code implementation • 20 Oct 2022 • Yanfei Xiang, Xin Wang, Shu Hu, Bin Zhu, Xiaomeng Huang, Xi Wu, Siwei Lyu
Reinforcement learning is applied to solve actual complex tasks from high-dimensional, sensory inputs.
1 code implementation • 19 Oct 2022 • Xin Wang, Junichi Yamagishi
To make better use of pairs of bona fide and spoofed data, this study introduces a contrastive feature loss that can be plugged into the standard training criterion.
no code implementations • 14 Oct 2022 • Mingfu Xue, Xin Wang, Yinghao Wu, Shifeng Ni, Yushu Zhang, Weiqiang Liu
Since the intrinsic feature is composed of unique interpretation of the model's decision, the intrinsic feature can be regarded as fingerprint of the model.
no code implementations • 12 Oct 2022 • Haotian Wu, Peipei Wang, Xin Wang, Ji Xiang, Rui Gong
The compression of videos on social media has destroyed some pixel details that could be used to detect forgeries.
no code implementations • 11 Oct 2022 • Ilya Soloveychik, Ilya Lyubomirsky, Xin Wang, Sudeep Bhoja
This measure allows us to determine the optimal parameters, such as the block size, yielding highest accuracy.
no code implementations • 11 Oct 2022 • Lin Wang, Xiufen Ye, Donghao Zhang, Wanji He, Lie Ju, Yi Luo, Huan Luo, Xin Wang, Wei Feng, Kaimin Song, Xin Zhao, ZongYuan Ge
In this work, we introduce the image matting into the 3D scenes and use the alpha matte, i. e., a soft mask, to describe lesions in a 3D medical image.
no code implementations • 6 Oct 2022 • Feng Zhu, Jingjing Zhang, Xin Wang
Synchronous local stochastic gradient descent (local SGD) suffers from some workers being idle and random delays due to slow and straggling workers, as it waits for the workers to complete the same amount of local updates.
no code implementations • 1 Oct 2022 • Hongwei Wu, Junlin Wang, Xin Wang, Hui Nan, Yaxin Wang, Haonan Jing, Kaixuan Shi
It is a challenge to segment the location and size of rectal cancer tumours through deep learning.
no code implementations • 28 Sep 2022 • Zheng Li, Caili Guo, Xin Wang, Zerun Feng, Jenq-Neng Hwang, Zhongtian Du
More specifically, Triplet loss with Hard Negative mining (Triplet-HN), which is widely used in existing retrieval models to improve the discriminative ability, is easy to fall into local minima in training.
no code implementations • 16 Sep 2022 • Lin Wang, Xiufen Ye, Donghao Zhang, Wanji He, Lie Ju, Xin Wang, Wei Feng, Kaimin Song, Xin Zhao, ZongYuan Ge
It can be caused by many factors, such as the imaging properties, pathological anatomy, and the weak representation of the binary masks, which brings challenges to accurate 3D segmentation.
1 code implementation • 9 Sep 2022 • Hanlei Zhang, Hua Xu, Xin Wang, Qianrui Zhou, Shaojie Zhao, Jiayan Teng
This paper introduces a novel dataset for multimodal intent recognition (MIntRec) to address this issue.
Ranked #1 on
Multimodal Intent Recognition
on MIntRec
no code implementations • 1 Sep 2022 • Chang Zeng, Xiaoxiao Miao, Xin Wang, Erica Cooper, Junichi Yamagishi
Conventional automatic speaker verification systems can usually be decomposed into a front-end model such as time delay neural network (TDNN) for extracting speaker embeddings and a back-end model such as statistics-based probabilistic linear discriminant analysis (PLDA) or neural network-based neural PLDA (NPLDA) for similarity scoring.
no code implementations • 31 Aug 2022 • Dustin Carrión-Ojeda, Hong Chen, Adrian El Baz, Sergio Escalera, Chaoyu Guan, Isabelle Guyon, Ihsan Ullah, Xin Wang, Wenwu Zhu
We present the design and baseline results for a new challenge in the ChaLearn meta-learning series, accepted at NeurIPS'22, focusing on "cross-domain" meta-learning.
no code implementations • 29 Aug 2022 • Faysal Hossain Shezan, Yingjie Lao, Minlong Peng, Xin Wang, Mingming Sun, Ping Li
At the core, NL2GDPR is a privacy-centric information extraction model, appended with a GDPR policy finder and a policy generator.
no code implementations • 22 Aug 2022 • Xin Wang, Jian Sun, Gang Wang, Frank Allgöwer, Jie Chen
The present paper deals with data-driven event-triggered control of a class of unknown discrete-time interconnected systems (a. k. a.
