1 code implementation • ACL 2022 • Yan Liu, Sanyuan Chen, Yazheng Yang, Qi Dai
In this paper, we propose a multi-level Mutual Promotion mechanism for self-evolved Inference and sentence-level Interpretation (MPII).
1 code implementation • 8 Jun 2023 • Ruijie Zhang, Qiaozhe Zhang, Yingzhuang Liu, Hao Xin, Yan Liu, Xinggang Wang
The combination of both should provide new insights for deep learning based image diagnosis.
no code implementations • 25 May 2023 • Yan Liu, Yan Gao, Zhe Su, Xiaokang Chen, Elliott Ash, Jian-Guang Lou
In this work, we aim to uncover and categorize social biases in Text-to-SQL models.
no code implementations • 24 May 2023 • Yan Liu, Xiaokang Chen, Yan Gao, Zhe Su, Fengji Zhang, Daoguang Zan, Jian-Guang Lou, Pin-Yu Chen, Tsung-Yi Ho
In this work, we explore the social bias problem in pre-trained code generation models.
no code implementations • 15 Apr 2023 • Yizhou Zhang, Loc Trinh, Defu Cao, Zijun Cui, Yan Liu
Recent years have witnessed the sustained evolution of misinformation that aims at manipulating public opinions.
1 code implementation • 3 Apr 2023 • Lianghui Zhu, Yingyue Li, Jiemin Fang, Yan Liu, Hao Xin, Wenyu Liu, Xinggang Wang
Thus a novel weight-based method is proposed to end-to-end estimate the importance of attention heads, while the self-attention maps are adaptively fused for high-quality CAM results that tend to have more complete objects.
Weakly-supervised Learning Weakly supervised Semantic Segmentation +1
no code implementations • 4 Mar 2023 • Defu Cao, James Enouen, Yujing Wang, Xiangchen Song, Chuizheng Meng, Hao Niu, Yan Liu
Causal analysis for time series data, in particular estimating individualized treatment effect (ITE), is a key task in many real-world applications, such as finance, retail, healthcare, etc.
no code implementations • 23 Feb 2023 • Kun Yang, Jing Liu, Dingkang Yang, Hanqi Wang, Peng Sun, Yanni Zhang, Yan Liu, Liang Song
With the rapid development of intelligent transportation system applications, a tremendous amount of multi-view video data has emerged to enhance vehicle perception.
no code implementations • 21 Feb 2023 • Yan Liu, Xiaokang Chen, Qi Dai
However, current works pursuing sentence-level explanations rely heavily on annotated training data, which limits the development of interpretability to only a few tasks.
no code implementations • 19 Feb 2023 • Defu Cao, James Enouen, Yan Liu
Estimating treatment effects plays a crucial role in causal inference, having many real-world applications like policy analysis and decision making.
no code implementations • 6 Feb 2023 • Zengyou He, Yifan Tang, Lianyu Hu, Mudi Jiang, Yan Liu
In addition to the problem formulation on this new issue, we present a greedy algorithm called PIC (Personalized Interpretable Classifier) to identify a personalized rule for each individual test sample.
no code implementations • CVPR 2023 • Defu Cao, Zhaowen Wang, Jose Echevarria, Yan Liu
Advances in representation learning have led to great success in understanding and generating data in various domains.
no code implementations • 17 Nov 2022 • Defu Cao, Yousef El-Laham, Loc Trinh, Svitlana Vyetrenko, Yan Liu
Using the proposed synthetic dataset, we provide a holistic analysis on the forecasting performance of three different state-of-the-art forecasting methods.
no code implementations • 17 Nov 2022 • Xiaokang Chen, Jiahui Chen, Yan Liu, Gang Zeng
Specifically, Adaptive Matching applies bipartite matching to adaptively match the outputs of the teacher and the student in each decoder layer, while Fixed Matching fixes the correspondence between the outputs of the teacher and the student with the same object queries, with the teacher's fixed object queries fed to the decoder of the student as an auxiliary group.
1 code implementation • 8 Nov 2022 • Lianyu Hu, Mudi Jiang, Yan Liu, Zengyou He
As a by-product, we can further calculate an empirical $p$-value to assess the statistical significance of a set of clusters and develop an improved gap statistic for estimating the cluster number.
no code implementations • 2 Nov 2022 • Le Xie, Tong Huang, Xiangtian Zheng, Yan Liu, Mengdi Wang, Vijay Vittal, P. R. Kumar, Srinivas Shakkottai, Yi Cui
The transition towards carbon-neutral electricity is one of the biggest game changers in addressing climate change since it addresses the dual challenges of removing carbon emissions from the two largest sectors of emitters: electricity and transportation.
no code implementations • 14 Oct 2022 • Yizhou Zhang, Defu Cao, Yan Liu
To address these issues, in this paper, we build up a causal framework that model the causal effect of misinformation from the perspective of temporal point process.
1 code implementation • 21 Sep 2022 • Yan Liu, Maria Laricheva, Chiyu Zhang, Patrick Boutet, GuanYu Chen, Terence Tracey, Giuseppe Carenini, Richard Young
This study is to explore how to use natural language processing (NLP) methods, especially unsupervised machine learning, to assist psychologists to analyze emotions and sentiments and to use topic modeling to identify common issues and challenges that young people with IDD and their families have.
no code implementations • 19 Sep 2022 • James Enouen, Yan Liu
There is currently a large gap in performance between the statistically rigorous methods like linear regression or additive splines and the powerful deep methods using neural networks.
