AAAI 2021

1,961 papers

MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements

Yang Li, Yu Shen, Jiawei Jiang, Jinyang Gao, Ce Zhang

Improving Adversarial Robustness via Probabilistically Compact Loss with Logit Constraints

Xin Li, Xiangrui Li, Deng Pan, Dongxiao Zhu

A Free Lunch for Unsupervised Domain Adaptive Object Detection without Source Data

Xianfeng Li, Weijie Chen, Di Xie, Shicai Yang, Peng Yuan

Sublinear Classical and Quantum Algorithms for General Matrix Games

Tongyang Li, Chunhao Wang, Shouvanik Chakrabarti, Xiaodi Wu

Bi-Classifier Determinacy Maximization for Unsupervised Domain Adaptation

Shuang Li, fangrui lv, Binhui Xie, Chi Harold Liu, Jian Liang

Multi-View Representation Learning with Manifold Smoothness

Shu Li, Wei Wang, Wen-Tao Li, Pan Chen

Learning Graph Neural Networks with Approximate Gradient Descent

Qunwei Li, Shaofeng Zou, Wenliang Zhong

Bayesian Distributional Policy Gradients

Luchen Li, A. Aldo Faisal

Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting

Longyuan Li, Jihai Zhang, Junchi Yan, Yaohui Jin, Yunhao Zhang

Token-Aware Virtual Adversarial Training in Natural Language Understanding

Linyang Li, Xipeng Qiu

Learning Intact Features by Erasing-Inpainting for Few-shot Classification

Junjie Li, Zilei Wang, Xiaoming Hu

Self-Paced Two-dimensional PCA

Jiangxin Li, Zhao Kang, Chong Peng, Wenyu Chen

A Bayesian Approach for Subset Selection in Contextual Bandits

Jialian Li, Chao Du, Jun Zhu

ShapeNet: A Shapelet-Neural Network Approach for Multivariate Time Series Classification

Guozhong Li, Byron Choi, Jianliang Xu, Sourav S Bhowmick, Kwok-Pan Chun

High Fidelity GAN Inversion via Prior Multi-Subspace Feature Composition

Guanyue Li, Qianfen Jiao, Sheng Qian, Si Wu, Hau-San Wong

VSQL: Variational Shadow Quantum Learning for Classification

Guangxi Li, Zhixin Song, Xin Wang

GoT: a Growing Tree Model for Clustering Ensemble

Feijiang Li, Yuhua Qian, Jieting Wang

LRSC: Learning Representations for Subspace Clustering

Changsheng Li, chen yang, Bo Liu, Ye Yuan, Guoren Wang

Unsupervised Active Learning via Subspace Learning

Changsheng Li, Kaihang Mao, Lingyan Liang, Dongchun Ren, Wei Zhang

Enhancing Parameter-Free Frank Wolfe with an Extra Subproblem

Bingcong Li, Lingda Wang, Georgios B. Giannakis, Zhizhen Zhao

Memory and Computation-Efficient Kernel SVM via Binary Embedding and Ternary Model Coefficients

Zijian Lei, Liang Lan

Unsupervised Domain Adaptation for Semantic Segmentation by Content Transfer

Suhyeon Lee, Junhyuk Hyun, Hongje Seong, Euntai Kim

Interpretable Embedding Procedure Knowledge Transfer via Stacked Principal Component Analysis and Graph Neural Network

Seunghyun Lee, Byung Cheol Song

Learnable Dynamic Temporal Pooling for Time Series Classification

Dongha Lee, Seonghyeon Lee, Hwanjo Yu

Norm-Based Generalisation Bounds for Deep Multi-Class Convolutional Neural Networks

Antoine Ledent, Waleed Mustafa, Yunwen Lei, Marius Kloft

Lipschitz Lifelong Reinforcement Learning

Erwan Lecarpentier, David Abel, Kavosh Asadi, Yuu Jinnai, Emmanuel Rachelson

Metrics and Continuity in Reinforcement Learning

Charline Le Lan, Marc G. Bellemare, Pablo Samuel Castro

Query Training: Learning a Worse Model to Infer Better Marginals in Undirected Graphical Models with Hidden Variables

Miguel Lázaro-Gredilla, Wolfgang Lehrach, Nishad Gothoskar, Guangyao Zhou, Antoine Dedieu

Hypothesis Disparity Regularized Mutual Information Maximization

Qicheng Lao, Xiang Jiang, Mohammad Havaei

Compressing Deep Convolutional Neural Networks by Stacking Low-dimensional Binary Convolution Filters

Weichao Lan, Liang Lan

MolGrow: A Graph Normalizing Flow for Hierarchical Molecular Generation

Maksim Kuznetsov, Daniil Polykovskiy

Positions, Channels, and Layers: Fully Generalized Non-Local Network for Singer Identification

I-Yuan Kuo, Wen-Li Wei, Jen-Chun Lin

Asynchronous Optimization Methods for Efficient Training of Deep Neural Networks with Guarantees

Vyacheslav Kungurtsev, Malcolm Egan, Bapi Chatterjee, Dan Alistarh

Nearly Linear-Time, Parallelizable Algorithms for Non-Monotone Submodular Maximization

