AAAI 2021

1,961 papers

Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection

Edward Raff, William Fleshman, Richard Zak, Hyrum S. Anderson, Bobby Filar

Uncertainty-Aware Policy Optimization: A Robust, Adaptive Trust Region Approach

James Queeney, Ioannis Ch. Paschalidis, Christos G. Cassandras

Relation-aware Graph Attention Model with Adaptive Self-adversarial Training

Xiao Qin, Nasrullah Sheikh, Berthold Reinwald, Lingfei Wu

Fast Multi-view Discrete Clustering with Anchor Graphs

Qianyao Qiang, Bin Zhang, Fei Wang, Feiping Nie

AutoDropout: Learning Dropout Patterns to Regularize Deep Networks

Hieu Pham, Quoc Le

Fast PCA in 1-D Wasserstein Spaces via B-splines Representation and Metric Projection

Matteo Pegoraro, Mario Beraha

Maximum Roaming Multi-Task Learning

Lucas Pascal, Pietro Michiardi, Xavier Bost, Benoit Huet, Maria A. Zuluaga

Vector Quantized Bayesian Neural Network Inference for Data Streams

Namuk Park, Taekyu Lee, Songkuk Kim

Tempered Sigmoid Activations for Deep Learning with Differential Privacy

Nicolas Papernot, Abhradeep Thakurta, Shuang Song, Steve Chien, Úlfar Erlingsson

Robust Reinforcement Learning: A Case Study in Linear Quadratic Regulation

Bo Pang, Zhong-Ping Jiang

NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search

Rameswar Panda, Michele Merler, Mayoore S Jaiswal, Hui Wu, Kandan Ramakrishnan

Disentangled Information Bottleneck

Ziqi Pan, Li Niu, Jianfu Zhang, Liqing Zhang

Robustness Guarantees for Mode Estimation with an Application to Bandits

Aldo Pacchiano, Heinrich Jiang, Michael I. Jordan

Defending against Backdoors in Federated Learning with Robust Learning Rate

Mustafa Safa Ozdayi, Murat Kantarcioglu, Yulia R. Gel

Second Order Techniques for Learning Time-series with Structural Breaks

Takayuki Osogami

Augmented Experiment in Material Engineering Using Machine Learning

Aomar Osmani, Massinissa Hamidi, Salah Bouhouche

Meta-Learning Framework with Applications to Zero-Shot Time-Series Forecasting

Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio

FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting

Boris N. Oreshkin, Arezou Amini, Lucy Coyle, Mark Coates

OT-Flow: Fast and Accurate Continuous Normalizing Flows via Optimal Transport

Derek Onken, Samy Wu Fung, Xingjian Li, Lars Ruthotto

Learning Deep Generative Models for Queuing Systems

César Ojeda, Kostadin Cvejoski, Bodgan Georgiev, Christian Bauckhage, Jannis Schuecker

Multinomial Logit Contextual Bandits: Provable Optimality and Practicality

Min-hwan Oh, Garud Iyengar

Inverse Reinforcement Learning From Like-Minded Teachers

Ritesh Noothigattu, Tom Yan, Ariel D. Procaccia

Warm Starting CMA-ES for Hyperparameter Optimization

Masahiro Nomura, Shuhei Watanabe, Youhei Akimoto, Yoshihiko Ozaki, Masaki Onishi

RT3D: Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices

Wei Niu, Mengshu Sun, Zhengang Li, Jou-An Chen, Jiexiong Guan

Learning of Structurally Unambiguous Probabilistic Grammars

Dolav Nitay, Dana Fisman, Michal Ziv-Ukelson

Improving Model Robustness by Adaptively Correcting Perturbation Levels with Active Queries

Kun-Peng Ning, Lue Tao, Songcan Chen, Sheng-jun Huang

Precision-based Boosting

Mohammad Hossein Nikravan, Marjan Movahedan, Sandra Zilles

Distributional Reinforcement Learning via Moment Matching

Thanh Nguyen-Tang, Sunil Gupta, Svetha Venkatesh

Top-k Ranking Bayesian Optimization

Quoc Phong Nguyen, Sebastian Tay, Bryan Kian Hsiang Low, Patrick Jaillet

An Information-Theoretic Framework for Unifying Active Learning Problems

Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet

Temporal Latent Auto-Encoder: A Method for Probabilistic Multivariate Time Series Forecasting

