AAAI 2020

1,794 papers

Federated Patient Hashing

Jie Xu, Zhenxing Xu, Peter Walker, Fei Wang

Gromov-Wasserstein Factorization Models for Graph Clustering

Hongtengl Xu

Learning Feature Interactions with Lorentzian Factorization Machine

Canran Xu, Ming Wu

Infinite ShapeOdds: Nonparametric Bayesian Models for Shape Representations

Wei Xing, Shireen Elhabian, Robert Kirby, Ross T. Whitaker, Shandian Zhe

Partial Multi-Label Learning with Noisy Label Identification

Ming-Kun Xie, Sheng-jun Huang

Efficient Projection-Free Online Methods with Stochastic Recursive Gradient

Jiahao Xie, Zebang Shen, Chao Zhang, Boyu Wang, Hui Qian

Dual Adversarial Co-Learning for Multi-Domain Text Classification

Yuan Wu, Yuhong Guo

Multi-Label Causal Feature Selection

Xingyu Wu, Bingbing Jiang, Kui Yu, Huanhuan Chen, Chunyan Miao

SK-Net: Deep Learning on Point Cloud via End-to-End Discovery of Spatial Keypoints

Weikun Wu, Yan Zhang, David Wang, Yunqi Lei

Regional Tree Regularization for Interpretability in Deep Neural Networks

Mike Wu, Sonali Parbhoo, Michael Hughes, Ryan Kindle, Leo Celi

Meta-Amortized Variational Inference and Learning

Mike Wu, Kristy Choi, Noah Goodman, Stefano Ermon

Estimating Early Fundraising Performance of Innovations via Graph-Based Market Environment Model

Likang Wu, Zhi Li, Hongke Zhao, Zhen Pan, Qi Liu

Unified Graph and Low-Rank Tensor Learning for Multi-View Clustering

Jianlong Wu, Xingyu Xie, Liqiang Nie, Zhouchen Lin, Hongbin Zha

Vector Quantization-Based Regularization for Autoencoders

Hanwei Wu, Markus Flierl

Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics

Bingzhe Wu, Chaochao Chen, Shiwan Zhao, Cen Chen, Yuan Yao

ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems

Philippe Wenk, Gabriele Abbati, Michael A. Osborne, Bernhard Schölkopf, Andreas Krause

Towards Certificated Model Robustness Against Weight Perturbations

Tsui-Wei Weng, Pu Zhao, Sijia Liu, Pin-Yu Chen, Xue Lin

Multi-View Multiple Clusterings Using Deep Matrix Factorization

Shaowei Wei, Jun Wang, Guoxian Yu, Carlotta Domeniconi, Xiangliang Zhang

Less Is Better: Unweighted Data Subsampling via Influence Function

Zifeng Wang, Hong Zhu, Zhenhua Dong, Xiuqiang He, Shao-Lun Huang

Transparent Classification with Multilayer Logical Perceptrons and Random Binarization

Zhuo Wang, Wei Zhang, Ning Liu, Jianyong Wang

Attention-over-Attention Field-Aware Factorization Machine

Zhibo Wang, Jinxin Ma, Yongquan Zhang, Qian Wang, Ju Ren

Non-Local U-Nets for Biomedical Image Segmentation

Zhengyang Wang, Na Zou, Dinggang Shen, Shuiwang Ji

An Objective for Hierarchical Clustering in Euclidean Space and Its Connection to Bisecting K-means

Yuyan Wang, Benjamin Moseley

Dynamic Network Pruning with Interpretable Layerwise Channel Selection

Yulong Wang, Xiaolu Zhang, Xiaolin Hu, Bo Zhang, Hang Su

Transductive Ensemble Learning for Neural Machine Translation

Yiren Wang, Lijun Wu, Yingce Xia, Tao Qin, ChengXiang Zhai

Federated Latent Dirichlet Allocation: A Local Differential Privacy Based Framework

Yansheng Wang, Yongxin Tong, Dingyuan Shi

Attention-Guide Walk Model in Heterogeneous Information Network for Multi-Style Recommendation Explanation

Xin Wang, Ying Wang, Yunzhi Ling

Multi-Component Graph Convolutional Collaborative Filtering

Xiao Wang, Ruijia Wang, Chuan Shi, Guojie Song, Qingyong Li

Intention Nets: Psychology-Inspired User Choice Behavior Modeling for Next-Basket Prediction

