Papers
Bias and Generalization in Deep Generative Models: An Empirical Study
Shengjia Zhao, Hongyu Ren, Arianna Yuan et al.
Bilevel Distance Metric Learning for Robust Image Recognition
Jie Xu, Lei Luo, Cheng Deng et al.
Bilevel learning of the Group Lasso structure
Jordan Frecon, Saverio Salzo, Massimiliano Pontil
Bilinear Attention Networks
Jin-Hwa Kim, Jaehyun Jun, Byoung-Tak Zhang
Binary Classification from Positive-Confidence Data
Takashi Ishida, Gang Niu, Masashi Sugiyama
Binary Rating Estimation with Graph Side Information
Kwangjun Ahn, Kangwook Lee, Hyunseung Cha et al.
BinGAN: Learning Compact Binary Descriptors with a Regularized GAN
Maciej Zieba, Piotr Semberecki, Tarek El-Gaaly et al.
Bipartite Stochastic Block Models with Tiny Clusters
Stefan Neumann
Blind Deconvolutional Phase Retrieval via Convex Programming
Ali Ahmed, Alireza Aghasi, Paul Hand
Blockwise Parallel Decoding for Deep Autoregressive Models
Mitchell Stern, Noam Shazeer, Jakob Uszkoreit
BML: A High-performance, Low-cost Gradient Synchronization Algorithm for DML Training
Songtao Wang, Dan Li, Yang Cheng et al.
Boolean Decision Rules via Column Generation
Sanjeeb Dash, Oktay Gunluk, Dennis Wei
Boosted Sparse and Low-Rank Tensor Regression
Lifang He, Kun Chen, Wanwan Xu et al.
Boosting Black Box Variational Inference
Francesco Locatello, Gideon Dresdner, Rajiv Khanna et al.
Bounded-Loss Private Prediction Markets
Rafael Frongillo, Bo Waggoner
BourGAN: Generative Networks with Metric Embeddings
Chang Xiao, Peilin Zhong, Changxi Zheng
Breaking the Activation Function Bottleneck through Adaptive Parameterization
Sebastian Flennerhag, Hujun Yin, John Keane et al.
Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation
Qiang Liu, Lihong Li, Ziyang Tang et al.
Breaking the Span Assumption Yields Fast Finite-Sum Minimization
Robert Hannah, Yanli Liu, Daniel O'Connor et al.
BRITS: Bidirectional Recurrent Imputation for Time Series
Wei Cao, Dong Wang, Jian Li et al.
BRUNO: A Deep Recurrent Model for Exchangeable Data
Iryna Korshunova, Jonas Degrave, Ferenc Huszar et al.
But How Does It Work in Theory? Linear SVM with Random Features
Yitong Sun, Anna Gilbert, Ambuj Tewari
Byzantine Stochastic Gradient Descent
Dan Alistarh, Zeyuan Allen-Zhu, Jerry Li
Can We Gain More from Orthogonality Regularizations in Training Deep Networks?
Nitin Bansal, Xiaohan Chen, Zhangyang Wang
CapProNet: Deep Feature Learning via Orthogonal Projections onto Capsule Subspaces
Liheng Zhang, Marzieh Edraki, Guo-Jun Qi