1 code implementation • 12 Aug 2022 • Maria Laricheva, Chiyu Zhang, Yan Liu, GuanYu Chen, Terence Tracey, Richard Young, Giuseppe Carenini
Conversational data is essential in psychology because it can help researchers understand individuals cognitive processes, emotions, and behaviors.
no code implementations • 8 Aug 2022 • Jiawei Li, Bolin Jiang, Yan Liu, Chengxiao Luo, Naiqi Li, Bin Chen
To make a step forward, this paper outlines an automatic annotation system called SsaA, working in a self-supervised learning manner, for continuously making the online visual inspection in the manufacturing automation scenarios.
no code implementations • 27 Jul 2022 • Elias Munoz, Pierre Baudot, Van-Khoa Le, Charles Voyton, Benjamin Renoust, Danny Francis, Vladimir Groza, Jean-Christophe Brisset, Ezequiel Geremia, Antoine Iannessi, Yan Liu, Benoit Huet
This framework is applied to the prediction of the malignancy of lung's nodules.
1 code implementation • IJCAI 2022 • Bruce X.B. Yu, Yan Liu, Xiang Zhang, Gong Chen, Keith C.C. Chan
We also examine the properness of existing evaluation criteria and focus on evaluating the prediction ability of our proposed method.
Ranked #1 on Action Assessment on KIMORE
1 code implementation • Proceedings of the AAAI Conference on Artificial Intelligence 2022 • Sirisha Rambhatla, Zhengping Che, Yan Liu
To this end, we develop an Importance Sampling based distance metric -- I-SEA -- which enjoys the properties of a metric while consistently achieving superior performance for machine learning tasks such as classification and representation learning.
no code implementations • 20 Jun 2022 • Yan Liu
To this end, we incorporate the marginal treatment effects (MTE) when identifying treatment effect parameters and consider encouragement rules that affect social welfare through treatment take-up when designing policies.
1 code implementation • IEEE Transactions on Pattern Analysis and Machine Intelligence 2022 • Bruce X.B. Yu, Yan Liu, Xiang Zhang, Sheng-hua Zhong, Keith C.C. Chan
Upon aggregating the results of multiple modalities, our method is found to outperform state-of-the-art approaches on six evaluation protocols of the five datasets; thus, the proposed MMNet can effectively capture mutually complementary features in different RGB-D video modalities and provide more discriminative features for HAR.
Ranked #1 on Action Recognition In Videos on PKU-MMD (using extra training data)
no code implementations • 31 Mar 2022 • Chuizheng Meng, Sungyong Seo, Defu Cao, Sam Griesemer, Yan Liu
Physics-informed machine learning (PIML), referring to the combination of prior knowledge of physics, which is the high level abstraction of natural phenomenons and human behaviours in the long history, with data-driven machine learning models, has emerged as an effective way to mitigate the shortage of training data, to increase models' generalizability and to ensure the physical plausibility of results.
BIG-bench Machine Learning Physics-informed machine learning
1 code implementation • 24 Feb 2022 • Karishma Sharma, Emilio Ferrara, Yan Liu
Malicious accounts spreading misinformation has led to widespread false and misleading narratives in recent times, especially during the COVID-19 pandemic, and social media platforms struggle to eliminate these contents rapidly.
2 code implementations • 17 Feb 2022 • Wenjie Du, David Cote, Yan Liu
Missing data in time series is a pervasive problem that puts obstacles in the way of advanced analysis.
1 code implementation • 14 Feb 2022 • Zhensu Sun, Yan Liu, Xiaoning Du, Li Li
The performance of neural code search is significantly influenced by the quality of the training data from which the neural models are derived.
1 code implementation • 21 Jan 2022 • Zhejing Hu, Yan Liu, Gong Chen, Yongxu Liu
User preference music transfer (UPMT) is a new problem in music style transfer that can be applied to many scenarios but remains understudied.
no code implementations • 9 Jan 2022 • Yan Liu, Qingyong Hu, Yinjie Lei, Kai Xu, Jonathan Li, Yulan Guo
In this paper, we introduce a neural architecture, termed Box2Seg, to learn point-level semantics of 3D point clouds with bounding box-level supervision.
1 code implementation • 8 Jan 2022 • Wenjie Du, David Cote, Chris Barber, Yan Liu
Furthermore, we show that it is possible to forecast LOS from all facility types and all networks with a single model, whereas fine-tuning for a particular facility or network only brings modest improvements.
BIG-bench Machine Learning Classification on Time Series with Missing Data
no code implementations • 29 Nov 2021 • Weiliang Tao, Yan Liu, Zhimin Ma, Wenbin Hu
This paper proposes a novel particle image velocimetry (PIV) technique to generate an instantaneous two-dimensional velocity field for sediment-laden fluid based on the optical flow algorithm of ultrasound imaging.
no code implementations • 17 Nov 2021 • Yan Liu, Yansha Deng, Maged Elkashlan, Arumugam Nallanathan, George K. Karagiannidis
To support these requirements, the third generation partnership project (3GPP) has introduced enhanced grant-free (GF) transmission in the uplink (UL), with multiple active configured-grants (CGs) for URLLC UEs.
