AAAI 2020

1,794 papers

Adaptive Trust Region Policy Optimization: Global Convergence and Faster Rates for Regularized MDPs

Lior Shani, Yonathan Efroni, Shie Mannor

Improved PAC-Bayesian Bounds for Linear Regression

Vera Shalaeva, Alireza Fakhrizadeh Esfahani, Pascal Germain, Mihaly Petreczky

Online Active Learning of Reject Option Classifiers

Kulin Shah, Naresh Manwani

Sequential Mode Estimation with Oracle Queries

Dhruti Shah, Tuhinangshu Choudhury, Nikhil Karamchandani, Aditya Gopalan

Universal Adversarial Training

Ali Shafahi, Mahyar Najibi, Zheng Xu, John Dickerson, Larry S. Davis

Empirical Bounds on Linear Regions of Deep Rectifier Networks

Thiago Serra, Srikumar Ramalingam

Uncertainty-Aware Deep Classifiers Using Generative Models

Murat Sensoy, Lance Kaplan, Federico Cerutti, Maryam Saleki

Learning Counterfactual Representations for Estimating Individual Dose-Response Curves

Patrick Schwab, Lorenz Linhardt, Stefan Bauer, Joachim M. Buhmann, Walter Karlen

Graph Representation Learning via Ladder Gamma Variational Autoencoders

Arindam Sarkar, Nikhil Mehta, Piyush Rai

Weighted Sampling for Combined Model Selection and Hyperparameter Tuning

Dimitrios Sarigiannis, Thomas Parnell, Haralampos Pozidis

Rank3DGAN: Semantic Mesh Generation Using Relative Attributes

Yassir Saquil, Qun-Ce Xu, Yong-Liang Yang, Peter Hall

Random Intersection Graphs and Missing Data

Dror Salti, Yakir Berchenko

Weakly Supervised Sequence Tagging from Noisy Rules

Esteban Safranchik, Shiying Luo, Stephen Bach

Chained Representation Cycling: Learning to Estimate 3D Human Pose and Shape by Cycling Between Representations

Nadine Rueegg, Christoph Lassner, Michael Black, Konrad Schindler

Linear Context Transform Block

Dongsheng Ruan, Jun Wen, Nenggan Zheng, Min Zheng

Generative Continual Concept Learning

Mohammad Rostami, Soheil Kolouri, Praveen Pilly, James McClelland

Actionable Ethics through Neural Learning

Daniele Rossini, Danilo Croce, Sara Mancini, Massimo Pellegrino, Roberto Basili

Ensembles of Locally Independent Prediction Models

Andrew Ross, Weiwei Pan, Leo Celi, Finale Doshi-velez

On the Role of Weight Sharing During Deep Option Learning

Matthew Riemer, Ignacio Cases, Clemens Rosenbaum, Miao Liu, Gerald Tesauro

Fairness for Robust Log Loss Classification

Ashkan Rezaei, Rizal Fathony, Omid Memarrast, Brian Ziebart

Delay-Adaptive Distributed Stochastic Optimization

Zhaolin Ren, Zhengyuan Zhou, Linhai Qiu, Ajay Deshpande, Jayant Kalagnanam

DARB: A Density-Adaptive Regular-Block Pruning for Deep Neural Networks

Ren Ao, Zhang Tao, Wang Yuhao, Lin Sheng, Dong Peiyan

Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains

Sathya N. Ravi, Abhay Venkatesh, Glenn M. Fung, Vikas Singh

Abstract Interpretation of Decision Tree Ensemble Classifiers

Francesco Ranzato, Marco Zanella

ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

Ekagra Ranjan, Soumya Sanyal, Partha Talukdar

Synthesizing Action Sequences for Modifying Model Decisions

Goutham Ramakrishnan, Yun Chan Lee, Aws Albarghouthi

How Should an Agent Practice?

Janarthanan Rajendran, Richard Lewis, Vivek Veeriah, Honglak Lee, Satinder Singh

A New Burrows Wheeler Transform Markov Distance

Edward Raff, Charles Nicholas, Mark McLean

Temporal Network Embedding with High-Order Nonlinear Information

Zhenyu Qiu, Wenbin Hu, Jia Wu, Weiwei Liu, Bo Du

Stochastic Approximate Gradient Descent via the Langevin Algorithm

Yixuan Qiu, Xiao Wang

Diversified Bayesian Nonnegative Matrix Factorization

Qiao Maoying, Yu Jun, Liu Tongliang, Wang Xinchao, Tao Dacheng

CAG: A Real-Time Low-Cost Enhanced-Robustness High-Transferability Content-Aware Adversarial Attack Generator

Huy Phan, Yi Xie, Siyu Liao, Jie Chen, Bo Yuan

Generalized Hidden Parameter MDPs:Transferable Model-Based RL in a Handful of Trials

Christian Perez, Felipe Petroski Such, Theofanis Karaletsos

A Bayesian Approach for Estimating Causal Effects from Observational Data

Johan Pensar, Topi Talvitie, Antti Hyttinen, Mikko Koivisto

Motif-Matching Based Subgraph-Level Attentional Convolutional Network for Graph Classification

