AAAI 2019

1,341 papers

Video Inpainting by Jointly Learning Temporal Structure and Spatial Details

Chuan Wang, Haibin Huang, Xiaoguang Han, Jue Wang

CAMO: A Collaborative Ranking Method for Content Based Recommendation

Chengwei Wang, Tengfei Zhou, Chen Chen, Tianlei Hu, Gang Chen

Robust Anomaly Detection in Videos Using Multilevel Representations

Hung Vu, Tu Dinh Nguyen, Trung Le, Wei Luo, Dinh Phung

Automatic Bayesian Density Analysis

Antonio Vergari, Alejandro Molina, Robert Peharz, Zoubin Ghahramani, Kristian Kersting

Predicting Urban Dispersal Events: A Two-Stage Framework through Deep Survival Analysis on Mobility Data

Amin Vahedian, Xun Zhou, Ling Tong, W. Nick Street, Yanhua Li

Improving GAN with Neighbors Embedding and Gradient Matching

Ngoc-Trung Tran, Tuan-Anh Bui, Ngai-Man Cheung

Learning Triggers for Heterogeneous Treatment Effects

Christopher Tran, Elena Zheleva

Natural Option Critic

Saket Tiwari, Philip S. Thomas

Learning Competitive and Discriminative Reconstructions for Anomaly Detection

Kai Tian, Shuigeng Zhou, Jianping Fan, Jihong Guan

A Non–Convex Optimization Approach to Correlation Clustering

Erik Thiel, Morteza Haghir Chehreghani, Devdatt Dubhashi

Clipped Matrix Completion: A Remedy for Ceiling Effects

Takeshi Teshima, Miao Xu, Issei Sato, Masashi Sugiyama

Holographic Factorization Machines for Recommendation

Yi Tay, SHUAI ZHANG, Anh Tuan Luu, Siu Cheung Hui, Lina Yao

Optimization of Hierarchical Regression Model with Application to Optimizing Multi-Response Regression K-ary Trees

Pooya Tavallali, Peyman Tavallali, Mukesh Singhal

A Radical-Aware Attention-Based Model for Chinese Text Classification

Hanqing Tao, Shiwei Tong, Hongke Zhao, Tong Xu, Binbin Jin

Self-Paced Active Learning: Query the Right Thing at the Right Time

Ying-Peng Tang, Sheng-jun Huang

An Integral Tag Recommendation Model for Textual Content

Shijie Tang, Yuan Yao, Suwei Zhang, Feng Xu, Tianxiao Gu

Cross-View Local Structure Preserved Diversity and Consensus Learning for Multi-View Unsupervised Feature Selection

Chang Tang, Xinzhong Zhu, Xinwang Liu, Lizhe Wang

Refining Coarse-Grained Spatial Data Using Auxiliary Spatial Data Sets with Various Granularities

Yusuke Tanaka, Tomoharu Iwata, Toshiyuki Tanaka, Takeshi Kurashima, Maya Okawa

Coreset Stochastic Variance-Reduced Gradient with Application to Optimal Margin Distribution Machine

Zhi-Hao Tan, Teng Zhang, Wei Wang

Character n-Gram Embeddings to Improve RNN Language Models

Sho Takase, Jun Suzuki, Masaaki Nagata

Variational Autoencoder with Implicit Optimal Priors

Hiroshi Takahashi, Tomoharu Iwata, Yuki Yamanaka, Masanori Yamada, Satoshi Yagi

Matrix Completion for Graph-Based Deep Semi-Supervised Learning

Fariborz Taherkhani, Hadi Kazemi, Nasser M. Nasrabadi

Learning Vine Copula Models for Synthetic Data Generation

Yi Sun, Alfredo Cuesta-Infante, Kalyan Veeramachaneni

Network Structure and Transfer Behaviors Embedding via Deep Prediction Model

Xin Sun, Zenghui Song, Junyu Dong, Yongbo Yu, Claudia Plant

Non-Ergodic Convergence Analysis of Heavy-Ball Algorithms

Tao Sun, Penghang Yin, Dongsheng Li, Chun Huang, Lei Guan

Multi-Precision Quantized Neural Networks via Encoding Decomposition of {-1,+1}

Qigong Sun, Fanhua Shang, Kang Yang, Xiufang Li, Yan Ren

Partial Multi-Label Learning by Low-Rank and Sparse Decomposition

Lijuan Sun, Songhe Feng, Tao Wang, Congyan Lang, Yi Jin

Soft Facial Landmark Detection by Label Distribution Learning

Kai Su, Xin Geng

On the Persistence of Clustering Solutions and True Number of Clusters in a Dataset

Amber Srivastava, Mayank Baranwal, Srinivasa Salapaka

Diversity-Driven Extensible Hierarchical Reinforcement Learning

Yuhang Song, Jianyi Wang, Thomas Lukasiewicz, Zhenghua Xu, Mai Xu

Hierarchical Context Enabled Recurrent Neural Network for Recommendation

Kyungwoo Song, Mingi Ji, Sungrae Park, Il-chul Moon

Composable Modular Reinforcement Learning

Christopher Simpkins, Charles Isbell

Safe Policy Improvement with Baseline Bootstrapping in Factored Environments

Thiago D. Simão, Matthijs T. J. Spaan

Unsupervised Transfer Learning for Spoken Language Understanding in Intelligent Agents