1 code implementation • 16 Aug 2022 • Gur-Eyal Sela, Ionel Gog, Justin Wong, Kumar Krishna Agrawal, Xiangxi Mo, Sukrit Kalra, Peter Schafhalter, Eric Leong, Xin Wang, Bharathan Balaji, Joseph Gonzalez, Ion Stoica
These works evaluate accuracy offline, one image at a time.
no code implementations • 15 Aug 2022 • Xin Wang, Wei Xue, Yilun Han, Guangwen Yang
We develop a user-friendly platform NeuroGCM for efficiently developing hybrid modeling in climate simulation.
1 code implementation • SIGKDD 2022 • Mingchen Sun, Kaixiong Zhou, Xin He, Ying Wang, Xin Wang
Based on the pre-trained model, we propose the graph prompting function to modify the standalone node into a token pair, and reformulate the downstream node classification looking the same as edge prediction.
no code implementations • 13 Aug 2022 • Xin Wang, Heng Chang, Beini Xie, Tian Bian, Shiji Zhou, Daixin Wang, Zhiqiang Zhang, Wenwu Zhu
Graph neural networks (GNNs) have achieved tremendous success in the task of graph classification and its diverse downstream real-world applications.
no code implementations • 8 Aug 2022 • Cenk Baykal, Nishanth Dikkala, Rina Panigrahy, Cyrus Rashtchian, Xin Wang
After representing LSH-based sparse networks with our model, we prove that sparse networks can match the approximation power of dense networks on Lipschitz functions.
no code implementations • 1 Aug 2022 • Xin Wang, Jian Sun, Gang Wang, Jie Chen
This article deals with model- and data-based consensus control of heterogenous leader-following multi-agent systems (MASs) under an event-triggering transmission scheme.
no code implementations • 27 Jul 2022 • Shuyan Hu, Xin Yuan, Wei Ni, Xin Wang
Being a key technology for beyond fifth-generation wireless systems, joint communication and radar sensing (JCAS) utilizes the reflections of communication signals to detect foreign objects and deliver situational awareness.
no code implementations • 24 Jul 2022 • Quanshi Zhang, Xin Wang, Jie Ren, Xu Cheng, Shuyun Lin, Yisen Wang, Xiangming Zhu
This paper summarizes the common mechanism shared by twelve previous transferability-boosting methods in a unified view, i. e., these methods all reduce game-theoretic interactions between regional adversarial perturbations.
1 code implementation • 22 Jul 2022 • Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta, Guchun Zhang, Yinpeng Guo, Zhongqi Li, Qi Zhang, Meng Xiao, Bo Shen, Lin Li, Hao Yu, Li Yan, Pingyi Zhou, Xin Wang, Yuchi Ma, Ignacio Iacobacci, Yasheng Wang, Guangtai Liang, Jiansheng Wei, Xin Jiang, Qianxiang Wang, Qun Liu
We present PanGu-Coder, a pretrained decoder-only language model adopting the PanGu-Alpha architecture for text-to-code generation, i. e. the synthesis of programming language solutions given a natural language problem description.
1 code implementation • 22 Jul 2022 • Yunhao Ge, Harkirat Behl, Jiashu Xu, Suriya Gunasekar, Neel Joshi, Yale Song, Xin Wang, Laurent Itti, Vibhav Vineet
However, existing approaches either require human experts to manually tune each scene property or use automatic methods that provide little to no control; this requires rendering large amounts of random data variations, which is slow and is often suboptimal for the target domain.
no code implementations • 20 Jul 2022 • Ji Zhang, Jean-Paul Ainam, Li-hui Zhao, Wenai Song, Xin Wang
Based on the complementarity of attribute and category labels, we propose a Multi-task Attribute-Scene Recognition (MASR) network which learns a category embedding and at the same time predicts scene attributes.
no code implementations • 18 Jul 2022 • Shu Hu, Xin Wang, Siwei Lyu
Following these categories, we review the literature on rank-based aggregate losses and rank-based individual losses.