Nam Nguyen, Brian Quanz

Minimum Robust Multi-Submodular Cover for Fairness

Lan N. Nguyen, My T. Thai

Differentially Private k-Means via Exponential Mechanism and Max Cover

Huy L. Nguyen, Anamay Chaturvedi, Eric Z Xu

Modular Graph Transformer Networks for Multi-Label Image Classification

Hoang D. Nguyen, Xuan-Son Vu, Duc-Trong Le

Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning

A. Tuan Nguyen, Hyewon Jeong, Eunho Yang, Sung Ju Hwang

Advice-Guided Reinforcement Learning in a non-Markovian Environment

Daniel Neider, Jean-Raphael Gaglione, Ivan Gavran, Ufuk Topcu, Bo Wu

5* Knowledge Graph Embeddings with Projective Transformations

Mojtaba Nayyeri, Sahar Vahdati, Can Aykul, Jens Lehmann

Objective-Based Hierarchical Clustering of Deep Embedding Vectors

Stanislav Naumov, Grigory Yaroslavtsev, Dmitrii Avdiukhin

Game of Gradients: Mitigating Irrelevant Clients in Federated Learning

Lokesh Nagalapatti, Ramasuri Narayanam

Elastic Consistency: A Practical Consistency Model for Distributed Stochastic Gradient Descent

Giorgi Nadiradze, Ilia Markov, Bapi Chatterjee, Vyacheslav Kungurtsev, Dan Alistarh

Task-Agnostic Exploration via Policy Gradient of a Non-Parametric State Entropy Estimate

Mirco Mutti, Lorenzo Pratissoli, Marcello Restelli

Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines

Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi, Pushkar Shukla, Sadhana Kumaravel

Improved Mutual Information Estimation

Youssef Mroueh, Igor Melnyk, Pierre Dognin, Jarret Ross, Tom Sercu

Scheduling of Time-Varying Workloads Using Reinforcement Learning

Shanka Subhra Mondal, Nikhil Sheoran, Subrata Mitra

A General Class of Transfer Learning Regression without Implementation Cost

Shunya Minami, Song Liu, Stephen Wu, Kenji Fukumizu, Ryo Yoshida

Generative Semi-supervised Learning for Multivariate Time Series Imputation

Xiaoye Miao, Yangyang Wu, Jun Wang, Yunjun Gao, Xudong Mao

Discovering Fully Oriented Causal Networks

Osman A Mian, Alexander Marx, Jilles Vreeken

Consistency and Finite Sample Behavior of Binary Class Probability Estimation

Alexander Mey, Marco Loog

Policy Optimization as Online Learning with Mediator Feedback

Alberto Maria Metelli, Matteo Papini, Pierluca D'Oro, Marcello Restelli

Lenient Regret for Multi-Armed Bandits

Nadav Merlis, Shie Mannor

Physarum Powered Differentiable Linear Programming Layers and Applications

Zihang Meng, Sathya N. Ravi, Vikas Singh

Exacerbating Algorithmic Bias through Fairness Attacks

Ninareh Mehrabi, Muhammad Naveed, Fred Morstatter, Aram Galstyan

Infinite Gaussian Mixture Modeling with an Improved Estimation of the Number of Clusters

Avi Matza, Yuval Bistritz

Scalable Graph Networks for Particle Simulations

Karolis Martinkus, Aurelien Lucchi, Nathanael Perraudin

Searching for Machine Learning Pipelines Using a Context-Free Grammar

Radu Marinescu, Akihiro Kishimoto, Parikshit Ram, Ambrish Rawat, Martin Wistuba

Deep Mutual Information Maximin for Cross-Modal Clustering

Yiqiao Mao, Xiaoqiang Yan, Qiang Guo, Yangdong Ye

Composite Adversarial Attacks

Xiaofeng Mao, YueFeng Chen, Shuhui Wang, Hang Su, Yuan He

Exact Reduction of Huge Action Spaces in General Reinforcement Learning

Sultan J. Majeed, Marcus Hutter

Sequential Attacks on Kalman Filter-based Forward Collision Warning Systems

Yuzhe Ma, Jon A Sharp, Ruizhe Wang, Earlence Fernandes, Xiaojin Zhu

Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport

Tengfei Ma, Jie Chen

Joint-Label Learning by Dual Augmentation for Time Series Classification

Qianli Ma, Zhenjing Zheng, Jiawei Zheng, Sen Li, Wanqing Zhuang

Learning Representations for Incomplete Time Series Clustering

Qianli Ma, Chuxin Chen, Sen Li, Garrison W. Cottrell

On the Adequacy of Untuned Warmup for Adaptive Optimization

Jerry Ma, Denis Yarats

Multi-Domain Multi-Task Rehearsal for Lifelong Learning

Fan Lyu, Shuai Wang, Wei Feng, Zihan Ye, Fuyuan Hu

Adaptive Knowledge Driven Regularization for Deep Neural Networks

Zhaojing Luo, Shaofeng Cai, Can Cui, Beng Chin Ooi, Yang Yang

Semi-supervised Medical Image Segmentation through Dual-task Consistency

Xiangde Luo, Jieneng Chen, Tao Song, Guotai Wang

Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices

Luo Luo, Cheng Chen, Guangzeng Xie, Haishan Ye

PULNS: Positive-Unlabeled Learning with Effective Negative Sample Selector

Chuan Luo, Pu Zhao, Chen Chen, Bo Qiao, Chao Du

Tailoring Embedding Function to Heterogeneous Few-Shot Tasks by Global and Local Feature Adaptors