1 code implementation • 15 Nov 2021 • Yaoming Cai, Zijia Zhang, Yan Liu, Pedram Ghamisi, Kun Li, Xiaobo Liu, Zhihua Cai
Specifically, we exploit a symmetric twin neural network comprised of a projection head with a dimensionality of the cluster number to conduct dual contrastive learning from a spectral-spatial augmentation pool.
no code implementations • 29 Oct 2021 • Chenyu Shen, Wenjun Xia, Hongwei Ye, Mingzheng Hou, Hu Chen, Yan Liu, Jiliu Zhou, Yi Zhang
Positron emission tomography (PET) reconstruction has become an ill-posed inverse problem due to low-count projection data, and a robust algorithm is urgently required to improve imaging quality.
no code implementations • NeurIPS 2021 • Yizhou Zhang, Karishma Sharma, Yan Liu
Specifically, when modeling the observed data from social media with neural temporal point process, we jointly learn a Gibbs-like distribution of group assignment based on how consistent an assignment is to (1) the account embedding space and (2) the prior knowledge.
1 code implementation • NeurIPS 2021 • Yan Liu, Zhijie Zhang, Li Niu, Junjie Chen, Liqing Zhang
Specifically, the ability of using mask prior to help detect objects is learned from base categories and transferred to novel categories.
1 code implementation • 12 Oct 2021 • Xiangtian Zheng, Nan Xu, Loc Trinh, Dongqi Wu, Tong Huang, S. Sivaranjani, Yan Liu, Le Xie
The electric grid is a key enabling infrastructure for the ambitious transition towards carbon neutrality as we grapple with climate change.
no code implementations • 11 Oct 2021 • Nuo Li, Bin Guo, Yan Liu, Lina Yao, Jiaqi Liu, Zhiwen Yu
On the one hand, we model the rich correlations between the users' diverse behaviors (e. g., answer, follow, vote) to obtain the individual-level behavior interaction.
no code implementations • 10 Oct 2021 • Yan Liu, Yazheng Yang
Long text understanding is important yet challenging in natural language processing.
no code implementations • 14 Sep 2021 • Chuan-Fei Zhang, Yan Liu, Tian-Hao Zhang, Song-Lu Chen, Feng Chen, Xu-Cheng Yin
To tackle the above problems, we propose a new non-autoregressive transformer with a unified bidirectional decoder (NAT-UBD), which can simultaneously utilize left-to-right and right-to-left contexts.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 7 Sep 2021 • Zhi Zhang, Sheng-hua Zhong, Yan Liu
Data augmentation has recently achieved considerable performance improvement for deep learning models: increased accuracy, stability, and reduced over-fitting.
no code implementations • 18 Aug 2021 • Huqun Suri, Qi Zhang, Wenhua Huo, Yan Liu, Chunsheng Guan
In this paper, we introduce MeDiaQA, a novel question answering(QA) dataset, which constructed on real online Medical Dialogues.
1 code implementation • 6 Aug 2021 • Yulin Li, Yuxi Qian, Yuchen Yu, Xiameng Qin, Chengquan Zhang, Yan Liu, Kun Yao, Junyu Han, Jingtuo Liu, Errui Ding
Due to the complexity of content and layout in VRDs, structured text understanding has been a challenging task.
no code implementations • 17 Jul 2021 • Karishma Sharma, Emilio Ferrara, Yan Liu
Identifying and characterizing disinformation in political discourse on social media is critical to ensure the integrity of elections and democratic processes around the world.
no code implementations • 25 Jun 2021 • Yan Liu, Zheng Li, Lin Li, Qingyang Hong
This paper proposes a multi-task learning network with phoneme-aware and channel-wise attentive learning strategies for text-dependent Speaker Verification (SV).
no code implementations • Pattern Recognition 2021 • Bruce X. B. Yu, Yan Liu, Keith C. C. Chan, Qintai Yang, Xiaoying Wang
In this paper, we propose a two-task graph convolutional network (2T-GCN) to represent skeleton data for HAE tasks involving abnormality detection and quality evaluation.
Ranked #2 on Action Assessment on EHE
no code implementations • 15 Jun 2021 • Karishma Sharma, Yizhou Zhang, Yan Liu
In this work, we investigate misinformation communities and narratives that can contribute to COVID-19 vaccine hesitancy.
1 code implementation • 9 Jun 2021 • Chuizheng Meng, Sirisha Rambhatla, Yan Liu
Vast amount of data generated from networks of sensors, wearables, and the Internet of Things (IoT) devices underscores the need for advanced modeling techniques that leverage the spatio-temporal structure of decentralized data due to the need for edge computation and licensing (data access) issues.
1 code implementation • Association for the Advancement of Artificial Intelligence (AAAI) 2021 • Bruce X.B. Yu, Yan Liu, Keith C.C. Chan
In our TSMF, we utilize a teacher network to transfer the structural knowledge of the skeleton modality to a student network for the RGB modality.
