Papers
Fast and Efficient Boolean Matrix Factorization by Geometric Segmentation
Changlin Wan, Wennan Chang, Tong Zhao et al.
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, Robert Busa-Fekete, Wojciech Kotlowski et al.
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 et al.
Sanity Checks for Saliency Metrics
Richard Tomsett, Dan Harborne, Supriyo Chakraborty et al.
Network as Regularization for Training Deep Neural Networks: Framework, Model and Performance
Kai Tian, Yi Xu, Jihong Guan et al.
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors
Jayaraman J. Thiagarajan, Bindya Venkatesh, Prasanna Sattigeri et al.
Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression
Tong Teng, Jie Chen, Yehong Zhang et al.
Bi-Objective Continual Learning: Learning ‘New’ While Consolidating ‘Known’
Xiaoyu Tao, Xiaopeng Hong, Xinyuan Chang et al.
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 et al.
Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks
Yehui Tang, Yunhe Wang, Yixing Xu et al.
Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values
Xianfeng Tang, Huaxiu Yao, Yiwei Sun et al.
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 et al.
CGD: Multi-View Clustering via Cross-View Graph Diffusion
Chang Tang, Xinwang Liu, Xinzhong Zhu et al.
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 et al.
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