Papers
Gradient Sparsification for Communication-Efficient Distributed Optimization
Jianqiao Wangni, Jialei Wang, Ji Liu et al.
GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training
Mingchao Yu, Zhifeng Lin, Krishna Narra et al.
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
Jiaxuan You, Bowen Liu, Zhitao Ying et al.
Graphical Generative Adversarial Networks
Chongxuan LI, Max Welling, Jun Zhu et al.
Graphical model inference: Sequential Monte Carlo meets deterministic approximations
Fredrik Lindsten, Jouni Helske, Matti Vihola
Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization
Blake E Woodworth, Jialei Wang, Adam Smith et al.
Greedy Hash: Towards Fast Optimization for Accurate Hash Coding in CNN
Shupeng Su, Chao Zhang, Kai Han et al.
Group Equivariant Capsule Networks
Jan Eric Lenssen, Matthias Fey, Pascal Libuschewski
GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking
Patrick Chen, Si Si, Yang Li et al.
GumBolt: Extending Gumbel trick to Boltzmann priors
Amir H Khoshaman, Mohammad Amin
Hamiltonian Variational Auto-Encoder
Anthony L Caterini, Arnaud Doucet, Dino Sejdinovic
Hardware Conditioned Policies for Multi-Robot Transfer Learning
Tao Chen, Adithyavairavan Murali, Abhinav Gupta
Hessian-based Analysis of Large Batch Training and Robustness to Adversaries
Zhewei Yao, Amir Gholami, Qi Lei et al.
Heterogeneous Bitwidth Binarization in Convolutional Neural Networks
Joshua Fromm, Shwetak Patel, Matthai Philipose
Heterogeneous Multi-output Gaussian Process Prediction
Pablo Moreno-Muñoz, Antonio Artés, Mauricio Álvarez
Hierarchical Graph Representation Learning with Differentiable Pooling
Zhitao Ying, Jiaxuan You, Christopher Morris et al.
Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies
Sungryull Sohn, Junhyuk Oh, Honglak Lee
High Dimensional Linear Regression using Lattice Basis Reduction
Ilias Zadik, David Gamarnik
HitNet: Hybrid Ternary Recurrent Neural Network
Peiqi Wang, Xinfeng Xie, Lei Deng et al.
HOGWILD!-Gibbs can be PanAccurate
Constantinos Daskalakis, Nishanth Dikkala, Siddhartha Jayanti
Horizon-Independent Minimax Linear Regression
Alan Malek, Peter L Bartlett
HOUDINI: Lifelong Learning as Program Synthesis
Lazar Valkov, Dipak Chaudhari, Akash Srivastava et al.
How Does Batch Normalization Help Optimization?
Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas et al.
How Many Samples are Needed to Estimate a Convolutional Neural Network?
Simon S Du, Yining Wang, Xiyu Zhai et al.