AAAI 2021

1,961 papers

A Primal-Dual Online Algorithm for Online Matching Problem in Dynamic Environments

Yu-Hang Zhou, Peng Hu, Chen Liang, Huan Xu, Guangda Huzhang

Local Differential Privacy for Bayesian Optimization

Xingyu Zhou, Jian Tan

Temporal-Coded Deep Spiking Neural Network with Easy Training and Robust Performance

Shibo Zhou, Xiaohua Li, Ying Chen, Sanjeev T. Chandrasekaran, Arindam Sanyal

Fairness in Forecasting and Learning Linear Dynamical Systems

Quan Zhou, Jakub Marecek, Robert N. Shorten

Tri-level Robust Clustering Ensemble with Multiple Graph Learning

Peng Zhou, Liang Du, Yi-Dong Shen, Xuejun Li

Inverse Reinforcement Learning with Natural Language Goals

Li Zhou, Kevin Small

Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting

Haoyi Zhou, Shanghang Zhang, Jieqi Peng, SHUAI ZHANG, Jianxin Li

MetaAugment: Sample-Aware Data Augmentation Policy Learning

Fengwei Zhou, Jiawei Li, Chuanlong Xie, Fei Chen, Lanqing Hong

Multi-task Learning by Leveraging the Semantic Information

Fan Zhou, Brahim Chaib-draa, Boyu Wang

How Does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches?

Li Zhong, Zhen Fang, Feng Liu, Jie Lu, Bo Yuan

Fully-Connected Tensor Network Decomposition and Its Application to Higher-Order Tensor Completion

Yu-Bang Zheng, Ting-Zhu Huang, Xi-Le Zhao, Qibin Zhao, Tai-Xiang Jiang

Going Deeper With Directly-Trained Larger Spiking Neural Networks

Hanle Zheng, YuJie Wu, Lei Deng, Yifan Hu, Guoqi Li

Meta Label Correction for Noisy Label Learning

Guoqing Zheng, Ahmed Hassan Awadallah, Susan Dumais

Flow-based Generative Models for Learning Manifold to Manifold Mappings

Xingjian Zhen, Rudrasis Chakraborty, Liu Yang, Vikas Singh

Improved Consistency Regularization for GANs

Zhengli Zhao, Sameer Singh, Honglak Lee, Zizhao Zhang, Augustus Odena

Augmenting Policy Learning with Routines Discovered from a Single Demonstration

Zelin Zhao, Chuang Gan, Jiajun Wu, Xiaoxiao Guo, Joshua B. Tenenbaum

Data Augmentation for Graph Neural Networks

Tong Zhao, Yozen Liu, Leonardo Neves, Oliver Woodford, Meng Jiang

Efficient Classification with Adaptive KNN

Puning Zhao, Lifeng LAI

Exploratory Machine Learning with Unknown Unknowns

Peng Zhao, Yu-Jie Zhang, Zhi-Hua Zhou

Distilling Localization for Self-Supervised Representation Learning

Nanxuan Zhao, Zhirong Wu, Rynson W.H. Lau, Stephen Lin

Looking Wider for Better Adaptive Representation in Few-Shot Learning

Jiabao Zhao, Yifan Yang, Xin lin, Jing Yang, Liang He

Exploiting Unlabeled Data via Partial Label Assignment for Multi-Class Semi-Supervised Learning

