Papers
Fitting New Speakers Based on a Short Untranscribed Sample
Eliya Nachmani, Adam Polyak, Yaniv Taigman et al.
Fixing a Broken ELBO
Alexander Alemi, Ben Poole, Ian Fischer et al.
Focused Hierarchical RNNs for Conditional Sequence Processing
Nan Rosemary Ke, Konrad Żołna, Alessandro Sordoni et al.
Fourier Policy Gradients
Matthew Fellows, Kamil Ciosek, Shimon Whiteson
Frank-Wolfe with Subsampling Oracle
Thomas Kerdreux, Fabian Pedregosa, Alexandre d’Aspremont
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents
Kaiqing Zhang, Zhuoran Yang, Han Liu et al.
Functional Gradient Boosting based on Residual Network Perception
Atsushi Nitanda, Taiji Suzuki
GAIN: Missing Data Imputation using Generative Adversarial Nets
Jinsung Yoon, James Jordon, Mihaela Schaar
Gated Path Planning Networks
Lisa Lee, Emilio Parisotto, Devendra Singh Chaplot et al.
Generalization without Systematicity: On the Compositional Skills of Sequence-to-Sequence Recurrent Networks
Brenden Lake, Marco Baroni
Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction
Siyuan Qi, Baoxiong Jia, Song-Chun Zhu
Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression
Haitao Liu, Jianfei Cai, Yi Wang et al.
Generative Temporal Models with Spatial Memory for Partially Observed Environments
Marco Fraccaro, Danilo Rezende, Yori Zwols et al.
Geodesic Convolutional Shape Optimization
Pierre Baque, Edoardo Remelli, Francois Fleuret et al.
Geometry Score: A Method For Comparing Generative Adversarial Networks
Valentin Khrulkov, Ivan Oseledets
GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms
Cédric Colas, Olivier Sigaud, Pierre-Yves Oudeyer
Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator
Maryam Fazel, Rong Ge, Sham Kakade et al.
Goodness-of-Fit Testing for Discrete Distributions via Stein Discrepancy
Jiasen Yang, Qiang Liu, Vinayak Rao et al.
Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace
Yoonho Lee, Seungjin Choi
Gradient Coding from Cyclic MDS Codes and Expander Graphs
Netanel Raviv, Rashish Tandon, Alex Dimakis et al.
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers
Yao Ma, Alexander Olshevsky, Csaba Szepesvari et al.
Gradient Descent Learns One-hidden-layer CNN: Don’t be Afraid of Spurious Local Minima
Simon Du, Jason Lee, Yuandong Tian et al.
Gradient descent with identity initialization efficiently learns positive definite linear transformations by deep residual networks
Peter Bartlett, Dave Helmbold, Philip Long
Gradient Primal-Dual Algorithm Converges to Second-Order Stationary Solution for Nonconvex Distributed Optimization Over Networks
Mingyi Hong, Meisam Razaviyayn, Jason Lee
GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks
Zhao Chen, Vijay Badrinarayanan, Chen-Yu Lee et al.