Ranked #2 on Action Recognition In Videos on PKU-MMD (using extra training data)
no code implementations • 14 May 2021 • Zhiwen Wang, Wenjun Xia, Zexin Lu, Yongqiang Huang, Yan Liu, Hu Chen, Jiliu Zhou, Yi Zhang
Magnetic resonance imaging (MRI) acquisition, reconstruction, and segmentation are usually processed independently in the conventional practice of MRI workflow.
no code implementations • 2 May 2021 • Loc Trinh, Yan Liu
Recent studies have demonstrated that deep learning models can discriminate based on protected classes like race and gender.
1 code implementation • 21 Apr 2021 • Ren Yang, Radu Timofte, Jing Liu, Yi Xu, Xinjian Zhang, Minyi Zhao, Shuigeng Zhou, Kelvin C. K. Chan, Shangchen Zhou, Xiangyu Xu, Chen Change Loy, Xin Li, Fanglong Liu, He Zheng, Lielin Jiang, Qi Zhang, Dongliang He, Fu Li, Qingqing Dang, Yibin Huang, Matteo Maggioni, Zhongqian Fu, Shuai Xiao, Cheng Li, Thomas Tanay, Fenglong Song, Wentao Chao, Qiang Guo, Yan Liu, Jiang Li, Xiaochao Qu, Dewang Hou, Jiayu Yang, Lyn Jiang, Di You, Zhenyu Zhang, Chong Mou, Iaroslav Koshelev, Pavel Ostyakov, Andrey Somov, Jia Hao, Xueyi Zou, Shijie Zhao, Xiaopeng Sun, Yiting Liao, Yuanzhi Zhang, Qing Wang, Gen Zhan, Mengxi Guo, Junlin Li, Ming Lu, Zhan Ma, Pablo Navarrete Michelini, Hai Wang, Yiyun Chen, Jingyu Guo, Liliang Zhang, Wenming Yang, Sijung Kim, Syehoon Oh, Yucong Wang, Minjie Cai, Wei Hao, Kangdi Shi, Liangyan Li, Jun Chen, Wei Gao, Wang Liu, XiaoYu Zhang, Linjie Zhou, Sixin Lin, Ru Wang
This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with a focus on the proposed methods and results.
no code implementations • 3 Apr 2021 • Tao Wang, Wenjun Xia, Zexin Lu, Huaiqiang Sun, Yan Liu, Hu Chen, Jiliu Zhou, Yi Zhang
Since the dual-domain MAR methods can leverage the hybrid information from both sinogram and image domains, they have significantly improved the performance compared to single-domain methods.
no code implementations • 16 Mar 2021 • Hongjie He, Ke Yang, Yuwei Cai, Zijian Jiang, Qiutong Yu, Kun Zhao, JunBo Wang, Sarah Narges Fatholahi, Yan Liu, Hasti Andon Petrosians, Bingxu Hu, Liyuan Qing, Zhehan Zhang, Hongzhang Xu, Siyu Li, Kyle Gao, Linlin Xu, Jonathan Li
Building rooftop data are of importance in several urban applications and in natural disaster management.
no code implementations • 1 Mar 2021 • Michael Tsang, James Enouen, Yan Liu
Interpretation of deep learning models is a very challenging problem because of their large number of parameters, complex connections between nodes, and unintelligible feature representations.
1 code implementation • 16 Feb 2021 • Tao Wang, Wenjun Xia, Yongqiang Huang, Huaiqiang Sun, Yan Liu, Hu Chen, Jiliu Zhou, Yi Zhang
With the rapid development of deep learning in the field of medical imaging, several network models have been proposed for metal artifact reduction (MAR) in CT.
no code implementations • 12 Feb 2021 • Chuizheng Meng, Loc Trinh, Nan Xu, Yan Liu
The recent release of large-scale healthcare datasets has greatly propelled the research of data-driven deep learning models for healthcare applications.
no code implementations • 11 Jan 2021 • Yan Liu, Mireille Schnitzer, Guanbo Wang, Edward Kennedy, Piret Viiklepp, Mario H. Vargas, Giovanni Sotgiu, Dick Menzies, Andrea Benedetti
We propose a marginal structural model (MSM) for effect modification by different patient characteristics and co-medications in a meta-analysis of observational IPD.
no code implementations • 1 Jan 2021 • Nan Xu, Nitin Kamra, Yan Liu
Treatment recommendation is a complex multi-faceted problem with many conflicting objectives, e. g., optimizing the survival rate (or expected lifetime), mitigating negative impacts, reducing financial expenses and time costs, avoiding over-treatment, etc.
no code implementations • 1 Jan 2021 • Guangyu Li, Jiahao Chen, Samuel A Assefa, Yan Liu
We present augmented counterfactual ordinary differential equations (ACODEs), a new approach to counterfactual inference on time series data with a focus on healthcare applications.
no code implementations • 1 Jan 2021 • Yizhou Zhang, Zhaoheng Zheng, Yan Liu
Recent researches have achieved substantial advances in learning structured representations from images.
no code implementations • 1 Jan 2021 • Nitin Kamra, Yan Liu
Resource allocation for coverage of physical spaces is a challenging problem in robotic surveillance, mobile sensor networks and security domains.
1 code implementation • 22 Dec 2020 • Liye Mei, Yalan Yu, Yueyun Weng, Xiaopeng Guo, Yan Liu, Du Wang, Sheng Liu, Fuling Zhou, Cheng Lei
Since manual analysis is highly time and effort consuming, computer-assisted automatic chromosome karyotype analysis based on images is routinely used to improve the efficiency and accuracy of the analysis.