Aditya Siddhant, Anuj Goyal, Angeliki Metallinou

Transferable Curriculum for Weakly-Supervised Domain Adaptation

Yang Shu, ZHANGJIE CAO, Mingsheng Long, Jianmin Wang

Sensitivity Analysis of Deep Neural Networks

Hai Shu, Hongtu Zhu

Evaluating Recommender System Stability with Influence-Guided Fuzzing

David Shriver, Sebastian Elbaum, Matthew B. Dwyer, David S. Rosenblum

Label Embedding with Partial Heterogeneous Contexts

Yaxin Shi, Donna Xu, Yuangang Pan, Ivor W. Tsang, Shirui Pan

Sublinear Time Numerical Linear Algebra for Structured Matrices

Xiaofei Shi, David P. Woodruff

Automatic Code Review by Learning the Revision of Source Code

Shu-Ting Shi, Ming Li, David Lo, Ferdian Thung, Xuan Huo

Virtual-Taobao: Virtualizing Real-World Online Retail Environment for Reinforcement Learning

Jing-Cheng Shi, Yang Yu, Qing Da, Shi-Yong Chen, An-Xiang Zeng

Multi-View Anomaly Detection: Neighborhood in Locality Matters

Xiang-Rong Sheng, De-Chuan Zhan, Su Lu, Yuan Jiang

MEAL: Multi-Model Ensemble via Adversarial Learning

Zhiqiang Shen, Zhankui He, Xiangyang Xue

Geometric Hawkes Processes with Graph Convolutional Recurrent Neural Networks

Jin Shang, Mingxuan Sun

Sparse Reject Option Classifier Using Successive Linear Programming

Kulin Shah, Naresh Manwani

Unsupervised Learning with Contrastive Latent Variable Models

Kristen A. Severson, Soumya Ghosh, Kenney Ng

Congestion Graphs for Automated Time Predictions

Arik Senderovich, J. Christopher Beck, Avigdor Gal, Matthias Weidlich

Granger-Causal Attentive Mixtures of Experts: Learning Important Features with Neural Networks

Patrick Schwab, Djordje Miladinovic, Walter Karlen

Covariate Shift Adaptation on Learning from Positive and Unlabeled Data

Tomoya Sakai, Nobuyuki Shimizu

How Many Pairwise Preferences Do We Need to Rank a Graph Consistently?

Aadirupa Saha, Rakesh Shivanna, Chiranjib Bhattacharyya

Latent Multi-Task Architecture Learning

Sebastian Ruder, Joachim Bingel, Isabelle Augenstein, Anders Søgaard

Devil in the Details: Towards Accurate Single and Multiple Human Parsing

Tao Ruan, Ting Liu, Zilong Huang, Yunchao Wei, Shikui Wei

RepeatNet: A Repeat Aware Neural Recommendation Machine for Session-Based Recommendation

Pengjie Ren, Zhumin Chen, Jing Li, Zhaochun Ren, Jun Ma

Deep Recurrent Survival Analysis

Kan Ren, Jiarui Qin, Lei Zheng, Zhengyu Yang, Weinan Zhang

On Fair Cost Sharing Games in Machine Learning

Ievgen Redko, Charlotte Laclau

Regularized Evolution for Image Classifier Architecture Search

Esteban Real, Alok Aggarwal, Yanping Huang, Quoc V. Le

Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence

Sathya N. Ravi, Tuan Dinh, Vishnu Suresh Lokhande, Vikas Singh

Training Complex Models with Multi-Task Weak Supervision

Alexander Ratner, Braden Hancock, Jared Dunnmon, Frederic Sala, Shreyash Pandey

Nearest-Neighbour-Induced Isolation Similarity and Its Impact on Density-Based Clustering

Xiaoyu Qin, Kai Ming Ting, Ye Zhu, Vincent CS Lee

Composite Binary Decomposition Networks

You Qiaoben, Zheng Wang, Jianguo Li, Yinpeng Dong, Yu-Gang Jiang

Robust Optimization over Multiple Domains

Qi Qian, Shenghuo Zhu, Jiasheng Tang, Rong Jin, Baigui Sun

Learning to Solve NP-Complete Problems: A Graph Neural Network for Decision TSP

Marcelo Prates, Pedro H. C. Avelar, Henrique Lemos, Luis C. Lamb, Moshe Y. Vardi

Interpretable Preference Learning: A Game Theoretic Framework for Large Margin On-Line Feature and Rule Learning