1 code implementation • 11 Jul 2022 • Tyler LaBonte, Yale Song, Xin Wang, Vibhav Vineet, Neel Joshi
A critical object detection task is finetuning an existing model to detect novel objects, but the standard workflow requires bounding box annotations which are time-consuming and expensive to collect.
1 code implementation • 8 Jul 2022 • Wei Feng, Lin Wang, Lie Ju, Xin Zhao, Xin Wang, Xiaoyu Shi, ZongYuan Ge
Existing unsupervised domain adaptation methods based on adversarial learning have achieved good performance in several medical imaging tasks.
no code implementations • 7 Jul 2022 • Yaqian Yang, Zhiming Zheng, Longzhao Liu, Hongwei Zheng, Yi Zhen, Yi Zheng, Xin Wang, Shaoting Tang
Specifically, low-frequency eigenmodes, which are considered sufficient to capture the essence of the functional network, contribute little to functional connectivity reconstruction in transmodal regions, resulting in structure-function decoupling along the unimodal-transmodal gradient.
1 code implementation • 18 Jun 2022 • Yijian Qin, Ziwei Zhang, Xin Wang, Zeyang Zhang, Wenwu Zhu
To the best of our knowledge, our work is the first benchmark for graph neural architecture search.
no code implementations • 16 Jun 2022 • Guangxi Li, Ruilin Ye, Xuanqiang Zhao, Xin Wang
This result in particular implies that the average encoded state will concentrate on the maximally mixed state at an exponential speed on depth.
1 code implementation • 15 Jun 2022 • Sheng Zhou, Hongjia Xu, Zhuonan Zheng, Jiawei Chen, Zhao Li, Jiajun Bu, Jia Wu, Xin Wang, Wenwu Zhu, Martin Ester
Motivated by the tremendous success of deep learning in clustering, one of the most fundamental machine learning tasks, and the large number of recent advances in this direction, in this paper we conduct a comprehensive survey on deep clustering by proposing a new taxonomy of different state-of-the-art approaches.
no code implementations • 15 Jun 2022 • Adrian El Baz, Ihsan Ullah, Edesio Alcobaça, André C. P. L. F. Carvalho, Hong Chen, Fabio Ferreira, Henry Gouk, Chaoyu Guan, Isabelle Guyon, Timothy Hospedales, Shell Hu, Mike Huisman, Frank Hutter, Zhengying Liu, Felix Mohr, Ekrem Öztürk, Jan N. van Rijn, Haozhe Sun, Xin Wang, Wenwu Zhu
Although deep neural networks are capable of achieving performance superior to humans on various tasks, they are notorious for requiring large amounts of data and computing resources, restricting their success to domains where such resources are available.
no code implementations • 10 Jun 2022 • Xin Wang, Xiaolin Hou, Lan Chen, Yoshihisa Kishiyama, Takahiro Asai
Considering its large impact on air-interface design, it will be a candidate technology for 6th generation (6G) networks, in which an air interface designed by artificial intelligence can be used.
no code implementations • 6 Jun 2022 • Xin Wang, Xinzhe Luo, Xiahai Zhuang
Multimodal groupwise registration aligns internal structures in a group of medical images.
no code implementations • 26 May 2022 • Xia Liu, Geng Liu, Jiaxin Huang, Hao-Kai Zhang, Xin Wang
Variational quantum algorithms (VQAs) are expected to establish valuable applications on near-term quantum computers.
no code implementations • 23 May 2022 • Xin Wang, Sheng Wang, Honglin Xiong, Kai Xuan, Zixu Zhuang, Mengjun Liu, Zhenrong Shen, Xiangyu Zhao, Lichi Zhang, Qian Wang
Magnetic resonance (MR) images collected in 2D clinical protocols typically have large inter-slice spacing, resulting in high in-plane resolution and reduced through-plane resolution.
no code implementations • 16 May 2022 • Zhan Yu, Hongshun Yao, Mujin Li, Xin Wang
Quantum neural networks (QNNs) have emerged as a leading strategy to establish applications in machine learning, chemistry, and optimization.
