AAAI 2019

1,341 papers

Active Sampling for Open-Set Classification without Initial Annotation

Zhao-Yang Liu, Sheng-jun Huang

Adaptive Sparse Confidence-Weighted Learning for Online Feature Selection

Yanbin Liu, Yan Yan, Ling Chen, Yahong Han, Yi Yang

Ranking-Based Deep Cross-Modal Hashing

Xuanwu Liu, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Yazhou Ren

Efficient and Effective Incomplete Multi-View Clustering

Xinwang Liu, Xinzhong Zhu, Miaomiao Li, Chang Tang, En Zhu

The Utility of Sparse Representations for Control in Reinforcement Learning

Vincent Liu, Raksha Kumaraswamy, Lei Le, Martha White

A Bandit Approach to Maximum Inner Product Search

Rui Liu, Tianyi Wu, Barzan Mozafari

A Theoretically Guaranteed Deep Optimization Framework for Robust Compressive Sensing MRI

Risheng Liu, Yuxi Zhang, Shichao Cheng, Xin Fan, Zhongxuan Luo

Learning Multi-Task Communication with Message Passing for Sequence Learning

Pengfei Liu, Jie Fu, Yue Dong, Xipeng Qiu, Jackie Chi Kit CHEUNG

Trust Region Evolution Strategies

Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin

Scale Invariant Fully Convolutional Network: Detecting Hands Efficiently

Dan Liu, Dawei Du, Libo Zhang, Tiejian Luo, Yanjun Wu

Near-Neighbor Methods in Random Preference Completion

Ao Liu, Qiong Wu, Zhenming Liu, Lirong Xia

Learning Plackett-Luce Mixtures from Partial Preferences

Ao Liu, Zhibing Zhao, Chao Liao, Pinyan Lu, Lirong Xia

MFPCA: Multiscale Functional Principal Component Analysis

Zhenhua Lin, Hongtu Zhu

Which Factorization Machine Modeling Is Better: A Theoretical Answer with Optimal Guarantee

Ming Lin, Shuang Qiu, Jieping Ye, Xiaomin Song, Qi Qian

Non-Compensatory Psychological Models for Recommender Systems

CHEN LIN, Xiaolin Shen, Si Chen, Muhua Zhu, Yanghua Xiao

Evolutionary Manytasking Optimization Based on Symbiosis in Biocoenosis

Rung-Tzuo Liaw, Chuan-Kang Ting

CircConv: A Structured Convolution with Low Complexity

Siyu Liao, Bo Yuan

Learning Logistic Circuits

Yitao Liang, Guy Van den Broeck

Collaborative, Dynamic and Diversified User Profiling

Shangsong Liang

SepNE: Bringing Separability to Network Embedding

Ziyao Li, Liang Zhang, Guojie Song

Exploiting Coarse-to-Fine Task Transfer for Aspect-Level Sentiment Classification

Zheng Li, Ying Wei, Yu Zhang, Xiang Zhang, Xin Li

Learning Disentangled Representation with Pairwise Independence

Zejian Li, Yongchuan Tang, Wei Li, Yongxing He

Towards Automated Semi-Supervised Learning

Yu-feng Li, Hai Wang, Tong Wei, Wei-Wei Tu

Learning Adaptive Random Features

Yanjun Li, Kai Zhang, Jun Wang, Sanjiv Kumar

Spectral Clustering in Heterogeneous Information Networks

Xiang Li, Ben Kao, Zhaochun Ren, Dawei Yin

Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient

Shihui Li, Yi Wu, Xinyue Cui, Honghua Dong, Fei Fang

Sign-Full Random Projections

Ping Li

X-DMM: Fast and Scalable Model Based Text Clustering

Linwei Li, Liangchen Guo, Zhenying He, Yinan Jing, X. Sean Wang

From Zero-Shot Learning to Cold-Start Recommendation

Jingjing Li, Mengmeng Jing, Ke Lu, LEI ZHU, Yang Yang

Lifted Proximal Operator Machines

Jia Li, Cong Fang, Zhouchen Lin

Communication-Efficient Stochastic Gradient MCMC for Neural Networks

Chunyuan Li, Changyou Chen, Yunchen Pu, Ricardo Henao, Lawrence Carin

Structural Causal Bandits with Non-Manipulable Variables

Sanghack Lee, Elias Bareinboim

Understanding Learned Models by Identifying Important Features at the Right Resolution

Kyubin Lee, Akshay Sood, Mark Craven

Gradient-Based Inference for Networks with Output Constraints

Jay Yoon Lee, Sanket Vaibhav Mehta, Michael Wick, Jean-Baptiste Tristan, Jaime Carbonell

