AAAI 2021

1,961 papers

Unified Tensor Framework for Incomplete Multi-view Clustering and Missing-view Inferring

Jie Wen, Zheng Zhang, Zhao Zhang, LEI ZHU, Lunke Fei

Gene Regulatory Network Inference as Relaxed Graph Matching

Deborah Weighill, Marouen Ben Guebila, Camila Lopes-Ramos, Kimberly Glass, John Quackenbush

Incremental Embedding Learning via Zero-Shot Translation

Kun Wei, Cheng Deng, Xu Yang, Maosen Li

Data-Free Knowledge Distillation with Soft Targeted Transfer Set Synthesis

Zi Wang

Deep Recurrent Belief Propagation Network for POMDPs

Yuhui Wang, Xiaoyang Tan

Tied Block Convolution: Leaner and Better CNNs with Shared Thinner Filters

Xudong Wang, Stella X. Yu

Harmonized Dense Knowledge Distillation Training for Multi-Exit Architectures

Xinglu Wang, Yingming Li

Adaptive Algorithms for Multi-armed Bandit with Composite and Anonymous Feedback

Siwei Wang, Haoyun Wang, Longbo Huang

Adaptive Verifiable Training Using Pairwise Class Similarity

Shiqi Wang, Kevin Eykholt, Taesung Lee, Jiyong Jang, Ian Molloy

Learning with Group Noise

qizhou wang, Jiangchao Yao, Chen Gong, Tongliang Liu, Mingming Gong

Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model

qizhou wang, Bo Han, Tongliang Liu, Gang Niu, Jian Yang

Contrastive Transformation for Self-supervised Correspondence Learning

Ning Wang, Wengang Zhou, Houqiang Li

Addressing Class Imbalance in Federated Learning

Lixu Wang, Shichao Xu, Xiao Wang, Qi Zhu

Adversarial Linear Contextual Bandits with Graph-Structured Side Observations

Lingda Wang, Bingcong Li, Huozhi Zhou, Georgios B. Giannakis, Lav R. Varshney

Embedding Heterogeneous Networks into Hyperbolic Space Without Meta-path

Lili Wang, Chongyang Gao, Chenghan Huang, Ruibo Liu, Weicheng Ma

Consistency Regularization with High-dimensional Non-adversarial Source-guided Perturbation for Unsupervised Domain Adaptation in Segmentation

Kaihong Wang, Chenhongyi Yang, Margrit Betke

Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion

Jinpeng Wang, Yuting Gao, Ke Li, Jianguo Hu, XINYANG JIANG

Debiasing Evaluations That Are Biased by Evaluations

Jingyan Wang, Ivan Stelmakh, Yuting Wei, Nihar B. Shah

Learning from Noisy Labels with Complementary Loss Functions

Deng-Bao Wang, Yong Wen, Lujia Pan, Min-ling Zhang

Quantum Exploration Algorithms for Multi-Armed Bandits

Daochen Wang, Xuchen You, Tongyang Li, Andrew M. Childs

Semi-Supervised Node Classification on Graphs: Markov Random Fields vs. Graph Neural Networks

Binghui Wang, Jinyuan Jia, Neil Zhenqiang Gong

Multi-View Information-Bottleneck Representation Learning

Zhibin Wan, Changqing Zhang, Pengfei Zhu, Qinghua Hu

Projection-free Online Learning over Strongly Convex Sets

Yuanyu Wan, Lijun Zhang

Projection-free Online Learning in Dynamic Environments

Yuanyu Wan, Bo Xue, Lijun Zhang

Approximate Multiplication of Sparse Matrices with Limited Space

Yuanyu Wan, Lijun Zhang

Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning

Sheng Wan, Shirui Pan, Jian Yang, Chen Gong

Nearest Neighbor Classifier Embedded Network for Active Learning

Fang Wan, Tianning Yuan, Mengying Fu, Xiangyang Ji, Qingming Huang

PID-Based Approach to Adversarial Attacks

Chen Wan, Biaohua Ye, Fangjun Huang

GraphMix: Improved Training of GNNs for Semi-Supervised Learning

Vikas Verma, Meng Qu, Kenji Kawaguchi, Alex Lamb, Yoshua Bengio

Gated Linear Networks

Joel Veness, Tor Lattimore, David Budden, Avishkar Bhoopchand, Christopher Mattern

Continual General Chunking Problem and SyncMap

Danilo Vasconcellos Vargas, Toshitake Asabuki

Expected Eligibility Traces

Hado van Hasselt, Sephora Madjiheurem, Matteo Hessel, David Silver, Andre Barreto

ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare

Ali Burak Ünal, Mete Akgün, Nico Pfeifer

Deep Fusion Clustering Network

Wenxuan Tu, sihang zhou, Xinwang Liu, Xifeng Guo, Zhiping Cai

Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks

Russell Tsuchida, Tim Pearce, Chris van der Heide, Fred Roosta, Marcus Gallagher

Toward Robust Long Range Policy Transfer

Wei-Cheng Tseng, Jin-Siang Lin, Yao-Min Feng, Min Sun

*-CFQ: Analyzing the Scalability of Machine Learning on a Compositional Task

Dmitry Tsarkov, Tibor Tihon, Nathan Scales, Nikola Momchev, Danila Sinopalnikov

Learning Adjustment Sets from Observational and Limited Experimental Data

Sofia Triantafillou, Greg Cooper

Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach

Cuong Tran, Ferdinando Fioretto, Pascal Van Hentenryck

Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods

Nicholay Topin, Stephanie Milani, Fei Fang, Manuela Veloso

Characterizing Deep Gaussian Processes via Nonlinear Recurrence Systems

Anh Tong, Jaesik Choi

Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior

Anh Tong, Toan M Tran, Hung Bui, Jaesik Choi

Meta Learning for Causal Direction

Jean-Francois Ton, Dino Sejdinovic, Kenji Fukumizu

Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration

Christian Tomani, Florian Buettner

Detecting Adversarial Examples from Sensitivity Inconsistency of Spatial-Transform Domain

Jinyu Tian, Jiantao Zhou, Yuanman Li, Jia Duan

Online Non-Monotone DR-Submodular Maximization

Nguyễn Kim Thắng, Abhinav Srivastav

Semi-Supervised Knowledge Amalgamation for Sequence Classification

Jidapa Thadajarassiri, Thomas Hartvigsen, Xiangnan Kong, Elke A Rundensteiner

Evolutionary Approach for AutoAugment Using the Thermodynamical Genetic Algorithm

Akira Terauchi, Naoki Mori

Gradient Descent Averaging and Primal-dual Averaging for Strongly Convex Optimization

Wei Tao, Wei Li, Zhisong Pan, Qing Tao

Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction

Hongyao Tang, Zhaopeng Meng, Guangyong Chen, Pengfei Chen, Chen Chen

Empowering Adaptive Early-Exit Inference with Latency Awareness

Xinrui Tan, Hongjia Li, Liming Wang, Xueqing Huang, Zhen Xu

Strategy and Benchmark for Converting Deep Q-Networks to Event-Driven Spiking Neural Networks

Weihao Tan, Devdhar Patel, Robert Kozma

Proxy Graph Matching with Proximal Matching Networks

Hao-Ru Tan, Chuang Wang, Si-Tong Wu, Tie-Qiang Wang, Xu-yao Zhang

Explicitly Modeled Attention Maps for Image Classification

Andong Tan, Duc Tam Nguyen, Maximilian Dax, Matthias Nießner, Thomas Brox

Near-Optimal Regret Bounds for Contextual Combinatorial Semi-Bandits with Linear Payoff Functions

Kei Takemura, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga

Learning Dynamics Models with Stable Invariant Sets

Naoya Takeishi, Yoshinobu Kawahara

PAC Learning of Causal Trees with Latent Variables

Prasad Tadepalli, Stuart J. Russell

TempLe: Learning Template of Transitions for Sample Efficient Multi-task RL

Yanchao Sun, Xiangyu Yin, Furong Huang

Stability and Generalization of Decentralized Stochastic Gradient Descent

Tao Sun, Dongsheng Li, Bao Wang

HiABP: Hierarchical Initialized ABP for Unsupervised Representation Learning

Jiankai Sun, Rui Liu, Bolei Zhou

`Less Than One'-Shot Learning: Learning N Classes From M < N Samples

Ilia Sucholutsky, Matthias Schonlau

Hierarchical Relational Inference

Aleksandar Stanić, Sjoerd van Steenkiste, Jürgen Schmidhuber

Error-Correcting Output Codes with Ensemble Diversity for Robust Learning in Neural Networks