1 code implementation • 14 May 2022 • Natalia Tomashenko, Brij Mohan Lal Srivastava, Xin Wang, Emmanuel Vincent, Andreas Nautsch, Junichi Yamagishi, Nicholas Evans, Jose Patino, Jean-François Bonastre, Paul-Gauthier Noé, Massimiliano Todisco
The VoicePrivacy Challenge aims to promote the development of privacy preservation tools for speech technology by gathering a new community to define the tasks of interest and the evaluation methodology, and benchmarking solutions through a series of challenges.
no code implementations • 13 May 2022 • Hui Guo, Shu Hu, Xin Wang, Ming-Ching Chang, Siwei Lyu
In this work, we develop an online platform called Open-eye to study the human performance of AI-synthesized face detection.
no code implementations • 11 May 2022 • Guangxi Li, Xuanqiang Zhao, Xin Wang
Although some efforts based on syntactic analysis have opened the door to research in Quantum NLP (QNLP), limitations such as heavy syntactic preprocessing and syntax-dependent network architecture make them impracticable on larger and real-world data sets.
no code implementations • 10 May 2022 • Hao-Kai Zhang, Chengkai Zhu, Geng Liu, Xin Wang
Exploring quantum applications of near-term quantum devices is a rapidly growing field of quantum information science with both theoretical and practical interests.
no code implementations • 10 May 2022 • Xin Wang, Azim Khan, Jianwu Wang, Aryya Gangopadhyay, Carl E. Busart, Jade Freeman
In this paper, we study how to best leverage edge and cloud resources to achieve better accuracy and latency for stream analytics using a type of RNN model called long short-term memory (LSTM).
no code implementations • Findings (NAACL) 2022 • Xin Wang, Yasheng Wang, Yao Wan, Jiawei Wang, Pingyi Zhou, Li Li, Hao Wu, Jin Liu
Specifically, we first extract multiple code views using compiler tools, and learn the complementary information among them under a contrastive learning framework.
no code implementations • 30 Apr 2022 • Zeyu Han, Xiaojun Yuan, Chongbin Xu, Xin Wang
In this letter, we extend the sparse Kronecker-product (SKP) coding scheme, originally designed for the additive white Gaussian noise (AWGN) channel, to multiple input multiple output (MIMO) unsourced random access (URA).
1 code implementation • 23 Apr 2022 • Baifeng Shi, Yale Song, Neel Joshi, Trevor Darrell, Xin Wang
We present VARS, Visual Attention from Recurrent Sparse reconstruction, a new attention formulation built on two prominent features of the human visual attention mechanism: recurrency and sparsity.
no code implementations • 13 Apr 2022 • Shaojin Ding, Weiran Wang, Ding Zhao, Tara N. Sainath, Yanzhang He, Robert David, Rami Botros, Xin Wang, Rina Panigrahy, Qiao Liang, Dongseong Hwang, Ian McGraw, Rohit Prabhavalkar, Trevor Strohman
In this paper, we propose a dynamic cascaded encoder Automatic Speech Recognition (ASR) model, which unifies models for different deployment scenarios.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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no code implementations • 11 Apr 2022 • Lin Zhang, Xin Wang, Erica Cooper, Nicholas Evans, Junichi Yamagishi
Since the short spoofed speech segments to be embedded by attackers are of variable length, six different temporal resolutions are considered, ranging from as short as 20 ms to as large as 640 ms. Third, we propose a new CM that enables the simultaneous use of the segment-level labels at different temporal resolutions as well as utterance-level labels to execute utterance- and segment-level detection at the same time.
no code implementations • 7 Apr 2022 • Lie Ju, Yicheng Wu, Lin Wang, Zhen Yu, Xin Zhao, Xin Wang, Paul Bonnington, ZongYuan Ge
To address this, in this paper, we propose a curriculum learning-based framework called Flexible Sampling for the long-tailed skin lesion classification task.
1 code implementation • 7 Apr 2022 • Zeyang Zhang, Ziwei Zhang, Xin Wang, Wenwu Zhu
To solve these challenges, we first propose a principled hardness measurement to quantify the hardness of TSP instances.
1 code implementation • 28 Mar 2022 • Xin Wang, Junich Yamagishi
This study took the initiative and investigated CM training using active learning (AL), a framework that iteratively selects useful data from a large pool set and fine-tunes the CM.
no code implementations • 24 Mar 2022 • Zhiyuan Zhai, Xinhong Dai, Bin Duo, Xin Wang, Xiaojun Yuan
Unmanned aerial vehicle (UAV) and reconfigurable intelligent surface (RIS) have been recently applied in the field of mobile edge computing (MEC) to improve the data exchange environment by proactively changing the wireless channels through maneuverable location deployment and intelligent signals reflection, respectively.