Alan Kuhnle

HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference

Jakob Kruse, Gianluca Detommaso, Ullrich Köthe, Robert Scheichl

Sparsity Aware Normalization for GANs

Idan Kligvasser, Tomer Michaeli

Visual Concept Reasoning Networks

Taesup Kim, Sungwoong Kim, Yoshua Bengio

Neural Sequence-to-grid Module for Learning Symbolic Rules

Segwang Kim, Hyoungwook Nam, Joonyoung Kim, Kyomin Jung

Kernel-convoluted Deep Neural Networks with Data Augmentation

Minjin Kim, Young-geun Kim, Dongha Kim, Yongdai Kim, Myunghee Cho Paik

DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation

Jungeun Kim, Kookjin Lee, Dongeun Lee, Sheo Yon Jhin, Noseong Park

Split-and-Bridge: Adaptable Class Incremental Learning within a Single Neural Network

Jong-Yeong Kim, Dong-Wan Choi

Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder

Hyemi Kim, Seungjae Shin, JoonHo Jang, Kyungwoo Song, Weonyoung Joo

Understanding Catastrophic Overfitting in Single-step Adversarial Training

Hoki Kim, Woojin Lee, Jaewook Lee

GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning

Krishnateja Killamsetty, Durga Sivasubramanian, Ganesh Ramakrishnan, Rishabh Iyer

A Flexible Framework for Communication-Efficient Machine Learning

Sarit Khirirat, Sindri Magnússon, Arda Aytekin, Mikael Johansson

Improving Fairness and Privacy in Selection Problems

Mohammad Mahdi Khalili, Xueru Zhang, Mahed Abroshan, Somayeh Sojoudi

Bayesian Dynamic Mode Decomposition with Variational Matrix Factorization

Takahiro Kawashima, Hayaru Shouno, Hideitsu Hino

A Recipe for Global Convergence Guarantee in Deep Neural Networks

Kenji Kawaguchi, Qingyun Sun

Learning Generalized Relational Heuristic Networks for Model-Agnostic Planning

Rushang Karia, Siddharth Srivastava

Deep Probabilistic Canonical Correlation Analysis

Mahdi Karami, Dale Schuurmans

Exploration via State influence Modeling

Yongxin Kang, Enmin Zhao, Kai Li, Junliang Xing

Winning Lottery Tickets in Deep Generative Models

Neha Mukund Kalibhat, Yogesh Balaji, Soheil Feizi

A Sample-Efficient Algorithm for Episodic Finite-Horizon MDP with Constraints

Krishna C. Kalagarla, Rahul Jain, Pierluigi Nuzzo

Linearly Replaceable Filters for Deep Network Channel Pruning

Donggyu Joo, Eojindl Yi, Sunghyun Baek, Junmo Kim

Balanced Open Set Domain Adaptation via Centroid Alignment

Mengmeng Jing, Jingjing Li, LEI ZHU, Zhengming Ding, Ke Lu

Power up! Robust Graph Convolutional Network via Graph Powering

Ming Jin, Heng Chang, Wenwu Zhu, Somayeh Sojoudi

Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks

Yuqian Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu

LightXML: Transformer with Dynamic Negative Sampling for High-Performance Extreme Multi-label Text Classification

Ting Jiang, Deqing Wang, Leilei Sun, Huayi Yang, Zhengyang Zhao

Action Candidate Based Clipped Double Q-learning for Discrete and Continuous Action Tasks

Haobo Jiang, Jin Xie, Jian Yang

Clustering Ensemble Meets Low-rank Tensor Approximation

Yuheng Jia, Hui LIU, Junhui Hou, Qingfu Zhang

Intrinsic Certified Robustness of Bagging against Data Poisoning Attacks

Jinyuan Jia, Xiaoyu Cao, Neil Zhenqiang Gong

Dynamic Multi-Context Attention Networks for Citation Forecasting of Scientific Publications

Taoran Ji, Nathan Self, Kaiqun Fu, Zhiqian Chen, Naren Ramakrishnan

Show, Attend and Distill: Knowledge Distillation via Attention-based Feature Matching

Mingi Ji, Byeongho Heo, Sungrae Park

Active Bayesian Assessment of Black-Box Classifiers

Disi Ji, Robert L. Logan, Padhraic Smyth, Mark Steyvers

IB-GAN: Disentangled Representation Learning with Information Bottleneck Generative Adversarial Networks

Insu Jeon, Wonkwang Lee, Myeongjang Pyeon, Gunhee Kim

Neural Utility Functions

Porter Jenkins, Ahmad Farag, J. Stockton Jenkins, Huaxiu Yao, Suhang Wang

Constructing a Fair Classifier with Generated Fair Data

Taeuk Jang, Feng Zheng, Xiaoqian Wang

Variance Penalized On-Policy and Off-Policy Actor-Critic

Arushi Jain, Gandharv Patil, Ayush Jain, Khimya Khetarpal, Doina Precup

Accurate and Robust Feature Importance Estimation under Distribution Shifts

Jayaraman J. Thiagarajan, Vivek Narayanaswamy, Rushil Anirudh, Peer-Timo Bremer, Andreas Spanias