Accurate and Interpretable Factorization Machines

Liang Lan, Yu Geng

TransConv: Relationship Embedding in Social Networks

Yi-Yu Lai, Jennifer Neville, Dan Goldwasser

Unsupervised Domain Adaptation Based on Source-Guided Discrepancy

Seiichi Kuroki, Nontawat Charoenphakdee, Han Bao, Junya Honda, Issei Sato

Multi-Source Neural Variational Inference

Richard Kurle, Stephan Günnemann, Patrick van der Smagt

Unsupervised Domain Adaptation by Matching Distributions Based on the Maximum Mean Discrepancy via Unilateral Transformations

Atsutoshi Kumagai, Tomoharu Iwata

On-Line Learning of Linear Dynamical Systems: Exponential Forgetting in Kalman Filters

Mark Kozdoba, Jakub Marecek, Tigran Tchrakian, Shie Mannor

Active Generative Adversarial Network for Image Classification

Quan Kong, Bin Tong, Martin Klinkigt, Yuki Watanabe, Naoto Akira

Exploiting Class Learnability in Noisy Data

Matthew Klawonn, Eric Heim, James Hendler

Mixture of Expert/Imitator Networks: Scalable Semi-Supervised Learning Framework

Shun Kiyono, Jun Suzuki, Kentaro Inui

Guided Dropout

Rohit Keshari, Richa Singh, Mayank Vatsa

Zhao Kang, Yiwei Lu, Yuanzhang Su, Changsheng Li, Zenglin Xu

Dimension-Free Error Bounds from Random Projections

Ata Kaban

Precision-Recall versus Accuracy and the Role of Large Data Sets

Brendan Juba, Hai S. Le

DoPAMINE: Double-Sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling

Sunghwan Joo, Sungmin Cha, Taesup Moon

Estimating the Days to Success of Campaigns in Crowdfunding: A Deep Survival Perspective

Binbin Jin, Hongke Zhao, Enhong Chen, Qi Liu, Yong Ge

SCFont: Structure-Guided Chinese Font Generation via Deep Stacked Networks

Yue Jiang, Zhouhui Lian, Yingmin Tang, Jianguo Xiao

Gaussian-Induced Convolution for Graphs

Jiatao Jiang, Zhen Cui, Chunyan Xu, Jian Yang

Non-Asymptotic Uniform Rates of Consistency for k-NN Regression

Heinrich Jiang

Fast Incremental SVDD Learning Algorithm with the Gaussian Kernel

Hansi Jiang, Haoyu Wang, Wenhao Hu, Deovrat Kakde, Arin Chaudhuri

Joint Semi-Supervised Feature Selection and Classification through Bayesian Approach

Bingbing Jiang, Xingyu Wu, Kui Yu, Huanhuan Chen

Multi-Dimensional Classification via kNN Feature Augmentation

Bin-Bin Jia, Min-ling Zhang

Tile2Vec: Unsupervised Representation Learning for Spatially Distributed Data

Neal Jean, Sherrie Wang, Anshul Samar, George Azzari, David Lobell

Classification with Costly Features Using Deep Reinforcement Learning

Jaromír Janisch, Tomas Pevny, Viliam Lisy

Model-Free IRL Using Maximum Likelihood Estimation

Vinamra Jain, Prashant Doshi, Bikramjit Banerjee

Meta-Descent for Online, Continual Prediction

Andrew Jacobsen, Matthew Schlegel, Cameron Linke, Thomas Degris, Adam White

Neural Collective Graphical Models for Estimating Spatio-Temporal Population Flow from Aggregated Data

Tomoharu Iwata, Hitoshi Shimizu

TAPAS: Train-Less Accuracy Predictor for Architecture Search

R. Istrate, F. Scheidegger, G. Mariani, D. Nikolopoulos, C. Bekas

Estimating the Causal Effect from Partially Observed Time Series

Akane Iseki, Yusuke Mukuta, Yoshitaka Ushiku, Tatsuya Harada

Complex Moment-Based Supervised Eigenmap for Dimensionality Reduction

Akira Imakura, Momo Matsuda, Xiucai Ye, Tetsuya Sakurai

Tensorial Change Analysis Using Probabilistic Tensor Regression

Tsuyoshi Ide

Inter-Class Angular Loss for Convolutional Neural Networks

Le Hui, Xiang Li, Chen Gong, Meng Fang, Joey Tianyi Zhou

Manifold-Valued Image Generation with Wasserstein Generative Adversarial Nets

Zhiwu Huang, Jiqing Wu, Luc Van Gool

Large-Scale Heterogeneous Feature Embedding

Xiao Huang, Qingquan Song, Fan Yang, Xia Hu

Bootstrap Estimated Uncertainty of the Environment Model for Model-Based Reinforcement Learning

