Papers
Stochastic Gradient Monomial Gamma Sampler
Yizhe Zhang, Changyou Chen, Zhe Gan et al.
Continual Learning Through Synaptic Intelligence
Friedemann Zenke, Ben Poole, Surya Ganguli
Canopy Fast Sampling with Cover Trees
Manzil Zaheer, Satwik Kottur, Amr Ahmed et al.
Latent LSTM Allocation: Joint Clustering and Non-Linear Dynamic Modeling of Sequence Data
Manzil Zaheer, Amr Ahmed, Alexander J. Smola
Combined Group and Exclusive Sparsity for Deep Neural Networks
Jaehong Yoon, Sung Ju Hwang
Latent Feature Lasso
Ian En-Hsu Yen, Wei-Cheng Lee, Sung-En Chang et al.
A Simulated Annealing Based Inexact Oracle for Wasserstein Loss Minimization
Jianbo Ye, James Z. Wang, Jia Li
Approximate Newton Methods and Their Local Convergence
Haishan Ye, Luo Luo, Zhihua Zhang
Scalable Bayesian Rule Lists
Hongyu Yang, Cynthia Rudin, Margo Seltzer
Sparse + Group-Sparse Dirty Models: Statistical Guarantees without Unreasonable Conditions and a Case for Non-Convexity
Eunho Yang, Aurélie C. Lozano
A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates
Tianbao Yang, Qihang Lin, Lijun Zhang
Tensor-Train Recurrent Neural Networks for Video Classification
Yinchong Yang, Denis Krompass, Volker Tresp
Improved Variational Autoencoders for Text Modeling using Dilated Convolutions
Zichao Yang, Zhiting Hu, Ruslan Salakhutdinov et al.
On The Projection Operator to A Three-view Cardinality Constrained Set
Haichuan Yang, Shupeng Gui, Chuyang Ke et al.
Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering
Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos et al.
High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation
Zhuoran Yang, Krishnakumar Balasubramanian, Han Liu
Adaptive Consensus ADMM for Distributed Optimization
Zheng Xu, Gavin Taylor, Hao Li et al.
Learning Hawkes Processes from Short Doubly-Censored Event Sequences
Hongteng Xu, Dixin Luo, Hongyuan Zha
Stochastic Convex Optimization: Faster Local Growth Implies Faster Global Convergence
Yi Xu, Qihang Lin, Tianbao Yang
Uncorrelation and Evenness: a New Diversity-Promoting Regularizer
Pengtao Xie, Aarti Singh, Eric P. Xing
Learning Latent Space Models with Angular Constraints
Pengtao Xie, Yuntian Deng, Yi Zhou et al.
Dual Supervised Learning
Yingce Xia, Tao Qin, Wei Chen et al.
A Unified View of Multi-Label Performance Measures
Xi-Zhu Wu, Zhi-Hua Zhou
Tensor Belief Propagation
Andrew Wrigley, Wee Sun Lee, Nan Ye
Exact Inference for Integer Latent-Variable Models
Kevin Winner, Debora Sujono, Dan Sheldon