Large Batch Optimization for Deep Learning Using New Complete Layer-Wise Adaptive Rate Scaling

Zhouyuan Huo, Bin Gu, Heng Huang

Reward-Biased Maximum Likelihood Estimation for Linear Stochastic Bandits

Yu-Heng Hung, Ping-Chun Hsieh, Xi Liu, P. R. Kumar

Personalized Cross-Silo Federated Learning on Non-IID Data

Yutao Huang, Lingyang Chu, Zirui Zhou, Lanjun Wang, Jiangchuan Liu

ACMo: Angle-Calibrated Moment Methods for Stochastic Optimization

Xunpeng Huang, Runxin Xu, Hao Zhou, Zhe Wang, Zhengyang Liu

Learning to Reweight Imaginary Transitions for Model-Based Reinforcement Learning

Wenzhen Huang, Qiyue Yin, Junge Zhang, Kaiqi Huang

Attributes-Guided and Pure-Visual Attention Alignment for Few-Shot Recognition

Siteng Huang, Min Zhang, Yachen Kang, Donglin Wang

Accelerating Continuous Normalizing Flow with Trajectory Polynomial Regularization

Han-Hsien Huang, Mi-Yen Yeh

Adversarial Defence by Diversified Simultaneous Training of Deep Ensembles

Bo Huang, Zhiwei Ke, Yi Wang, Wei Wang, Linlin Shen

Multidimensional Uncertainty-Aware Evidential Neural Networks

Yibo Hu, Yuzhe Ou, Xujiang Zhao, Jin-Hee Cho, Feng Chen

Predictive Adversarial Learning from Positive and Unlabeled Data

Wenpeng Hu, Ran Le, Bing Liu, Feng Ji, Jinwen Ma

Continual Learning by Using Information of Each Class Holistically

Wenpeng Hu, Qi Qin, Mengyu Wang, Jinwen Ma, Bing Liu

Multi-scale Graph Fusion for Co-saliency Detection

Rongyao Hu, Zhenyun Deng, Xiaofeng Zhu

OPQ: Compressing Deep Neural Networks with One-shot Pruning-Quantization

Peng Hu, Xi Peng, Hongyuan Zhu, Mohamed M. Sabry Aly, Jie Lin

Boosting Multi-task Learning Through Combination of Task Labels - with Applications in ECG Phenotyping

Ming-En Hsieh, Vincent Tseng

Gaussian Process Priors for View-Aware Inference

Yuxin Hou, Ari Heljakka, Arno Solin

Disentangled Representation Learning in Heterogeneous Information Network for Large-scale Android Malware Detection in the COVID-19 Era and Beyond

Shifu Hou, Yujie Fan, Mingxuan Ju, Yanfang Ye, Wenqiang Wan

Slimmable Generative Adversarial Networks

Liang Hou, Zehuan Yuan, Lei Huang, Huawei Shen, Xueqi Cheng

Reinforcement Learning Based Multi-Agent Resilient Control: From Deep Neural Networks to an Adaptive Law

Jian Hou, Fangyuan Wang, Lili Wang, Zhiyong Chen

Storage Fit Learning with Feature Evolvable Streams

Bo-Jian Hou, Yu-Hu Yan, Peng Zhao, Zhi-Hua Zhou

Topology Distance: A Topology-Based Approach for Evaluating Generative Adversarial Networks

Danijela Horak, Simiao Yu, Gholamreza Salimi-Khorshidi

Graph Game Embedding

Xiaobin Hong, Tong Zhang, Zhen Cui, Yuge Huang, Pengcheng Shen

Learning Model-Based Privacy Protection under Budget Constraints

Junyuan Hong, Haotao Wang, Zhangyang Wang, Jiayu Zhou

Scaling-Up Robust Gradient Descent Techniques

Matthew J. Holland

Provably Good Solutions to the Knapsack Problem via Neural Networks of Bounded Size

Christoph Hertrich, Martin Skutella

Analysing the Noise Model Error for Realistic Noisy Label Data

Michael A. Hedderich, Dawei Zhu, Dietrich Klakow

Learning with Safety Constraints: Sample Complexity of Reinforcement Learning for Constrained MDPs

Aria HasanzadeZonuzy, Archana Bura, Dileep Kalathil, Srinivas Shakkottai

Liquid Time-constant Networks

Ramin Hasani, Mathias Lechner, Alexander Amini, Daniela Rus, Radu Grosu

DeepSynth: Automata Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning

Mohammadhosein Hasanbeig, Natasha Yogananda Jeppu, Alessandro Abate, Tom Melham, Daniel Kroening

Explanation Consistency Training: Facilitating Consistency-Based Semi-Supervised Learning with Interpretability

Tao Han, Wei-Wei Tu, Yu-feng Li

High-Dimensional Bayesian Optimization via Tree-Structured Additive Models

Eric Han, Ishank Arora, Jonathan Scarlett

Towards Reusable Network Components by Learning Compatible Representations

Michael Gygli, Jasper Uijlings, Vittorio Ferrari