Papers
Conditional Neural Processes
Marta Garnelo, Dan Rosenbaum, Christopher Maddison et al.
Structured Output Learning with Abstention: Application to Accurate Opinion Prediction
Alexandre Garcia, Chloé Clavel, Slim Essid et al.
Parallel Bayesian Network Structure Learning
Tian Gao, Dennis Wei
Spotlight: Optimizing Device Placement for Training Deep Neural Networks
Yuanxiang Gao, Li Chen, Baochun Li
Synthesizing Programs for Images using Reinforced Adversarial Learning
Yaroslav Ganin, Tejas Kulkarni, Igor Babuschkin et al.
Parameterized Algorithms for the Matrix Completion Problem
Robert Ganian, Iyad Kanj, Sebastian Ordyniak et al.
Hyperbolic Entailment Cones for Learning Hierarchical Embeddings
Octavian Ganea, Gary Becigneul, Thomas Hofmann
Inductive Two-Layer Modeling with Parametric Bregman Transfer
Vignesh Ganapathiraman, Zhan Shi, Xinhua Zhang et al.
Local Private Hypothesis Testing: Chi-Square Tests
Marco Gaboardi, Ryan Rogers
The Generalization Error of Dictionary Learning with Moreau Envelopes
Alexandros Georgogiannis
Born Again Neural Networks
Tommaso Furlanello, Zachary Lipton, Michael Tschannen et al.
Clipped Action Policy Gradient
Yasuhiro Fujita, Shin-ichi Maeda
Addressing Function Approximation Error in Actor-Critic Methods
Scott Fujimoto, Herke Hoof, David Meger
Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning
Ronan Fruit, Matteo Pirotta, Alessandro Lazaric et al.
Bilevel Programming for Hyperparameter Optimization and Meta-Learning
Luca Franceschi, Paolo Frasconi, Saverio Salzo et al.
ADMM and Accelerated ADMM as Continuous Dynamical Systems
Guilherme Franca, Daniel Robinson, Rene Vidal
Generative Temporal Models with Spatial Memory for Partially Observed Environments
Marco Fraccaro, Danilo Rezende, Yori Zwols et al.
Practical Contextual Bandits with Regression Oracles
Dylan Foster, Alekh Agarwal, Miroslav Dudik et al.
DiCE: The Infinitely Differentiable Monte Carlo Estimator
Jakob Foerster, Gregory Farquhar, Maruan Al-Shedivat et al.
Automatic Goal Generation for Reinforcement Learning Agents
Carlos Florensa, David Held, Xinyang Geng et al.
Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization
Louis Filstroff, Alberto Lumbreras, Cédric Févotte
Nonparametric variable importance using an augmented neural network with multi-task learning
Jean Feng, Brian Williamson, Noah Simon et al.
Fourier Policy Gradients
Matthew Fellows, Kamil Ciosek, Shimon Whiteson
CRVI: Convex Relaxation for Variational Inference
Ghazal Fazelnia, John Paisley
Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator
Maryam Fazel, Rong Ge, Sham Kakade et al.