Zhen-Ru Zhang, Qian-Wen Zhang, Yunbo Cao, Min-ling Zhang

Towards Enabling Learnware to Handle Unseen Jobs

Yu-Jie Zhang, Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou

Memory-Gated Recurrent Networks

Yaquan Zhang, Qi Wu, Nanbo Peng, Min Dai, Jing Zhang

Partial-Label and Structure-constrained Deep Coupled Factorization Network

Yan Zhang, Zhao Zhang, Yang Wang, Zheng Zhang, Li Zhang

The Sample Complexity of Teaching by Reinforcement on Q-Learning

Xuezhou Zhang, Shubham Bharti, Yuzhe Ma, Adish Singla, Xiaojin Zhu

Regret Bounds for Online Kernel Selection in Continuous Kernel Space

Xiao Zhang, Shizhong Liao, Jun Xu, Ji-Rong Wen

Treatment Effect Estimation with Disentangled Latent Factors

Weijia Zhang, Lin Liu, Jiuyong Li

Deep Wasserstein Graph Discriminant Learning for Graph Classification

Tong Zhang, Yun Wang, Zhen Cui, Chuanwei Zhou, Baoliang Cui

Mean-Variance Policy Iteration for Risk-Averse Reinforcement Learning

Shangtong Zhang, Bo Liu, Shimon Whiteson

Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating

Qingsong Zhang, Bin Gu, Cheng Deng, Heng Huang

Sample Efficient Reinforcement Learning with REINFORCE

Junzi Zhang, Jongho Kim, Brendan O'Donoghue, Stephen Boyd

Interpreting Multivariate Shapley Interactions in DNNs

Hao Zhang, Yichen Xie, Longjie Zheng, Die Zhang, Quanshi Zhang

Efficient Folded Attention for Medical Image Reconstruction and Segmentation

Hang Zhang, Jinwei Zhang, Rongguang Wang, Qihao Zhang, Pascal Spincemaille

Exploration by Maximizing Renyi Entropy for Reward-Free RL Framework

Chuheng Zhang, Yuanying Cai, Longbo Huang, Jian Li

CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting

Chaoyun Zhang, Marco Fiore, Iain Murray, Paul Patras

A Hybrid Stochastic Gradient Hamiltonian Monte Carlo Method

Chao Zhang, Zhijian Li, Zebang Shen, Jiahao Xie, Hui Qian

Data-driven Competitive Algorithms for Online Knapsack and Set Cover

Ali Zeynali, Bo Sun, Mohammad Hajiesmaili, Adam Wierman

Contrastive Self-supervised Learning for Graph Classification

Jiaqi Zeng, Pengtao Xie

Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks

Huimin Zeng, Chen Zhu, Tom Goldstein, Furong Huang

Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning

Syed Zawad, Ahsan Ali, Pin-Yu Chen, Ali Anwar, Yi Zhou

Knowledge-Guided Object Discovery with Acquired Deep Impressions

Jinyang Yuan, Bin Li, Xiangyang Xue

Learning Modality-Specific Representations with Self-Supervised Multi-Task Learning for Multimodal Sentiment Analysis

Wenmeng Yu, Hua Xu, Ziqi Yuan, Jiele Wu

Measuring Dependence with Matrix-based Entropy Functional

Shujian Yu, Francesco Alesiani, Xi Yu, Robert Jenssen, Jose Principe

Personalized Adaptive Meta Learning for Cold-start User Preference Prediction

Runsheng Yu, Yu Gong, Xu He, Yu Zhu, Qingwen Liu

Any-Precision Deep Neural Networks

Haichao Yu, Haoxiang Li, Humphrey Shi, Thomas S. Huang, Gang Hua

DAST: Unsupervised Domain Adaptation in Semantic Segmentation Based on Discriminator Attention and Self-Training

Fei Yu, Mo Zhang, Hexin Dong, Sheng Hu, Bin Dong

How Does Data Augmentation Affect Privacy in Machine Learning?

Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-yan Liu

Identity-aware Graph Neural Networks

Jiaxuan You, Jonathan M Gomes-Selman, Rex Ying, Jure Leskovec

Learning Interpretable Models for Coupled Networks Under Domain Constraints

Hongyuan You, Sikun Lin, Ambuj Singh

Image-to-Image Retrieval by Learning Similarity between Scene Graphs

Sangwoong Yoon, Woo Young Kang, Sungwook Jeon, SeongEun Lee, Changjin Han

Enhanced Audio Tagging via Multi- to Single-Modal Teacher-Student Mutual Learning

Yifang Yin, Harsh Shrivastava, Ying Zhang, Zhenguang Liu, Rajiv Ratn Shah

Sequential Generative Exploration Model for Partially Observable Reinforcement Learning

Haiyan Yin, Jianda Chen, Sinno Jialin Pan, Sebastian Tschiatschek

Amata: An Annealing Mechanism for Adversarial Training Acceleration

Nanyang Ye, Qianxiao Li, Xiao-Yun Zhou, Zhanxing Zhu

Task Cooperation for Semi-Supervised Few-Shot Learning

Han-Jia Ye, Xin-Chun Li, De-Chuan Zhan

Improving Sample Efficiency in Model-Free Reinforcement Learning from Images

Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning

Zhewei Yao, Amir Gholami, Sheng Shen, Mustafa Mustafa, Kurt Keutzer

SeCo: Exploring Sequence Supervision for Unsupervised Representation Learning

Ting Yao, Yiheng Zhang, Zhaofan Qiu, Yingwei Pan, Tao Mei

Characterizing the Evasion Attackability of Multi-label Classifiers

Zhuo Yang, Yufei Han, Xiangliang Zhang

WCSAC: Worst-Case Soft Actor Critic for Safety-Constrained Reinforcement Learning

Qisong Yang, Thiago D. Simão, Simon H Tindemans, Matthijs T. J. Spaan

Sample Complexity of Policy Gradient Finding Second-Order Stationary Points

Long Yang, Qian Zheng, Gang Pan

On Convergence of Gradient Expected Sarsa(λ)

Long Yang, Gang Zheng, Yu Zhang, Qian Zheng, Pengfei Li

FracBits: Mixed Precision Quantization via Fractional Bit-Widths

Linjie Yang, Qing Jin

Hierarchical Graph Capsule Network

JINYU YANG, Peilin Zhao, Yu Rong, Chaochao Yan, Chunyuan Li

Robust Bandit Learning with Imperfect Context

Jianyi Yang, Shaolei Ren

DeHiB: Deep Hidden Backdoor Attack on Semi-supervised Learning via Adversarial Perturbation