Hao Peng, Jianxin Li, Qiran Gong, Yuanxin Ning, Senzhang Wang

Achieving Fairness in the Stochastic Multi-Armed Bandit Problem

Vishakha Patil, Ganesh Ghalme, Vineet Nair, Y. Narahari

Unsupervised Attributed Multiplex Network Embedding

Chanyoung Park, Donghyun Kim, Jiawei Han, Hwanjo Yu

EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

Aldo Pareja, Giacomo Domeniconi, Jie Chen, Tengfei Ma, Toyotaro Suzumura

Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks

Fabio Pardo, Vitaly Levdik, Petar Kormushev

Adversarial Localized Energy Network for Structured Prediction

Pingbo Pan, Ping Liu, Yan Yan, Tianbao Yang, Yi Yang

Overcoming Catastrophic Forgetting by Neuron-Level Plasticity Control

Inyoung Paik, Sangjun Oh, Taeyeong Kwak, Injung Kim

Linear Bandits with Feature Feedback

Urvashi Oswal, Aniruddha Bhargava, Robert Nowak

Uncorrected Least-Squares Temporal Difference with Lambda-Return

Takayuki Osogami

Cut-Based Graph Learning Networks to Discover Compositional Structure of Sequential Video Data

Kyoung-Woon On, Eun-Sol Kim, Yu-Jung Heo, Byoung-tak Zhang

Weighted Automata Extraction from Recurrent Neural Networks via Regression on State Spaces

Takamasa Okudono, Masaki Waga, Taro Sekiyama, Ichiro Hasuo

Radial and Directional Posteriors for Bayesian Deep Learning

Changyong Oh, Kamil Adamczewski, Mijung Park

Maximum Likelihood Embedding of Logistic Random Dot Product Graphs

Luke J. O'Connor, Muriel Medard, Soheil Feizi

Brain-Mediated Transfer Learning of Convolutional Neural Networks

Satoshi Nishida, Yusuke Nakano, Antoine Blanc, Naoya Maeda, Masataka Kado

On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models

Erik Nijkamp, Mitch Hill, Tian Han, Song-chun Zhu, Ying Nian Wu

Reliable Multilabel Classification: Prediction with Partial Abstention

Vu-Linh Nguyen, Eyke Hüllermeier

Bayesian Optimization for Categorical and Category-Specific Continuous Inputs

Dang Nguyen, Sunil Gupta, Santu Rana, Alistair Shilton, Svetha Venkatesh

Pairwise Fairness for Ranking and Regression

Harikrishna Narasimhan, Andrew Cotter, Maya Gupta, Serena Wang

Efficiently Enumerating Substrings with Statistically Significant Frequencies of Locally Optimal Occurrences in Gigantic String

Atsuyoshi Nakamura, Ichigaku Takigawa, Hiroshi Mamitsuka

An Intrinsically-Motivated Approach for Learning Highly Exploring and Fast Mixing Policies

Mirco Mutti, Marcello Restelli

Learning Weighted Model Integration Distributions

Paolo Morettin, Samuel Kolb, Stefano Teso, Andrea Passerini

Self-Supervised Learning for Generalizable Out-of-Distribution Detection

Sina Mohseni, Mandar Pitale, JBS Yadawa, Zhangyang Wang

Metareasoning in Modular Software Systems: On-the-Fly Configuration Using Reinforcement Learning with Rich Contextual Representations

Aditya Modi, Debadeepta Dey, Alekh Agarwal, Adith Swaminathan, Besmira Nushi

On Adaptivity in Information-Constrained Online Learning

Siddharth Mitra, Aditya Gopalan

Improved Knowledge Distillation via Teacher Assistant

Seyed Iman Mirzadeh, Mehrdad Farajtabar, Ang Li, Nir Levine, Akihiro Matsukawa

Differentiable Reasoning on Large Knowledge Bases and Natural Language

Pasquale Minervini, Matko Bošnjak, Tim Rocktäschel, Sebastian Riedel, Edward Grefenstette

Deep Embedded Non-Redundant Clustering

Lukas Miklautz, Dominik Mautz, Muzaffer Can Altinigneli, Christian Böhm, Claudia Plant

Regularized Wasserstein Means for Aligning Distributional Data

Liang Mi, Wen Zhang, Yalin Wang

Neural Inheritance Relation Guided One-Shot Layer Assignment Search

Rang Meng, Weijie Chen, Di Xie, yuan zhang, Shiliang Pu

Multi-Zone Unit for Recurrent Neural Networks

Fandong Meng, Jinchao Zhang, Yang Liu, Jie Zhou

Learning Agent Communication under Limited Bandwidth by Message Pruning

Hangyu Mao, Zhengchao Zhang, Zhen Xiao, Zhibo Gong, Yan Ni

Graph-Hist: Graph Classification from Latent Feature Histograms with Application to Bot Detection

Thomas Magelinski, David Beskow, Kathleen M. Carley

Count-Based Exploration with the Successor Representation

Marlos C. Machado, Marc G. Bellemare, Michael Bowling

PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-Time Execution on Mobile Devices

