Papers
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs
Li Jing, Yichen Shen, Tena Dubcek et al.
How to Escape Saddle Points Efficiently
Chi Jin, Rong Ge, Praneeth Netrapalli et al.
Efficient Nonmyopic Active Search
Shali Jiang, Gustavo Malkomes, Geoff Converse et al.
Contextual Decision Processes with low Bellman rank are PAC-Learnable
Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal et al.
Uniform Convergence Rates for Kernel Density Estimation
Heinrich Jiang
Density Level Set Estimation on Manifolds with DBSCAN
Heinrich Jiang
From Patches to Images: A Nonparametric Generative Model
Geng Ji, Michael C. Hughes, Erik B. Sudderth
Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation
Yacine Jernite, Anna Choromanska, David Sontag
Bayesian Optimization with Tree-structured Dependencies
Rodolphe Jenatton, Cedric Archambeau, Javier González et al.
Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control
Natasha Jaques, Shixiang Gu, Dzmitry Bahdanau et al.
Scalable Generative Models for Multi-label Learning with Missing Labels
Vikas Jain, Nirbhay Modhe, Piyush Rai
Decoupled Neural Interfaces using Synthetic Gradients
Max Jaderberg, Wojciech Marian Czarnecki, Simon Osindero et al.
Fairness in Reinforcement Learning
Shahin Jabbari, Matthew Joseph, Michael Kearns et al.
Variational Inference for Sparse and Undirected Models
John Ingraham, Debora Marks
Tensor Decomposition with Smoothness
Masaaki Imaizumi, Kohei Hayashi
Toward Controlled Generation of Text
Zhiting Hu, Zichao Yang, Xiaodan Liang et al.
Deep Generative Models for Relational Data with Side Information
Changwei Hu, Piyush Rai, Lawrence Carin
State-Frequency Memory Recurrent Neural Networks
Hao Hu, Guo-Jun Qi
Learning Discrete Representations via Information Maximizing Self-Augmented Training
Weihua Hu, Takeru Miyato, Seiya Tokui et al.
Dissipativity Theory for Nesterov’s Accelerated Method
Bin Hu, Laurent Lessard
Analysis and Optimization of Graph Decompositions by Lifted Multicuts
Andrea Horňáková, Jan-Hendrik Lange, Bjoern Andres
Prox-PDA: The Proximal Primal-Dual Algorithm for Fast Distributed Nonconvex Optimization and Learning Over Networks
Mingyi Hong, Davood Hajinezhad, Ming-Min Zhao
Minimizing Trust Leaks for Robust Sybil Detection
János Höner, Shinichi Nakajima, Alexander Bauer et al.
Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo
Matthew D. Hoffman
Multilevel Clustering via Wasserstein Means
Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin et al.