Mirko Polato, Fabio Aiolli

Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets

M. Peréz-Ortiz, P. Tiňo, R. Mantiuk, C. Hervás-Martínez

Trainable Undersampling for Class-Imbalance Learning

Minlong Peng, Qi Zhang, Xiaoyu Xing, Tao Gui, Xuanjing Huang

Adversarial Dropout for Recurrent Neural Networks

Sungrae Park, Kyungwoo Song, Mingi Ji, Wonsung Lee, Il-chul Moon

On Reinforcement Learning for Full-Length Game of StarCraft

Zhen-Jia Pang, Ruo-Ze Liu, Zhou-Yu Meng, Yi Zhang, Yang Yu

Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition

Yu Pan, Jing Xu, Maolin Wang, Jinmian Ye, Fei Wang

Policy Optimization with Model-Based Explorations

Feiyang Pan, Qingpeng Cai, An-Xiang Zeng, Chun-Xiang Pan, Qing Da

Non-Parametric Transformation Networks for Learning General Invariances from Data

Dipan K. Pal, Marios Savvides

Determinantal Reinforcement Learning

Takayuki Osogami, Rudy Raymond

Biologically Motivated Algorithms for Propagating Local Target Representations

Alexander G. Ororbia, Ankur Mali

Multigrid Backprojection Super–Resolution and Deep Filter Visualization

Pablo Navarrete Michelini, Hanwen Liu, Dan Zhu

Efficient Counterfactual Learning from Bandit Feedback

Yusuke Narita, Shota Yasui, Kohei Yata

Number Sequence Prediction Problems for Evaluating Computational Powers of Neural Networks

Hyoungwook Nam, Segwang Kim, Kyomin Jung

Subspace Selection via DR-Submodular Maximization on Lattices

So Nakashima, Takanori Maehara

ClusterGAN: Latent Space Clustering in Generative Adversarial Networks

Sudipto Mukherjee, Himanshu Asnani, Eugene Lin, Sreeram Kannan

Weisfeiler and Leman Go Neural: Higher-Order Graph Neural Networks

Christopher Morris, Martin Ritzert, Matthias Fey, William L. Hamilton, Jan Eric Lenssen

Cogra: Concept-Drift-Aware Stochastic Gradient Descent for Time-Series Forecasting

Kohei Miyaguchi, Hiroshi Kajino

A Probabilistic Derivation of LASSO and L12-Norm Feature Selections

Di Ming, Chris Ding, Feiping Nie

A Two-Stream Mutual Attention Network for Semi-Supervised Biomedical Segmentation with Noisy Labels

Shaobo Min, Xuejin Chen, Zheng-Jun Zha, Feng Wu, Yongdong Zhang

Cost-Sensitive Learning to Rank

Ryan McBride, Ke Wang, Zhouyang Ren, Wenyuan Li

Towards Better Interpretability in Deep Q-Networks

Raghuram Mandyam Annasamy, Katia Sycara

DyS: A Framework for Mixture Models in Quantification

André Maletzke, Denis dos Reis, Everton Cherman, Gustavo Batista

A Distillation Approach to Data Efficient Individual Treatment Effect Estimation

Maggie Makar, Adith Swaminathan, Emre Kıcıman

The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure

Saeed Mahloujifar, Dimitrios I. Diochnos, Mohammad Mahmoody

Complex Unitary Recurrent Neural Networks Using Scaled Cayley Transform

Kehelwala D. G. Maduranga, Kyle E. Helfrich, Qiang Ye

LabelForest: Non-Parametric Semi-Supervised Learning for Activity Recognition

Yuchao Ma, Hassan Ghasemzadeh

State-Augmentation Transformations for Risk-Sensitive Reinforcement Learning

Shuai Ma, Jia Yuan Yu

A Comparative Analysis of Expected and Distributional Reinforcement Learning

Clare Lyle, Marc G. Bellemare, Pablo Samuel Castro

Distributed PageRank Computation: An Improved Theoretical Study

Siqiang Luo

Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions

Simon Luo, Mahito Sugiyama

Robust Metric Learning on Grassmann Manifolds with Generalization Guarantees

Lei Luo, Jie Xu, Cheng Deng, Heng Huang

Orthogonality-Promoting Dictionary Learning via Bayesian Inference

Lei Luo, Jie Xu, Cheng Deng, Heng Huang

Scaling-Up Split-Merge MCMC with Locality Sensitive Sampling (LSS)

Chen Luo, Anshumali Shrivastava

Relation Structure-Aware Heterogeneous Information Network Embedding

Yuanfu Lu, Chuan Shi, Linmei Hu, Zhiyuan Liu

Block Belief Propagation for Parameter Learning in Markov Random Fields

You Lu, Zhiyuan Liu, Bert Huang

Super Sparse Convolutional Neural Networks

Yao Lu, Guangming Lu, Bob Zhang, Yuanrong Xu, Jinxing Li

Guiding the One-to-One Mapping in CycleGAN via Optimal Transport

Guansong Lu, Zhiming Zhou, Yuxuan Song, Kan Ren, Yong Yu

GeniePath: Graph Neural Networks with Adaptive Receptive Paths

Ziqi Liu, Chaochao Chen, Longfei Li, Jun Zhou, Xiaolong Li