Wenzhen Huang, Junge Zhang, Kaiqi Huang

Efficient Identification of Approximate Best Configuration of Training in Large Datasets

Silu Huang, Chi Wang, Bolin Ding, Surajit Chaudhuri

Efficient Quantization for Neural Networks with Binary Weights and Low Bitwidth Activations

Kun Huang, Bingbing Ni, Xiaokang Yang

Multi-Fidelity Automatic Hyper-Parameter Tuning via Transfer Series Expansion

Yi-Qi Hu, Yang Yu, Wei-Wei Tu, Qiang Yang, Yuqiang Chen

One-Pass Incomplete Multi-View Clustering

Menglei Hu, Songcan Chen

HERS: Modeling Influential Contexts with Heterogeneous Relations for Sparse and Cold-Start Recommendation

Liang Hu, Songlei Jian, Longbing Cao, Zhiping Gu, Qingkui Chen

Learning to Adaptively Scale Recurrent Neural Networks

Hao Hu, Liqiang Wang, Guo-Jun Qi

Learning Anytime Predictions in Neural Networks via Adaptive Loss Balancing

Hanzhang Hu, Debadeepta Dey, Martial Hebert, J. Andrew Bagnell

Interaction-Aware Factorization Machines for Recommender Systems

Fuxing Hong, Dongbo Huang, Ge Chen

Multi-Task Deep Reinforcement Learning with PopArt

Matteo Hessel, Hubert Soyer, Lasse Espeholt, Wojciech Czarnecki, Simon Schmitt

The SpectACl of Nonconvex Clustering: A Spectral Approach to Density-Based Clustering

Sibylle Hess, Wouter Duivesteijn, Philipp Honysz, Katharina Morik

Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons

Byeongho Heo, Minsik Lee, Sangdoo Yun, Jin Young Choi

Knowledge Distillation with Adversarial Samples Supporting Decision Boundary

Byeongho Heo, Minsik Lee, Sangdoo Yun, Jin Young Choi

Efficient and Scalable Multi-Task Regression on Massive Number of Tasks

Xiao He, Francesco Alesiani, Ammar Shaker

Temporal Anomaly Detection: Calibrating the Surprise

Eyal Gutflaish, Aryeh Kontorovich, Sivan Sabato, Ofer Biller, Oded Sofer

Distributional Semantics Meets Multi-Label Learning

Vivek Gupta, Rahul Wadbude, Nagarajan Natarajan, Harish Karnick, Prateek Jain

Hybrid Reinforcement Learning with Expert State Sequences

Xiaoxiao Guo, Shiyu Chang, Mo Yu, Gerald Tesauro, Murray Campbell

Smooth Deep Image Generator from Noises

Tianyu Guo, Chang Xu, Boxin Shi, Chao Xu, Dacheng Tao

Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input

Junliang Guo, Xu Tan, Di He, Tao Qin, Linli Xu

MixUp as Locally Linear Out-of-Manifold Regularization

Hongyu Guo, Yongyi Mao, Richong Zhang

AFS: An Attention-Based Mechanism for Supervised Feature Selection

Ning Gui, Danni Ge, Ziyin Hu

Scalable and Efficient Pairwise Learning to Achieve Statistical Accuracy

Bin Gu, Zhouyuan Huo, Heng Huang

Using Benson’s Algorithm for Regularization Parameter Tracking

Joachim Giesen, Sӧren Laue, Andreas Lӧhne, Christopher Schneider

Interpretation of Neural Networks Is Fragile

Amirata Ghorbani, Abubakar Abid, James Zou

Eliminating Latent Discrimination: Train Then Mask

Soheil Ghili, Ehsan Kazemi, Amin Karbasi

Counting and Sampling from Markov Equivalent DAGs Using Clique Trees

AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash, Kun Zhang

Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting

Xu Geng, Yaguang Li, Leye Wang, Lingyu Zhang, Qiang Yang

Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift

Carles Gelada, Marc G. Bellemare

Incomplete Label Multi-Task Deep Learning for Spatio-Temporal Event Subtype Forecasting

Yuyang Gao, Liang Zhao, Lingfei Wu, Yanfang Ye, Hui Xiong

Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds

Tingran Gao, Shahab Asoodeh, Yi Huang, James Evans

Explainable Recommendation through Attentive Multi-View Learning

Jingyue Gao, Xiting Wang, Yasha Wang, Xing Xie

Towards Reliable Learning for High Stakes Applications

Jinyang Gao, Junjie Yao, Yingxia Shao

Bayesian Posterior Approximation via Greedy Particle Optimization

Futoshi Futami, Zhenghang Cui, Issei Sato, Masashi Sugiyama