Shoujin Wang, Liang Hu, Yan Wang, Quan Z. Sheng, Mehmet Orgun

Learning from Weak-Label Data: A Deep Forest Expedition

Qian-Wei Wang, Liang Yang, Yu-feng Li

Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling

Qian Wang, Toby Breckon

A Knowledge Transfer Framework for Differentially Private Sparse Learning

Lingxiao Wang, Quanquan Gu

Dual Relation Semi-Supervised Multi-Label Learning

Lichen Wang, Yunyu Liu, Can Qin, Gan Sun, Yun Fu

Differentially Private Learning with Small Public Data

Jun Wang, Zhi-Hua Zhou

Crowdfunding Dynamics Tracking: A Reinforcement Learning Approach

Jun Wang, Hefu Zhang, Qi Liu, Zhen Pan, Hanqing Tao

Reinforcement Learning with Perturbed Rewards

Jingkang Wang, Yang Liu, Bo Li

Logo-2K+: A Large-Scale Logo Dataset for Scalable Logo Classification

Jing Wang, Weiqing Min, Sujuan Hou, Shengnan Ma, Yuanjie Zheng

M-NAS: Meta Neural Architecture Search

Jiaxing Wang, Jiaxiang Wu, Haoli Bai, Jian Cheng

Incorporating Label Embedding and Feature Augmentation for Multi-Dimensional Classification

Haobo Wang, Chen Chen, Weiwei Liu, Ke Chen, Tianlei Hu

Repetitive Reprediction Deep Decipher for Semi-Supervised Learning

Guo-Hua Wang, Jianxin Wu

Adapting to Smoothness: A More Universal Algorithm for Online Convex Optimization

Guanghui Wang, Shiyin Lu, Yao Hu, Lijun Zhang

Neural Cognitive Diagnosis for Intelligent Education Systems

Fei Wang, Qi Liu, Enhong Chen, Zhenya Huang, Yuying Chen

Compact Autoregressive Network

Di Wang, Feiqing Huang, Jingyu Zhao, Guodong Li, Guangjian Tian

Estimating Stochastic Linear Combination of Non-Linear Regressions

Di Wang, Xiangyu Guo, Chaowen Guan, Shi Li, Jinhui Xu

SetRank: A Setwise Bayesian Approach for Collaborative Ranking from Implicit Feedback

Chao Wang, Hengshu Zhu, Chen Zhu, Chuan Qin, Hui Xiong

Learning General Latent-Variable Graphical Models with Predictive Belief Propagation

Borui Wang, Geoffrey Gordon

Robust Self-Weighted Multi-View Projection Clustering

Beilei Wang, Yun Xiao, Zhihui Li, Xuanhong Wang, Xiaojiang Chen

Robust Tensor Decomposition via Orientation Invariant Tubal Nuclear Norms

Andong Wang, CHAO LI, Zhong Jin, Qibin Zhao

Reinforcement Learning Based Meta-Path Discovery in Large-Scale Heterogeneous Information Networks

Guojia Wan, Bo Du, Shirui Pan, Gholameza Haffari

Fast and Efficient Boolean Matrix Factorization by Geometric Segmentation

Changlin Wan, Wennan Chang, Tong Zhao, Mengya Li, Sha Cao

Justification-Based Reliability in Machine Learning

Nurali Virani, Naresh Iyer, Zhaoyuan Yang

Deep Conservative Policy Iteration

Nino Vieillard, Olivier Pietquin, Matthieu Geist

Meta-Learning for Generalized Zero-Shot Learning

Vinay Kumar Verma, Dhanajit Brahma, Piyush Rai

Transfer Learning for Anomaly Detection through Localized and Unsupervised Instance Selection

Vercruyssen Vincent, Meert Wannes, Davis Jesse

Learning to Crawl

Utkarsh Upadhyay, Róbert Busa-Fekete, Wojciech Kotlowski, Dávid Pál, Balázs Szörényi

Order-Free Learning Alleviating Exposure Bias in Multi-Label Classification

Che-Ping Tsai, Hung-yi Lee

Differential Equation Units: Learning Functional Forms of Activation Functions from Data

MohamadAli Torkamani, Shiv Shankar, Amirmohammad Rooshenas, Phillip Wallis

Sanity Checks for Saliency Metrics

Richard Tomsett, Dan Harborne, Supriyo Chakraborty, Prudhvi Gurram, Alun Preece

Network as Regularization for Training Deep Neural Networks: Framework, Model and Performance

Kai Tian, Yi Xu, Jihong Guan, Shuigeng Zhou

Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors

Jayaraman J. Thiagarajan, Bindya Venkatesh, Prasanna Sattigeri, Peer-Timo Bremer

Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression

Tong Teng, Jie Chen, Yehong Zhang, Bryan Kian Hsiang Low

Bi-Objective Continual Learning: Learning ‘New’ While Consolidating ‘Known’

Xiaoyu Tao, Xiaopeng Hong, Xinyuan Chang, Yihong Gong

Discretizing Continuous Action Space for On-Policy Optimization

Yunhao Tang, Shipra Agrawal

Reborn Filters: Pruning Convolutional Neural Networks with Limited Data

Yehui Tang, Shan You, Chang Xu, Jin Han, Chen Qian

Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks

Yehui Tang, Yunhe Wang, Yixing Xu, Boxin Shi, Chao Xu

Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values

Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Charu Aggarwal, Prasenjit Mitra

Parameterized Indexed Value Function for Efficient Exploration in Reinforcement Learning