1 code implementation • 14 Dec 2020 • Sirisha Rambhatla, Sepanta Zeighami, Kameron Shahabi, Cyrus Shahabi, Yan Liu
As countries look towards re-opening of economic activities amidst the ongoing COVID-19 pandemic, ensuring public health has been challenging.
1 code implementation • 13 Dec 2020 • Yi Zhang, Hu Chen, Wenjun Xia, Yang Chen, Baodong Liu, Yan Liu, Huaiqiang Sun, Jiliu Zhou
Compressed sensing (CS) computed tomography has been proven to be important for several clinical applications, such as sparse-view computed tomography (CT), digital tomosynthesis and interior tomography.
no code implementations • 23 Nov 2020 • Yan Liu, Yansha Deng, Maged Elkashlan, Arumugam Nallanathan, Jinhong Yuan, Ranjan K. Mallik
In this work, we analyze RACH success probability in a self-powered NB-IoT network taking into account the repeated preamble transmissions and collisions, where each IoT device with data is active when its battery energy is sufficient to support the transmission.
1 code implementation • NeurIPS 2020 • Nitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang, Yan Liu
Trajectory prediction for scenes with multiple agents and entities is a challenging problem in numerous domains such as traffic prediction, pedestrian tracking and path planning.
no code implementations • 27 Oct 2020 • Xiang Chen, Wenjun Xia, Yan Liu, Hu Chen, Jiliu Zhou, Yi Zhang
Spectral computed tomography (CT) can reconstruct spectral images from different energy bins using photon counting detectors (PCDs).
no code implementations • 27 Oct 2020 • Wenjun Xia, Zexin Lu, Yongqiang Huang, Yan Liu, Hu Chen, Jiliu Zhou, Yi Zhang
Current mainstream of CT reconstruction methods based on deep learning usually needs to fix the scanning geometry and dose level, which will significantly aggravate the training cost and need more training data for clinical application.
no code implementations • 10 Oct 2020 • Chaojun Li, Yan Liu
We prove the asymptotic properties of the maximum likelihood estimator (MLE) in time-varying transition probability (TVTP) regime-switching models.
no code implementations • 14 Sep 2020 • Yan Liu, Yansha Deng, Nan Jiang, Maged Elkashlan, Arumugam Nallanathan
NarrowBand-Internet of Things (NB-IoT) is a new 3GPP radio access technology designed to provide better coverage for Low Power Wide Area (LPWA) networks.
no code implementations • 3 Sep 2020 • Nitin Kamra, Yizhou Zhang, Sirisha Rambhatla, Chuizheng Meng, Yan Liu
Epidemic spread in a population is traditionally modeled via compartmentalized models which represent the free evolution of disease in absence of any intervention policies.
no code implementations • 11 Aug 2020 • Mubarak Albarka Umar, Chen Zhanfang, Yan Liu
We evaluate the effectiveness of our propose method by comparing it with the baseline models and also with state-of-the-art works.
no code implementations • 8 Aug 2020 • Karishma Sharma, Xinran He, Sungyong Seo, Yan Liu
Users influential in the propagation of true and fake contents are identified using the inferred diffusion dynamics.
no code implementations • ECCV 2020 • Yan Liu, Lingqiao Liu, Peng Wang, Pingping Zhang, Yinjie Lei
Most existing crowd counting systems rely on the availability of the object location annotation which can be expensive to obtain.
no code implementations • 29 Jun 2020 • Zhenyu Liu, Yaqiang Yao, Yan Liu, Yuening Zhu, Zhenchao Tao, Lei Wang, Yuhong Feng
In the proposed method, an activity is divided into several successive actions represented by spatio temporal patterns, and the evolution of these actions are captured by a sequential model.
no code implementations • 28 Jun 2020 • Loc Trinh, Michael Tsang, Sirisha Rambhatla, Yan Liu
In this paper we propose a novel human-centered approach for detecting forgery in face images, using dynamic prototypes as a form of visual explanations.
1 code implementation • ICLR 2020 • Michael Tsang, Dehua Cheng, Hanpeng Liu, Xue Feng, Eric Zhou, Yan Liu
Recommendation is a prevalent application of machine learning that affects many users; therefore, it is important for recommender models to be accurate and interpretable.
no code implementations • NeurIPS 2020 • Michael Tsang, Sirisha Rambhatla, Yan Liu
Feature attribution is a way to analyze the impact of features on predictions.
no code implementations • 15 Jun 2020 • Sungyong Seo, Chuizheng Meng, Sirisha Rambhatla, Yan Liu
Although the knowledge of governing partial differential equations (PDE) of data can be helpful for the fast adaptation to few observations, it is mostly infeasible to exactly find the equation for observations in real-world physical systems.
no code implementations • 24 May 2020 • Zhensu Sun, Yan Liu, Ziming Cheng, Chen Yang, Pengyu Che
In this work, we would like to make recommendations based on requirement descriptions to avoid these problems.
no code implementations • 29 Apr 2020 • Bruce X. B. Yu, Yan Liu, Keith C. C. Chan
The data-driven approach that learns an optimal representation of vision features like skeleton frames or RGB videos is currently a dominant paradigm for activity recognition.
