Papers
Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality
Yi Zhang, Orestis Plevrakis, Simon S Du et al.
Belief Propagation Neural Networks
Jonathan Kuck, Shuvam Chakraborty, Hao Tang et al.
Causal Intervention for Weakly-Supervised Semantic Segmentation
Dong Zhang, Hanwang Zhang, Jinhui Tang et al.
Online Agnostic Boosting via Regret Minimization
Nataly Brukhim, Xinyi Chen, Elad Hazan et al.
Rankmax: An Adaptive Projection Alternative to the Softmax Function
Weiwei Kong, Walid Krichene, Nicolas Mayoraz et al.
Towards Playing Full MOBA Games with Deep Reinforcement Learning
Deheng Ye, Guibin Chen, Wen Zhang et al.
Reinforcement Learning with Combinatorial Actions: An Application to Vehicle Routing
Arthur Delarue, Ross Anderson, Christian Tjandraatmadja
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
Kihyuk Sohn, David Berthelot, Nicholas Carlini et al.
Neuron Merging: Compensating for Pruned Neurons
Woojeong Kim, Suhyun Kim, Mincheol Park et al.
Improving Inference for Neural Image Compression
Yibo Yang, Robert Bamler, Stephan Mandt
Exploiting weakly supervised visual patterns to learn from partial annotations
Kaustav Kundu, Joseph Tighe
Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction
Jinheon Baek, Dong Bok Lee, Sung Ju Hwang
Neural Networks with Recurrent Generative Feedback
Yujia Huang, James Gornet, Sihui Dai et al.
Submodular Maximization Through Barrier Functions
Ashwinkumar Badanidiyuru, Amin Karbasi, Ehsan Kazemi et al.
What is being transferred in transfer learning?
Behnam Neyshabur, Hanie Sedghi, Chiyuan Zhang
One-bit Supervision for Image Classification
Hengtong Hu, Lingxi Xie, Zewei Du et al.
Deep Relational Topic Modeling via Graph Poisson Gamma Belief Network
Chaojie Wang, Hao Zhang, Bo Chen et al.
Learning Manifold Implicitly via Explicit Heat-Kernel Learning
Yufan Zhou, Changyou Chen, Jinhui Xu
Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee
Jincheng Bai, Qifan Song, Guang Cheng
Simultaneous Preference and Metric Learning from Paired Comparisons
Austin Xu, Mark Davenport
Flows for simultaneous manifold learning and density estimation
Johann Brehmer, Kyle Cranmer
Deterministic Approximation for Submodular Maximization over a Matroid in Nearly Linear Time
Kai Han, zongmai Cao, Shuang Cui et al.
Generalised Bayesian Filtering via Sequential Monte Carlo
Ayman Boustati, Omer Deniz Akyildiz, Theodoros Damoulas et al.
On the Value of Out-of-Distribution Testing: An Example of Goodhart's Law
Damien Teney, Ehsan Abbasnejad, Kushal Kafle et al.
A Closer Look at the Training Strategy for Modern Meta-Learning
JIAXIN CHEN, Xiao-Ming Wu, Yanke Li et al.