Tian Tan, Zhihan Xiong, Vikranth R. Dwaracherla

Discriminative Adversarial Domain Adaptation

Hui Tang, Kui Jia

Label Enhancement with Sample Correlations via Low-Rank Representation

Haoyu Tang, Jihua Zhu, Qinghai Zheng, Jun Wang, Shanmin Pang

CGD: Multi-View Clustering via Cross-View Graph Diffusion

Chang Tang, Xinwang Liu, Xinzhong Zhu, En Zhu, Zhigang Luo

Adversarial Transformations for Semi-Supervised Learning

Teppei Suzuki, Ikuro Sato

Revisiting Probability Distribution Assumptions for Information Theoretic Feature Selection

Yuan Sun, Wei Wang, Michael Kirley, Xiaodong Li, Jeffrey Chan

Attentive Experience Replay

Peiquan Sun, Wengang Zhou, Houqiang Li

Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes

Ke Sun, Zhouchen Lin, Zhanxing Zhu

Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning

Jianwen Sun, Tianwei Zhang, Xiaofei Xie, Lei Ma, YAN ZHENG

New Interpretations of Normalization Methods in Deep Learning

Jiacheng Sun, Xiangyong Cao, Hanwen Liang, Weiran Huang, Zewei Chen

Lifelong Spectral Clustering

Gan Sun, Yang Cong, Qianqian Wang, Jun Li, Yun Fu

Learning Efficient Representations for Fake Speech Detection

Nishant Subramani, Delip Rao

Scalable Probabilistic Matrix Factorization with Graph-Based Priors

Jonathan Strahl, Jaakko Peltonen, Hirsohi Mamitsuka, Samuel Kaski

Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance

Vignesh Srinivasan, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima

Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip

Yuxuan Song, Minkai Xu, Lantao Yu, Hao Zhou, Shuo Shao

Mega-Reward: Achieving Human-Level Play without Extrinsic Rewards

Yuhang Song, Jianyi Wang, Thomas Lukasiewicz, Zhenghua Xu, Shangtong Zhang

Bivariate Beta-LSTM

Kyungwoo Song, JoonHo Jang, Seung jae Shin, Il-chul Moon

Aggregated Learning: A Vector-Quantization Approach to Learning Neural Network Classifiers

Masoumeh Soflaei, Hongyu Guo, Ali Al-Bashabsheh, Yongyi Mao, Richong Zhang

Efficient Facial Feature Learning with Wide Ensemble-Based Convolutional Neural Networks

Henrique Siqueira, Sven Magg, Stefan Wermter

Uncertainty-Aware Action Advising for Deep Reinforcement Learning Agents

Felipe Leno Da Silva, Pablo Hernandez-Leal, Bilal Kartal, Matthew E. Taylor

HLHLp: Quantized Neural Networks Training for Reaching Flat Minima in Loss Surface

Sungho Shin, Jinhwan Park, Yoonho Boo, Wonyong Sung

Hierarchically Clustered Representation Learning

Su-Jin Shin, Kyungwoo Song, Il-chul Moon

Morphism-Based Learning for Structured Data

Kilho Shin, Dave Shepard

Block Hankel Tensor ARIMA for Multiple Short Time Series Forecasting

Qiquan Shi, Jiaming Yin, Jiajun Cai, Andrzej Cichocki, Tatsuya Yokota

Deep Message Passing on Sets

Yifeng Shi, Junier Oliva, Marc Niethammer

Loss-Based Attention for Deep Multiple Instance Learning

Xiaoshuang Shi, Fuyong Xing, Yuanpu Xie, Zizhao Zhang, Lei Cui

Quadruply Stochastic Gradient Method for Large Scale Nonlinear Semi-Supervised Ordinal Regression AUC Optimization

Wanli Shi, Bin Gu, Xiang Li, Heng Huang

Deep Time-Stream Framework for Click-through Rate Prediction by Tracking Interest Evolution

Shu-Ting Shi, Wenhao Zheng, Jun Tang, Qing-Guo Chen, Yao Hu

Gamma-Nets: Generalizing Value Estimation over Timescale

Craig Sherstan, Shibhansh Dohare, James MacGlashan, Johannes Günther, Patrick M. Pilarski

Revisiting Image Aesthetic Assessment via Self-Supervised Feature Learning

Kekai Sheng, Weiming Dong, Menglei Chai, Guohui Wang, Peng Zhou

Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference

Jianghao Shen, Yue Wang, Pengfei Xu, Yonggan Fu, Zhangyang Wang

Stable Learning via Sample Reweighting

Zheyan Shen, Peng Cui, Tong Zhang, Kun Kunag

AUC Optimization with a Reject Option

Song-Qing Shen, Bin-Bin Yang, Wei Gao

Transfer Value Iteration Networks

Junyi Shen, Hankz Hankui Zhuo, Jin Xu, Bin Zhong, Sinno Pan