Papers
Recurrent Predictive State Policy Networks
Ahmed Hefny, Zita Marinho, Wen Sun et al.
Multicalibration: Calibration for the (Computationally-Identifiable) Masses
Ursula Hebert-Johnson, Michael Kim, Omer Reingold et al.
Fairness Without Demographics in Repeated Loss Minimization
Tatsunori Hashimoto, Megha Srivastava, Hongseok Namkoong et al.
Learning Memory Access Patterns
Milad Hashemi, Kevin Swersky, Jamie Smith et al.
Deep Models of Interactions Across Sets
Jason Hartford, Devon Graham, Kevin Leyton-Brown et al.
Stein Variational Gradient Descent Without Gradient
Jun Han, Qiang Liu
Candidates vs. Noises Estimation for Large Multi-Class Classification Problem
Lei Han, Yiheng Huang, Tong Zhang
K-Beam Minimax: Efficient Optimization for Deep Adversarial Learning
Jihun Hamm, Yung-Kyun Noh
Comparison-Based Random Forests
Siavash Haghiri, Damien Garreau, Ulrike Luxburg
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel et al.
Latent Space Policies for Hierarchical Reinforcement Learning
Tuomas Haarnoja, Kristian Hartikainen, Pieter Abbeel et al.
Shampoo: Preconditioned Stochastic Tensor Optimization
Vineet Gupta, Tomer Koren, Yoram Singer
Characterizing Implicit Bias in Terms of Optimization Geometry
Suriya Gunasekar, Jason Lee, Daniel Soudry et al.
Learning to search with MCTSnets
Arthur Guez, Theophane Weber, Ioannis Antonoglou et al.
Faster Derivative-Free Stochastic Algorithm for Shared Memory Machines
Bin Gu, Zhouyuan Huo, Cheng Deng et al.
Learning Policy Representations in Multiagent Systems
Aditya Grover, Maruan Al-Shedivat, Jayesh Gupta et al.
Visualizing and Understanding Atari Agents
Samuel Greydanus, Anurag Koul, Jonathan Dodge et al.
Learning One Convolutional Layer with Overlapping Patches
Surbhi Goel, Adam Klivans, Raghu Meka
Non-linear motor control by local learning in spiking neural networks
Aditya Gilra, Wulfram Gerstner
Robust and Scalable Models of Microbiome Dynamics
Travis Gibson, Georg Gerber
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time
Asish Ghoshal, Jean Honorio
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors
Soumya Ghosh, Jiayu Yao, Finale Doshi-Velez
Linear Spectral Estimators and an Application to Phase Retrieval
Ramina Ghods, Andrew Lan, Tom Goldstein et al.
Budgeted Experiment Design for Causal Structure Learning
AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash et al.
Temporal Poisson Square Root Graphical Models
Sinong Geng, Zhaobin Kuang, Peggy Peissig et al.