Yang Song, Qiyu Kang, Wee Peng Tay

Implicit Kernel Attention

Kyungwoo Song, Yohan Jung, Dongjun Kim, Il-chul Moon

Improving Gradient Flow with Unrolled Highway Expectation Maximization

Chonghyuk Song, Eunseok Kim, Inwook Shim

Solving Common-Payoff Games with Approximate Policy Iteration

Samuel Sokota, Edward Lockhart, Finbarr Timbers, Elnaz Davoodi, Ryan D'Orazio

UNIPoint: Universally Approximating Point Processes Intensities

Alexander Soen, Alexander Mathews, Daniel Grixti-Cheng, Lexing Xie

Differential Spectral Normalization (DSN) for PDE Discovery

Chi Chiu So, Tsz On Li, Chufang Wu, Siu Pang Yung

DIBS: Diversity Inducing Information Bottleneck in Model Ensembles

Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg

Towards Domain Invariant Single Image Dehazing

Pranjay Shyam, Kuk-Jin Yoon, Kyung-Soo Kim

Interpretable Sequence Classification via Discrete Optimization

Maayan Shvo, Andrew C. Li, Rodrigo Toro Icarte, Sheila A. McIlraith

Scalable Affinity Propagation for Massive Datasets

Hiroaki Shiokawa

Online Class-Incremental Continual Learning with Adversarial Shapley Value

Dongsub Shim, Zheda Mai, Jihwan Jeong, Scott Sanner, Hyunwoo Kim

Improved Penalty Method via Doubly Stochastic Gradients for Bilevel Hyperparameter Optimization

Wanli Shi, Bin Gu

Raven's Progressive Matrices Completion with Latent Gaussian Process Priors

Fan Shi, Bin Li, Xiangyang Xue

Federated Multi-Armed Bandits

Chengshuai Shi, Cong Shen

Partial Is Better Than All: Revisiting Fine-tuning Strategy for Few-shot Learning

Zhiqiang Shen, Zechun Liu, Jie Qin, Marios Savvides, Kwang-Ting Cheng

PDO-eS2CNNs: Partial Differential Operator Based Equivariant Spherical CNNs

Zhengyang Shen, Tiancheng Shen, Zhouchen Lin, Jinwen Ma

STL-SGD: Speeding Up Local SGD with Stagewise Communication Period

Shuheng Shen, Yifei Cheng, Jingchang Liu, Linli Xu

Time Series Anomaly Detection with Multiresolution Ensemble Decoding

Lifeng Shen, Zhongzhong Yu, Qianli Ma, James T. Kwok

Theoretically Principled Deep RL Acceleration via Nearest Neighbor Function Approximation

Junhong Shen, Lin F. Yang

Membership Privacy for Machine Learning Models Through Knowledge Transfer

Virat Shejwalkar, Amir Houmansadr

Meta-Learning Effective Exploration Strategies for Contextual Bandits

Amr Sharaf, Hal Daume III

Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions

Xiaoting Shao, Arseny Skryagin, Wolfgang Stammer, Patrick Schramowski, Kristian Kersting

Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks

Uday Shankar Shanthamallu, Jayaraman J. Thiagarajan, Andreas Spanias

Multi-type Disentanglement without Adversarial Training

Lei Sha, Thomas Lukasiewicz

Learning Precise Temporal Point Event Detection with Misaligned Labels

Julien Schroeter, Kirill Sidorov, David Marshall

Active Feature Selection for the Mutual Information Criterion

Shachar Schnapp, Sivan Sabato

AdvantageNAS: Efficient Neural Architecture Search with Credit Assignment

Rei Sato, Jun Sakuma, Youhei Akimoto

A Deeper Look at the Hessian Eigenspectrum of Deep Neural Networks and its Applications to Regularization

Adepu Ravi Sankar, Yash Khasbage, Rahul Vigneswaran, Vineeth N Balasubramanian

Inverse Reinforcement Learning with Explicit Policy Estimates

Navyata Sanghvi, Shinnosuke Usami, Mohit Sharma, Joachim Groeger, Kris Kitani

Anytime Inference with Distilled Hierarchical Neural Ensembles

Adria Ruiz, Jakob Verbeek

Visual Transfer For Reinforcement Learning Via Wasserstein Domain Confusion

Josh Roy, George D. Konidaris

Adversarial Permutation Guided Node Representations for Link Prediction

Indradyumna Roy, Abir De, Soumen Chakrabarti

Why Adversarial Interaction Creates Non-Homogeneous Patterns: A Pseudo-Reaction-Diffusion Model for Turing Instability

Litu Rout

Shuffling Recurrent Neural Networks

Michael Rotman, Lior Wolf

Robust Fairness Under Covariate Shift

Ashkan Rezaei, Anqi Liu, Omid Memarrast, Brian D. Ziebart

Multiple Kernel Clustering with Kernel k-Means Coupled Graph Tensor Learning

Zhenwen Ren, Quansen Sun, Dong Wei

Improving Generative Moment Matching Networks with Distribution Partition

Yong Ren, Yucen Luo, Jun Zhu

Online DR-Submodular Maximization: Minimizing Regret and Constraint Violation

Prasanna Raut, Omid Sadeghi, Maryam Fazel