Xiaolong Ma, Fu-Ming Guo, Wei Niu, Xue Lin, Jian Tang

Reinforcement Learning from Imperfect Demonstrations under Soft Expert Guidance

Mingxuan Jing, Xiaojian Ma, Wenbing Huang, Fuchun Sun, Chao Yang

Particle Filter Recurrent Neural Networks

Xiao Ma, Peter Karkus, David Hsu, Wee Sun Lee

Projective Quadratic Regression for Online Learning

Wenye Ma

The HSIC Bottleneck: Deep Learning without Back-Propagation

Wan-Duo Kurt Ma, J. P. Lewis, W. Bastiaan Kleijn

Online Planner Selection with Graph Neural Networks and Adaptive Scheduling

Tengfei Ma, Patrick Ferber, Siyu Huo, Jie Chen, Michael Katz

Adversarial Dynamic Shapelet Networks

Qianli Ma, Wanqing Zhuang, Sen Li, Desen Huang, Garrison Cottrell

Temporal Pyramid Recurrent Neural Network

Qianli Ma, Zhenxi Lin, Enhuan Chen, Garrison Cottrell

Inefficiency of K-FAC for Large Batch Size Training

Linjian Ma, Gabe Montague, Jiayu Ye, Zhewei Yao, Amir Gholami

Memory Augmented Graph Neural Networks for Sequential Recommendation

Chen Ma, Liheng Ma, Yingxue Zhang, Jianing Sun, Xue Liu

Fastened CROWN: Tightened Neural Network Robustness Certificates

Zhaoyang Lyu, Ching-Yun Ko, Zhifeng Kong, Ngai Wong, Dahua Lin

Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment

You-Wei Luo, Chuan-Xian Ren, Pengfei Ge, Ke-Kun Huang, Yu-Feng Yu

Learning from the Past: Continual Meta-Learning with Bayesian Graph Neural Networks

Yadan Luo, Zi Huang, Zheng Zhang, Ziwei Wang, Mahsa Baktashmotlagh

Enhancing Nearest Neighbor Based Entropy Estimator for High Dimensional Distributions via Bootstrapping Local Ellipsoid

Chien Lu, Jaakko Peltonen

Structured Output Learning with Conditional Generative Flows

You Lu, Bert Huang

Cost-Effective Incentive Allocation via Structured Counterfactual Inference

Romain Lopez, Chenchen Li, Xiang Yan, Junwu Xiong, Michael Jordan

Structured Sparsification of Gated Recurrent Neural Networks

Ekaterina Lobacheva, Nadezhda Chirkova, Alexander Markovich, Dmitry Vetrov

Incentivized Exploration for Multi-Armed Bandits under Reward Drift

Zhiyuan Liu, Huazheng Wang, Fan Shen, Kai Liu, Lijun Chen

Towards Fine-Grained Temporal Network Representation via Time-Reinforced Random Walk

Zhining Liu, Dawei Zhou, Yada Zhu, Jinjie GU, Jingrui He

Interactive Rare-Category-of-Interest Mining from Large Datasets

Zhenguang Liu, Sihao Hu, Yifang Yin, Jianhai Chen, Kevin Chiew

Uncertainty Aware Graph Gaussian Process for Semi-Supervised Learning

Zhao-Yang Liu, Shao-Yuan Li, Songcan Chen, Yao Hu, Sheng-jun Huang

Collaborative Sampling in Generative Adversarial Networks

Yuejiang Liu, Parth Kothari, Alexandre Alahi

IPO: Interior-Point Policy Optimization under Constraints

Yongshuai Liu, Jiaxin Ding, Xin Liu

Diversified Interactive Recommendation with Implicit Feedback

Yong Liu, Yingtai Xiao, Qiong Wu, Chunyan Miao, Juyong Zhang

Adaptive Activation Network and Functional Regularization for Efficient and Flexible Deep Multi-Task Learning

Yingru Liu, Xuewen Yang, Dongliang Xie, Xin Wang, Li Shen

Independence Promoted Graph Disentangled Networks

Yanbei Liu, Xiao Wang, Shu Wu, Zhitao Xiao

Weighted-Sampling Audio Adversarial Example Attack

Xiaolei Liu, Kun Wan, Yufei Ding, Xiaosong Zhang, Qingxin Zhu

Layerwise Sparse Coding for Pruned Deep Neural Networks with Extreme Compression Ratio

Xiao Liu, Wenbin Li, Jing Huo, Lili Yao, Yang Gao

An ADMM Based Framework for AutoML Pipeline Configuration

Sijia Liu, Parikshit Ram, Deepak Vijaykeerthy, Djallel Bouneffouf, Gregory Bramble

Stochastic Loss Function

Qingliang Liu, Jinmei Lai

AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates

Ning Liu, Xiaolong Ma, Zhiyuan Xu, Yanzhi Wang, Jian Tang

Attribute Propagation Network for Graph Zero-Shot Learning

LU LIU, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang

A Cluster-Weighted Kernel K-Means Method for Multi-View Clustering

Jing Liu, Fuyuan Cao, Xiao-Zhi Gao, Liqin Yu, Jiye Liang