no code implementations • 29 Apr 2020 • Bruce X. B. Yu, Yan Liu, Keith C. C. Chan
To do so, we propose a HAR method that consists of three steps: (i) data transformation involving the generation of new features based on transforming of raw data, (ii) feature extraction involving the learning of a classifier based on the AdaBoost algorithm and the use of training data consisting of the transformed features, and (iii) parameter determination and pattern recognition involving the determination of parameters based on the features generated in (ii) and the use of the parameters as training data for deep learning algorithms to be used to recognize human activities.
no code implementations • 7 Apr 2020 • Xin Liu, Qingcai Chen, Yan Liu, Joanna Siebert, Baotian Hu, Xiang-Ping Wu, Buzhou Tang
We propose a Capsule network-based method to Decompose the unsupervised word Embedding of an ambiguous word into context specific Sense embedding, called CapsDecE2S.
1 code implementation • 2020 IEEE 36th International Conference on Data Engineering (ICDE) 2020 • Hongzhi Shi, Quanming Yao, Qi Guo, Yaguang Li, Lingyu Zhang, Jieping Ye, Yong Li, Yan Liu
Predicting Origin-Destination (OD) flow is a crucial problem for intelligent transportation.
3 code implementations • 26 Mar 2020 • Karishma Sharma, Sungyong Seo, Chuizheng Meng, Sirisha Rambhatla, Yan Liu
The analysis is presented and updated on a publically accessible dashboard (https://usc-melady. github. io/COVID-19-Tweet-Analysis) to track the nature of online discourse and misinformation about COVID-19 on Twitter from March 1 - June 5, 2020.
no code implementations • ECCV 2020 • Karishma Sharma, Pinar Donmez, Enming Luo, Yan Liu, I. Zeki Yalniz
Label noise is increasingly prevalent in datasets acquired from noisy channels.
Ranked #20 on Image Classification on Clothing1M (using extra training data)
no code implementations • 29 Feb 2020 • Yinjie Lei, Yan Liu, Pingping Zhang, Lingqiao Liu
Most existing crowd counting methods require object location-level annotation, i. e., placing a dot at the center of an object.
no code implementations • 18 Feb 2020 • Yan Liu, Yansha Deng, Maged Elkashlan, Arumugam Nallanathan, George K. Karagiannidis
Based on this framework, we define the latent access failure probability to characterize URLLC reliability and latency performances.
no code implementations • 13 Feb 2020 • Yan Liu, Zhiyuan Jiang, Shunqing Zhang, Shugong Xu
Ultra-Reliable and Low-Latency Communications (URLLC) services in vehicular networks on millimeter-wave bands present a significant challenge, considering the necessity of constantly adjusting the beam directions.
1 code implementation • ICLR 2020 • Sungyong Seo*, Chuizheng Meng*, Yan Liu
Sparsely available data points cause a numerical error on finite differences which hinder to modeling the dynamics of physical systems.
no code implementations • 7 Aug 2019 • Bin Guo, Huihui Chen, Yan Liu, Chao Chen, Qi Han, Zhiwen Yu
A generic model for CrowdMining is further proposed based on a set of existing studies.
no code implementations • 2 Aug 2019 • FangYuan Lei, Xun Liu, Qingyun Dai, Bingo Wing-Kuen Ling, Huimin Zhao, Yan Liu
With higher-order neighborhood information of graph network, the accuracy of graph representation learning classification can be significantly improved.
1 code implementation • AAAI 2019 • Xu Geng, Yaguang Li, Leye Wang, Lingyu Zhang, Qiang Yang, Jieping Ye, Yan Liu
This task is challenging due to the complicated spatiotemporal dependencies among regions.
no code implementations • 19 Jun 2019 • Yan Liu, Yun Li, Yunhao Yuan, Jipeng Qiang
Whether it is computer vision, natural language processing or speech recognition, the essence of these applications is to obtain powerful feature representations that make downstream applications completion more efficient.
no code implementations • 11 Jun 2019 • Conner Chyung, Michael Tsang, Yan Liu
In an attempt to gather a deeper understanding of how convolutional neural networks (CNNs) reason about human-understandable concepts, we present a method to infer labeled concept data from hidden layer activations and interpret the concepts through a shallow decision tree.
no code implementations • 27 May 2019 • Xu Geng, Xiyu Wu, Lingyu Zhang, Qiang Yang, Yan Liu, Jieping Ye
To incorporate multiple relationships into spatial feature extraction, we define the problem as a multi-modal machine learning problem on multi-graph convolution networks.
1 code implementation • WS 2019 • Yue Yu, YIlun Zhu, Yang Liu, Yan Liu, Siyao Peng, Mackenzie Gong, Amir Zeldes
In this paper we present GumDrop, Georgetown University's entry at the DISRPT 2019 Shared Task on automatic discourse unit segmentation and connective detection.
no code implementations • 3 Apr 2019 • Zhengping Che, Guangyu Li, Tracy Li, Bo Jiang, Xuefeng Shi, Xinsheng Zhang, Ying Lu, Guobin Wu, Yan Liu, Jieping Ye
Driving datasets accelerate the development of intelligent driving and related computer vision technologies, while substantial and detailed annotations serve as fuels and powers to boost the efficacy of such datasets to improve learning-based models.