Su Lu, Han-Jia Ye, De-Chuan Zhan

Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning

Songtao Lu, Kaiqing Zhang, Tianyi Chen, Tamer Basar, Lior Horesh

Stochastic Bandits with Graph Feedback in Non-Stationary Environments

Shiyin Lu, Yao Hu, Lijun Zhang

Stochastic Graphical Bandits with Adversarial Corruptions

Shiyin Lu, Guanghui Wang, Lijun Zhang

Improving Causal Discovery By Optimal Bayesian Network Learning

Ni Y Lu, Kun Zhang, Changhe Yuan

Learning from eXtreme Bandit Feedback

Romain Lopez, Inderjit S. Dhillon, Michael I. Jordan

Task Aligned Generative Meta-learning for Zero-shot Learning

Zhe Liu, Yun Li, Lina Yao, Xianzhi Wang, Guodong Long

ROSITA: Refined BERT cOmpreSsion with InTegrAted techniques

Yuanxin Liu, Zheng Lin, Fengcheng Yuan

Train a One-Million-Way Instance Classifier for Unsupervised Visual Representation Learning

Yu Liu, Lianghua Huang, PAN PAN, Bin Wang, Yinghui Xu

Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision

Xingchao Liu, Mao Ye, Dengyong Zhou, Qiang Liu

FLAME: Differentially Private Federated Learning in the Shuffle Model

Ruixuan Liu, Yang Cao, Hong Chen, Ruoyang Guo, Masatoshi Yoshikawa

Dynamically Grown Generative Adversarial Networks

Lanlan Liu, Yuting Zhang, Jia Deng, Stefano Soatto

Hierarchical Multiple Kernel Clustering

Jiyuan Liu, Xinwang Liu, Siwei Wang, sihang zhou, Yuexiang Yang

Stable Adversarial Learning under Distributional Shifts

Jiashuo Liu, Zheyan Shen, Peng Cui, Linjun Zhou, Kun Kuang

Overcoming Catastrophic Forgetting in Graph Neural Networks

Huihui Liu, Yiding Yang, Xinchao Wang

Unchain the Search Space with Hierarchical Differentiable Architecture Search

Guanting Liu, Yujie Zhong, Sheng Guo, Matthew R. Scott, Weilin Huang

Learning a Few-shot Embedding Model with Contrastive Learning

Chen Liu, Yanwei Fu, Chengming Xu, Siqian Yang, Jilin Li

TransTailor: Pruning the Pre-trained Model for Improved Transfer Learning

Bingyan Liu, Yifeng Cai, Yao Guo, Xiangqun Chen

Multi-Proxy Wasserstein Classifier for Image Classification

Benlin Liu, Yongming Rao, Jiwen Lu, Jie Zhou, Cho-jui Hsieh

Auto-Encoding Transformations in Reparameterized Lie Groups for Unsupervised Learning

Feng Lin, Haohang Xu, Houqiang Li, Hongkai Xiong, Guo-Jun Qi

Class-Attentive Diffusion Network for Semi-Supervised Classification

Jongin Lim, Daeho Um, Hyung Jin Chang, Dae Ung Jo, Jin Young Choi

Sample Selection for Universal Domain Adaptation

Omri Lifshitz, Lior Wolf

From Label Smoothing to Label Relaxation

Julian Lienen, Eyke Hüllermeier

Doubly Residual Neural Decoder: Towards Low-Complexity High-Performance Channel Decoding

Siyu Liao, Chunhua Deng, Miao Yin, Bo Yuan

Large Norms of CNN Layers Do Not Hurt Adversarial Robustness

Youwei Liang, Dong Huang

Longitudinal Deep Kernel Gaussian Process Regression

Junjie Liang, Yanting Wu, Dongkuan Xu, Vasant G Honavar

Contrastive Clustering

Yunfan Li, Peng Hu, Zitao Liu, Dezhong Peng, Joey Tianyi Zhou

TRQ: Ternary Neural Networks With Residual Quantization

Yue Li, Wenrui Ding, Chunlei Liu, Baochang Zhang, Guodong Guo

Online Optimal Control with Affine Constraints

Yingying Li, Subhro Das, Na Li

Scheduled Sampling in Vision-Language Pretraining with Decoupled Encoder-Decoder Network

Yehao Li, Yingwei Pan, Ting Yao, Jingwen Chen, Tao Mei

One-shot Graph Neural Architecture Search with Dynamic Search Space

Yanxi Li, Zean Wen, Yunhe Wang, Chang Xu

Learned Extragradient ISTA with Interpretable Residual Structures for Sparse Coding

Yangyang Li, Lin Kong, Fanhua Shang, Yuanyuan Liu, Hongying Liu