1 code implementation • 23 Mar 2022 • Natalia Tomashenko, Xin Wang, Xiaoxiao Miao, Hubert Nourtel, Pierre Champion, Massimiliano Todisco, Emmanuel Vincent, Nicholas Evans, Junichi Yamagishi, Jean-François Bonastre
Participants apply their developed anonymization systems, run evaluation scripts and submit objective evaluation results and anonymized speech data to the organizers.
no code implementations • 10 Mar 2022 • Xiaohan Lan, Yitian Yuan, Xin Wang, Long Chen, Zhi Wang, Lin Ma, Wenwu Zhu
New benchmarking results indicate that our proposed evaluation protocols can better monitor the research progress.
no code implementations • Findings (ACL) 2022 • Xin Wang, Yasheng Wang, Yao Wan, Fei Mi, Yitong Li, Pingyi Zhou, Jin Liu, Hao Wu, Xin Jiang, Qun Liu
Automatically generating compilable programs with (or without) natural language descriptions has always been a touchstone problem for computational linguistics and automated software engineering.
1 code implementation • CVPR 2022 • Xuefeng Du, Xin Wang, Gabriel Gozum, Yixuan Li
Building reliable object detectors that can detect out-of-distribution (OOD) objects is critical yet underexplored.
no code implementations • 1 Mar 2022 • Zhan Yu, Xuanqiang Zhao, Benchi Zhao, Xin Wang
In this work, we solve the problem on the minimum size of sufficient quantum datasets for learning a unitary transformation exactly, which reveals the power and limitation of quantum data.
no code implementations • 27 Feb 2022 • Chen Gong, Kong Bin, Eric J. Seibel, Xin Wang, Youbing Yin, Qi Song
Taking the expertise of DNNs to learn meaningful patterns before fitting noise, our framework first trains two networks over the current dataset with small loss selection.
1 code implementation • 24 Feb 2022 • Hemlata Tak, Massimiliano Todisco, Xin Wang, Jee-weon Jung, Junichi Yamagishi, Nicholas Evans
The performance of spoofing countermeasure systems depends fundamentally upon the use of sufficiently representative training data.
no code implementations • 16 Feb 2022 • Xin Wang, Julian Berberich, Jian Sun, Gang Wang, Frank Allgöwer, Jie Chen
To this end, we begin by presenting a dynamic event-triggering scheme (ETS) based on periodic sampling, and a discrete-time looped-functional approach, through which a model-based stability condition is derived.
no code implementations • 16 Feb 2022 • Haoyang Li, Xin Wang, Ziwei Zhang, Wenwu Zhu
This paper is the first systematic and comprehensive review of OOD generalization on graphs, to the best of our knowledge.
no code implementations • 15 Feb 2022 • Xin Wang, Hui Guo, Shu Hu, Ming-Ching Chang, Siwei Lyu
Generative Adversarial Networks (GAN) have led to the generation of very realistic face images, which have been used in fake social media accounts and other disinformation matters that can generate profound impacts.
no code implementations • COLING 2022 • Yihe Wang, Yitong Li, Yasheng Wang, Fei Mi, Pingyi Zhou, Xin Wang, Jin Liu, Xin Jiang, Qun Liu
Experiments over publicly available datasets demonstrate that our method can help models generate better responses, even such training data are usually impressed as low-quality data.
no code implementations • 23 Jan 2022 • Xin Wang, Serdar Kadioglu
We introduce a pattern mining framework that operates on semi-structured datasets and exploits the dichotomy between outcomes.
no code implementations • 12 Jan 2022 • Feng Zhu, Jingjing Zhang, Osvaldo Simeone, Xin Wang
Wall-clock convergence time and communication load are key performance metrics for the distributed implementation of stochastic gradient descent (SGD) in parameter server settings.
1 code implementation • CVPR 2022 • Ching-Yao Chuang, R Devon Hjelm, Xin Wang, Vibhav Vineet, Neel Joshi, Antonio Torralba, Stefanie Jegelka, Yale Song
Contrastive learning relies on an assumption that positive pairs contain related views, e. g., patches of an image or co-occurring multimodal signals of a video, that share certain underlying information about an instance.