5 code implementations • ICLR 2019 • Liangchen Luo, Yuanhao Xiong, Yan Liu, Xu sun
Recent work has put forward some algorithms such as AMSGrad to tackle this issue but they failed to achieve considerable improvement over existing methods.
1 code implementation • 8 Feb 2019 • Sungyong Seo, Yan Liu
While physics conveys knowledge of nature built from an interplay between observations and theory, it has been considered less importantly in deep neural networks.
no code implementations • 18 Jan 2019 • Karishma Sharma, Feng Qian, He Jiang, Natali Ruchansky, Ming Zhang, Yan Liu
The proliferation of fake news on social media has opened up new directions of research for timely identification and containment of fake news, and mitigation of its widespread impact on public opinion.
no code implementations • 3 Jan 2019 • Zengyou He, Chaohua Sheng, Yan Liu, Quan Zou
After these two steps, we have two p-values for each test instance and the test instance is assigned to the class associated with the smaller p-value.
no code implementations • ICLR 2019 • Michael Tsang, Youbang Sun, Dongxu Ren, Yan Liu
Interactions such as double negation in sentences and scene interactions in images are common forms of complex dependencies captured by state-of-the-art machine learning models.
no code implementations • NeurIPS 2018 • Michael Tsang, Hanpeng Liu, Sanjay Purushotham, Pavankumar Murali, Yan Liu
Neural networks are known to model statistical interactions, but they entangle the interactions at intermediate hidden layers for shared representation learning.
no code implementations • 1 Nov 2018 • Haojie Pan, Junpei Zhou, Zhou Zhao, Yan Liu, Deng Cai, Min Yang
We first propose a new task named Dialogue Description (Dial2Desc).
no code implementations • 1 Nov 2018 • Yaqiang Yao, Yan Liu, Huanhuan Chen
In this paper, we first design an efficient division method to decompose a manifold into ordered continuous maximal linear patches (CMLPs) that denote meaningful action snippets of the action sequence.
no code implementations • ICML 2018 • Zhengping Che, Sanjay Purushotham, Guangyu Li, Bo Jiang, Yan Liu
Multi-Rate Multivariate Time Series (MR-MTS) are the multivariate time series observations which come with various sampling rates and encode multiple temporal dependencies.
1 code implementation • 29 May 2018 • Palash Goyal, Nitin Kamra, Xinran He, Yan Liu
The major advantages of DynGEM include: (1) the embedding is stable over time, (2) it can handle growing dynamic graphs, and (3) it has better running time than using static embedding methods on each snapshot of a dynamic graph.
Social and Information Networks
no code implementations • 1 Feb 2018 • Feng Li, Yan Liu, Khidir Shaib Mohamed, Wei Wu
We propose in this paper a modified Sigma-Pi-Sigma neural network (MSPSNN) with an adaptive approach to find a better multinomial for a given problem.
no code implementations • 30 Jan 2018 • Jie Yang, Pingping Zhang, Yan Liu
The numerical results show that there is not significant reduction in the classification ability of the network if the input signals are subject to sinusoidal and Gaussian perturbations.
no code implementations • ICLR 2018 • Sungyong Seo, Arash Mohegh, George Ban-Weiss, Yan Liu
Spatiotemporal forecasting has become an increasingly important prediction task in machine learning and statistics due to its vast applications, such as climate modeling, traffic prediction, video caching predictions, and so on.
no code implementations • ICLR 2018 • Sanjay Purushotham, Zhengping Che, Bo Jiang, Tanachat Nilanon, Yan Liu
Recent advances in computing technology and sensor design have made it easier to collect longitudinal or time series data from patients, resulting in a gigantic amount of available medical data.
no code implementations • 31 Oct 2017 • Rose Yu, Guangyu Li, Yan Liu
Low-rank tensor regression, a new model class that learns high-order correlation from data, has recently received considerable attention.
no code implementations • ICLR 2018 • Nitin Kamra, Umang Gupta, Yan Liu
This phenomenon called catastrophic forgetting is a fundamental challenge to overcome before neural networks can learn continually from incoming data.
1 code implementation • 23 Oct 2017 • Sanjay Purushotham, Chuizheng Meng, Zhengping Che, Yan Liu
Deep learning models (aka Deep Neural Networks) have revolutionized many fields including computer vision, natural language processing, speech recognition, and is being increasingly used in clinical healthcare applications.
no code implementations • 6 Sep 2017 • Zhengping Che, Yu Cheng, Shuangfei Zhai, Zhaonan Sun, Yan Liu
We use this generative model together with a convolutional neural network (CNN) based prediction model to improve the onset prediction performance.
14 code implementations • ICLR 2018 • Yaguang Li, Rose Yu, Cyrus Shahabi, Yan Liu
Spatiotemporal forecasting has various applications in neuroscience, climate and transportation domain.
Ranked #3 on Traffic Prediction on PeMS-M
Multivariate Time Series Forecasting Spatio-Temporal Forecasting +2
no code implementations • ICLR 2018 • Michael Tsang, Dehua Cheng, Yan Liu
Interpreting neural networks is a crucial and challenging task in machine learning.
no code implementations • 19 Apr 2017 • Xin Liu, Qingcai Chen, Xiang-Ping Wu, Yan Liu, Yang Liu
Music emotion recognition (MER) is usually regarded as a multi-label tagging task, and each segment of music can inspire specific emotion tags.
