Papers
Composable Planning with Attributes
Amy Zhang, Sainbayar Sukhbaatar, Adam Lerer et al.
Deep Bayesian Nonparametric Tracking
Aonan Zhang, John Paisley
Tropical Geometry of Deep Neural Networks
Liwen Zhang, Gregory Naitzat, Lek-Heng Lim
Learning Long Term Dependencies via Fourier Recurrent Units
Jiong Zhang, Yibo Lin, Zhao Song et al.
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization
Jiong Zhang, Qi Lei, Inderjit Dhillon
Improving the Privacy and Accuracy of ADMM-Based Distributed Algorithms
Xueru Zhang, Mohammad Mahdi Khalili, Mingyan Liu
Safe Element Screening for Submodular Function Minimization
Weizhong Zhang, Bin Hong, Lin Ma et al.
High Performance Zero-Memory Overhead Direct Convolutions
Jiyuan Zhang, Franz Franchetti, Tze Meng Low
Large-Scale Sparse Inverse Covariance Estimation via Thresholding and Max-Det Matrix Completion
Richard Zhang, Salar Fattahi, Somayeh Sojoudi
Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow
Xiao Zhang, Simon Du, Quanquan Gu
Problem Dependent Reinforcement Learning Bounds Which Can Identify Bandit Structure in MDPs
Andrea Zanette, Emma Brunskill
Policy Optimization as Wasserstein Gradient Flows
Ruiyi Zhang, Changyou Chen, Chunyuan Li et al.
A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming
Alp Yurtsever, Olivier Fercoq, Francesco Locatello et al.
An Efficient Semismooth Newton based Algorithm for Convex Clustering
Yancheng Yuan, Defeng Sun, Kim-Chuan Toh
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
Jiaxuan You, Rex Ying, Xiang Ren et al.
RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks
Jinsung Yoon, James Jordon, Mihaela Schaar
GAIN: Missing Data Imputation using Generative Adversarial Nets
Jinsung Yoon, James Jordon, Mihaela Schaar
Probably Approximately Metric-Fair Learning
Gal Yona, Guy Rothblum
Disentangled Sequential Autoencoder
Li Yingzhen, Stephan Mandt
Semi-Implicit Variational Inference
Mingzhang Yin, Mingyuan Zhou
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates
Dong Yin, Yudong Chen, Ramchandran Kannan et al.
Loss Decomposition for Fast Learning in Large Output Spaces
Ian En-Hsu Yen, Satyen Kale, Felix Yu et al.
Communication-Computation Efficient Gradient Coding
Min Ye, Emmanuel Abbe
Massively Parallel Algorithms and Hardness for Single-Linkage Clustering under ℓ_p Distances
Grigory Yaroslavtsev, Adithya Vadapalli