1 code implementation • 10 Jan 2022 • Xin Wang, Junichi Yamagishi
Presentation attack detection (PAD) for ASV, or speech anti-spoofing, is therefore indispensable.
no code implementations • 4 Jan 2022 • Wenwu Zhu, Xin Wang, Pengtao Xie
Inspired by the concept of self-directed human learning, we introduce the principal concept of Self-directed Machine Learning (SDML) and propose a framework for SDML.
1 code implementation • 4 Jan 2022 • Xin Wang, Ziwei Zhang, Wenwu Zhu
Graph machine learning has been extensively studied in both academic and industry.
no code implementations • 3 Jan 2022 • Mingfu Xue, Xin Wang, Shichang Sun, Yushu Zhang, Jian Wang, Weiqiang Liu
After training, the backdoor attack against DNN is robust to image compression.
no code implementations • 23 Dec 2021 • Ziwei Zhang, Xin Wang, Zeyang Zhang, Peng Cui, Wenwu Zhu
Based on the experimental results, we advocate that TinvNN should be considered a new starting point and an essential baseline for further studies of transformation-invariant geometric deep learning.
no code implementations • 21 Dec 2021 • Xin Wang, Hong Shen
Coflow is a recently proposed networking abstraction to help improve the communication performance of data-parallel computing jobs.
no code implementations • 20 Dec 2021 • Xuanjie Li, Yuedong Xu, Jessie Hui Wang, Xin Wang, John C. S. Lui
By transforming our decentralized algorithm into a centralized inexact proximal gradient algorithm with variance reduction, and controlling the bounds of error sequences, we prove that DPSVRG converges at the rate of $O(1/T)$ for general convex objectives plus a non-smooth term with $T$ as the number of iterations, while DSPG converges at the rate $O(\frac{1}{\sqrt{T}})$.
1 code implementation • 17 Dec 2021 • Xin Wang, Pei Guo, Xingyan Li, Aryya Gangopadhyay, Carl E. Busart, Jade Freeman, Jianwu Wang
To tackle these problems, we leverage serverless computing and containerization techniques for automated scalable execution and reproducibility, and utilize the adapter design pattern to enable application portability and reproducibility across different clouds.
1 code implementation • 14 Dec 2021 • Ziwei Luo, Jing Hu, Xin Wang, Siwei Lyu, Bin Kong, Youbing Yin, Qi Song, Xi Wu
Training a model-free deep reinforcement learning model to solve image-to-image translation is difficult since it involves high-dimensional continuous state and action spaces.
1 code implementation • 14 Dec 2021 • Ziwei Luo, Jing Hu, Xin Wang, Shu Hu, Bin Kong, Youbing Yin, Qi Song, Xi Wu, Siwei Lyu
We evaluate our method on several 2D and 3D medical image datasets, some of which contain large deformations.
no code implementations • 9 Dec 2021 • Ju Kang, Shijie Zhang, Xin Wang
Explaining biodiversity is a fundamental issue in ecology.
no code implementations • 9 Dec 2021 • Fei Wang, Xilei Wu, Xin Wang, Jianlei Chi, Jingang Shi, Dong Huang
We propose UWash, an intelligent solution upon smartwatches, to assess handwashing for the purpose of raising users' awareness and cultivating habits in high-quality handwashing.
no code implementations • 7 Dec 2021 • Haoyang Li, Xin Wang, Ziwei Zhang, Wenwu Zhu
Our proposed OOD-GNN employs a novel nonlinear graph representation decorrelation method utilizing random Fourier features, which encourages the model to eliminate the statistical dependence between relevant and irrelevant graph representations through iteratively optimizing the sample graph weights and graph encoder.
1 code implementation • NeurIPS 2021 • Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Yiting Chen, Xu Cheng, Xin Wang, Meng Zhou, Jie Shi, Quanshi Zhang
This paper provides a unified view to explain different adversarial attacks and defense methods, i. e. the view of multi-order interactions between input variables of DNNs.
1 code implementation • NeurIPS 2021 • Hong Chen, Yudong Chen, Xin Wang, Ruobing Xie, Rui Wang, Feng Xia, Wenwu Zhu
However, learning such disentangled representations from multi-feedback data is challenging because i) multi-feedback is complex: there exist complex relations among different types of feedback (e. g., click, unclick, and dislike, etc) as well as various user intentions, and ii) multi-feedback is noisy: there exists noisy (useless) information both in features and labels, which may deteriorate the recommendation performance.