Zhicong Yan, Gaolei Li, Yuan Tian, Jun Wu, Shenghong Li

Near Lossless Transfer Learning for Spiking Neural Networks

Zhanglu Yan, Jun Zhou, Weng-Fai Wong

Adversarial Partial Multi-Label Learning with Label Disambiguation

Yan Yan, Yuhong Guo

Toward Understanding the Influence of Individual Clients in Federated Learning

Yihao Xue, Chaoyue Niu, Zhenzhe Zheng, Shaojie Tang, Chengfei Lyu

Rethinking Bi-Level Optimization in Neural Architecture Search: A Gibbs Sampling Perspective

Chao Xue, Xiaoxing Wang, Junchi Yan, Yonggang Hu, Xiaokang Yang

Deep Frequency Principle Towards Understanding Why Deeper Learning Is Faster

Zhiqin John Xu, Hanxu Zhou

MUFASA: Multimodal Fusion Architecture Search for Electronic Health Records

Zhen Xu, David R. So, Andrew M. Dai

Towards Feature Space Adversarial Attack by Style Perturbation

Qiuling Xu, Guanhong Tao, Siyuan Cheng, Xiangyu Zhang

Towards Generalized Implementation of Wasserstein Distance in GANs

Minkai Xu

Learning Graphons via Structured Gromov-Wasserstein Barycenters

Hongteng Xu, Dixin Luo, Lawrence Carin, Hongyuan Zha

Multi-Task Recurrent Modular Networks

Dongkuan Xu, Wei Cheng, Xin Dong, Bo Zong, Wenchao Yu

Isolation Graph Kernel

Bi-Cun Xu, Kai Ming Ting, Yuan Jiang

Step-Ahead Error Feedback for Distributed Training with Compressed Gradient

An Xu, Zhouyuan Huo, Heng Huang

Variational Disentanglement for Rare Event Modeling

Zidi Xiu, Chenyang Tao, Michael Gao, Connor Davis, Benjamin A. Goldstein

Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling

Huaqing Xiong, Tengyu Xu, Yingbin Liang, Wei Zhang

Domain Adaptation In Reinforcement Learning Via Latent Unified State Representation

Jinwei Xing, Takashi Nagata, Kexin Chen, Xinyun Zou, Emre Neftci

Learning Energy-Based Model with Variational Auto-Encoder as Amortized Sampler

Jianwen Xie, Zilong Zheng, Ping Li

Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation

Jianwen Xie, Zilong Zheng, Xiaolin Fang, Song-chun Zhu, Ying Nian Wu

Distant Transfer Learning via Deep Random Walk

Qiao Xiao, Yu Zhang

Physics-constrained Automatic Feature Engineering for Predictive Modeling in Materials Science

Ziyu Xiang, Mingzhou Fan, Guillermo Vázquez Tovar, William Trehern, Byung-Jun Yoon

Communication-Efficient Frank-Wolfe Algorithm for Nonconvex Decentralized Distributed Learning

Wenhan Xian, Feihu Huang, Heng Huang

Near-Optimal MNL Bandits Under Risk Criteria

Guangyu Xi, Chao Tao, Yuan Zhou

Learning to Purify Noisy Labels via Meta Soft Label Corrector

Yichen WU, Jun Shu, Qi Xie, Qian Zhao, Deyu Meng

Neural Architecture Search as Sparse Supernet

Yan Wu, Aoming Liu, Zhiwu Huang, Siwei Zhang, Luc Van Gool

Fractal Autoencoders for Feature Selection

xinxing wu, Qiang Cheng

Curriculum-Meta Learning for Order-Robust Continual Relation Extraction

Tongtong Wu, Xuekai Li, Yuan-Fang Li, Gholamreza Haffari, Guilin Qi

Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models

Ruiyuan Wu, Anna Scaglione, Hoi-To Wai, Nurullah Karakoc, Kari Hreinsson

Frugal Optimization for Cost-related Hyperparameters

Qingyun Wu, Chi Wang, Silu Huang

Fine-grained Generalization Analysis of Vector-Valued Learning

Liang Wu, Antoine Ledent, Yunwen Lei, Marius Kloft

Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients

Huimin Wu, Zhengmian Hu, Bin Gu

Training Spiking Neural Networks with Accumulated Spiking Flow

Hao Wu, Yueyi Zhang, Wenming Weng, Yongting Zhang, Zhiwei Xiong

Self-Supervised Attention-Aware Reinforcement Learning

Haiping Wu, Khimya Khetarpal, Doina Precup

Peer Collaborative Learning for Online Knowledge Distillation

Guile Wu, Shaogang Gong

BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search

Colin White, Willie Neiswanger, Yash Savani

Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases

Chris Wendler, Andisheh Amrollahi, Bastian Seifert, Andreas Krause, Markus Püschel