Papers
Stochastic Adaptive Quasi-Newton Methods for Minimizing Expected Values
Chaoxu Zhou, Wenbo Gao, Donald Goldfarb
Recovery Guarantees for One-hidden-layer Neural Networks
Kai Zhong, Zhao Song, Prateek Jain et al.
Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible
Kai Zheng, Wenlong Mou, Liwei Wang
Asynchronous Stochastic Gradient Descent with Delay Compensation
Shuxin Zheng, Qi Meng, Taifeng Wang et al.
Follow the Moving Leader in Deep Learning
Shuai Zheng, James T. Kwok
Learning Sleep Stages from Radio Signals: A Conditional Adversarial Architecture
Mingmin Zhao, Shichao Yue, Dina Katabi et al.
Learning Hierarchical Features from Deep Generative Models
Shengjia Zhao, Jiaming Song, Stefano Ermon
Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank
Liang Zhao, Siyu Liao, Yanzhi Wang et al.
Leveraging Node Attributes for Incomplete Relational Data
He Zhao, Lan Du, Wray Buntine
Multi-Class Optimal Margin Distribution Machine
Teng Zhang, Zhi-Hua Zhou
Projection-free Distributed Online Learning in Networks
Wenpeng Zhang, Peilin Zhao, Wenwu Zhu et al.
Convexified Convolutional Neural Networks
Yuchen Zhang, Percy Liang, Martin J. Wainwright
ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning
Hantian Zhang, Jerry Li, Kaan Kara et al.
Re-revisiting Learning on Hypergraphs: Confidence Interval and Subgradient Method
Chenzi Zhang, Shuguang Hu, Zhihao Gavin Tang et al.
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction
Weizhong Zhang, Bin Hong, Wei Liu et al.
Adversarial Feature Matching for Text Generation
Yizhe Zhang, Zhe Gan, Kai Fan et al.
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