1 code implementation • NeurIPS 2021 • Heng Chang, Yu Rong, Tingyang Xu, Yatao Bian, Shiji Zhou, Xin Wang, Junzhou Huang, Wenwu Zhu
Graph Convolutional Networks (GCNs) are promising deep learning approaches in learning representations for graph-structured data.
no code implementations • NeurIPS 2021 • Haoyang Li, Xin Wang, Ziwei Zhang, Zehuan Yuan, Hang Li, Wenwu Zhu
Then we propose a novel factor-wise discrimination objective in a contrastive learning manner, which can force the factorized representations to independently reflect the expressive information from different latent factors.
no code implementations • NeurIPS 2021 • Yijian Qin, Xin Wang, Zeyang Zhang, Wenwu Zhu
Extensive experiments on real-world graph datasets demonstrate that our proposed GASSO model is able to achieve state-of-the-art performance compared with existing baselines.
no code implementations • 23 Nov 2021 • Shaobo Guo, Xiao Jiang, Zhizhong Su, Rui Wu, Xin Wang
As a critical cue for understanding human intention, human gaze provides a key signal for Human-Computer Interaction(HCI) applications.
no code implementations • 22 Nov 2021 • Bernard Kleynhans, Xin Wang, Serdar Kadıoğlu
Designing recommendation systems with limited or no available training data remains a challenge.
no code implementations • 17 Nov 2021 • Lie Ju, Zhen Yu, Lin Wang, Xin Zhao, Xin Wang, Paul Bonnington, ZongYuan Ge
From a modeling perspective, most deep learning models trained on these datasets may lack the ability to generalize to rare diseases where only a few available samples are presented for training.
1 code implementation • 15 Nov 2021 • Xin Wang, Junichi Yamagishi
Self-supervised speech model is a rapid progressing research topic, and many pre-trained models have been released and used in various down stream tasks.
1 code implementation • 5 Nov 2021 • Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Yiting Chen, Xu Cheng, Xin Wang, Meng Zhou, Jie Shi, Quanshi Zhang
This paper provides a unified view to explain different adversarial attacks and defense methods, \emph{i. e.} the view of multi-order interactions between input variables of DNNs.
no code implementations • 28 Oct 2021 • Haotian Xue, Kaixiong Zhou, Tianlong Chen, Kai Guo, Xia Hu, Yi Chang, Xin Wang
In this paper, we investigate GNNs from the lens of weight and feature loss landscapes, i. e., the loss changes with respect to model weights and node features, respectively.
no code implementations • 25 Oct 2021 • Xin Wang, Jian Sun, Julian Berberich, Gang Wang, Frank Allgöwer, Jie Chen
Data-based representations for time-invariant linear systems with known or unknown system input matrices are first developed, along with a novel class of dynamic triggering schemes for sampled-data systems with time delays.
no code implementations • 21 Oct 2021 • ZongYuan Ge, Xin Wang
The current generation of deep neural networks has achieved close-to-human results on "closed-set" image recognition; that is, the classes being evaluated overlap with the training classes.
1 code implementation • 15 Oct 2021 • Xin Wang
The quantum circuits are comprised with single-qubit rotation gates implementing on each qubit.
1 code implementation • 10 Oct 2021 • Xin Wang, Junichi Yamagishi
On the ASVspoof2019 logical access database, the results demonstrate that an energy-based estimator and a neural-network-based one achieved acceptable performance in identifying unknown attacks in the test set.
no code implementations • 29 Sep 2021 • Rina Panigrahy, Brendan Juba, Zihao Deng, Xin Wang, Zee Fryer
We propose a modular architecture for lifelong learning of hierarchically structured tasks.
no code implementations • 29 Sep 2021 • Xu Cheng, Xin Wang, Haotian Xue, Zhengyang Liang, Xin Jin, Quanshi Zhang
This paper proposes a hypothesis to analyze the underlying reason for the cognitive difficulty of an image from two perspectives, i. e. a cognitive image usually makes a DNN strongly activated by cognitive concepts; discarding massive non-cognitive concepts may also help the DNN focus on cognitive concepts.