2 code implementations • 20 Mar 2017 • Natali Ruchansky, Sungyong Seo, Yan Liu
Specifically, we incorporate the behavior of both parties, users and articles, and the group behavior of users who propagate fake news.
no code implementations • 25 Jan 2017 • Zhengping Che, Yu Cheng, Zhaonan Sun, Yan Liu
To account for high dimensionality, we use the embedding medical features in the CNN model which hold the natural medical concepts.
no code implementations • NeurIPS 2016 • Dehua Cheng, Richard Peng, Yan Liu, Ioakeim Perros
In this paper, we show ways of sampling intermediate steps of alternating minimization algorithms for computing low rank tensor CP decompositions, leading to the sparse alternating least squares (SPALS) method.
no code implementations • WS 2016 • Marhaba Eli, Weinila Mushajiang, Tuergen Yibulayin, Kahaerjiang Abiderexiti, Yan Liu
The Universal Dependencies (UD) Project seeks to build a cross-lingual studies of treebanks, linguistic structures and parsing.
no code implementations • NeurIPS 2016 • Xinran He, Ke Xu, David Kempe, Yan Liu
We establish both proper and improper PAC learnability of influence functions under randomly missing observations.
no code implementations • 27 Oct 2016 • Jie Chen, Dehua Cheng, Yan Liu
A well-known construction of such functions comes from Bochner's characterization, which connects a positive-definite function with a probability distribution.
no code implementations • 23 Oct 2016 • Yuan Xie, DaCheng Tao, Wensheng Zhang, Lei Zhang, Yan Liu, Yanyun Qu
Different from traditional unfolding based tensor norm, this low-rank tensor constraint has optimality properties similar to that of matrix rank derived from SVD, so the complementary information among views can be explored more efficiently and thoroughly.
no code implementations • 8 Jul 2016 • Rose Yu, Yan Liu
In this paper, we introduce subsampled tensor projected gradient to solve the problem.
6 code implementations • 6 Jun 2016 • Zhengping Che, Sanjay Purushotham, Kyunghyun Cho, David Sontag, Yan Liu
Multivariate time series data in practical applications, such as health care, geoscience, and biology, are characterized by a variety of missing values.
Ranked #4 on Multivariate Time Series Forecasting on MuJoCo
Multivariate Time Series Forecasting Multivariate Time Series Imputation +2
no code implementations • 20 Jan 2016 • V. S. Subrahmanian, Amos Azaria, Skylar Durst, Vadim Kagan, Aram Galstyan, Kristina Lerman, Linhong Zhu, Emilio Ferrara, Alessandro Flammini, Filippo Menczer, Andrew Stevens, Alexander Dekhtyar, Shuyang Gao, Tad Hogg, Farshad Kooti, Yan Liu, Onur Varol, Prashant Shiralkar, Vinod Vydiswaran, Qiaozhu Mei, Tim Hwang
A number of organizations ranging from terrorist groups such as ISIS to politicians and nation states reportedly conduct explicit campaigns to influence opinion on social media, posing a risk to democratic processes.
no code implementations • 6 Jan 2016 • Rose Yu, Huida Qiu, Zhen Wen, Ching-Yung Lin, Yan Liu
In this paper, we present a survey on existing approaches to address this problem.
no code implementations • 11 Dec 2015 • Zhengping Che, Sanjay Purushotham, Robinder Khemani, Yan Liu
Exponential growth in Electronic Healthcare Records (EHR) has resulted in new opportunities and urgent needs for discovery of meaningful data-driven representations and patterns of diseases in Computational Phenotyping research.
no code implementations • 3 Dec 2015 • Yuan Xie, Shuhang Gu, Yan Liu, WangMeng Zuo, Wensheng Zhang, Lei Zhang
However, NNM tends to over-shrink the rank components and treats the different rank components equally, limiting its flexibility in practical applications.
no code implementations • 12 Feb 2015 • Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng
Our work is particularly motivated by the algorithmic problems for speeding up the classic Newton's method in applications such as computing the inverse square-root of the precision matrix of a Gaussian random field, as well as computing the $q$th-root transition (for $q\geq1$) in a time-reversible Markov model.
no code implementations • NeurIPS 2014 • Mohammad Taha Bahadori, Qi (Rose) Yu, Yan Liu
Accurate and efficient analysis of multivariate spatio-temporal data is critical in climatology, geology, and sociology applications.
no code implementations • 23 Oct 2014 • Dehua Cheng, Xinran He, Yan Liu
Topic models have achieved significant successes in analyzing large-scale text corpus.
no code implementations • 20 Oct 2014 • Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng
random samples for $n$-dimensional Gaussian random fields with SDDM precision matrices.
no code implementations • 7 Oct 2014 • QI, Yu, Xinran He, Yan Liu
Existing group anomaly detection approaches rely on the assumption that the groups are known, which can hardly be true in real world social media applications.
no code implementations • NeurIPS 2011 • Dan Zhang, Yan Liu, Luo Si, Jian Zhang, Richard D. Lawrence
Ignoring this structure information limits the performance of existing MIL algorithms.