Papers
11,951 papers found
Learning to Represent Edits
Pengcheng Yin, Graham Neubig, Miltiadis Allamanis et al.
Learning to Schedule Communication in Multi-agent Reinforcement Learning
Daewoo Kim, Sangwoo Moon, David Hostallero et al.
Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Networks
Patrick Chen, Si Si, Sanjiv Kumar et al.
Learning To Simulate
Nataniel Ruiz, Samuel Schulter, Manmohan Chandraker
Learning To Solve Circuit-SAT: An Unsupervised Differentiable Approach
Saeed Amizadeh, Sergiy Matusevych, Markus Weimer
Learning to Understand Goal Specifications by Modelling Reward
Dzmitry Bahdanau, Felix Hill, Jan Leike et al.
Learning Two-layer Neural Networks with Symmetric Inputs
Rong Ge, Rohith Kuditipudi, Zhize Li et al.
Learning what and where to attend
Drew Linsley, Dan Shiebler, Sven Eberhardt et al.
Learning what you can do before doing anything
Oleh Rybkin, Karl Pertsch, Konstantinos G. Derpanis et al.
Learning when to Communicate at Scale in Multiagent Cooperative and Competitive Tasks
Amanpreet Singh, Tushar Jain, Sainbayar Sukhbaatar
LeMoNADe: Learned Motif and Neuronal Assembly Detection in calcium imaging videos
Elke Kirschbaum, Manuel Haußmann, Steffen Wolf et al.
Local SGD Converges Fast and Communicates Little
Sebastian U. Stich
Local SGD with Periodic Averaging: Tighter Analysis and Adaptive Synchronization
Farzin Haddadpour, Mohammad Mahdi Kamani, Mehrdad Mahdavi et al.
L-Shapley and C-Shapley: Efficient Model Interpretation for Structured Data
Jianbo Chen, Le Song, Martin J. Wainwright et al.
M^3RL: Mind-aware Multi-agent Management Reinforcement Learning
Tianmin Shu, Yuandong Tian
MAE: Mutual Posterior-Divergence Regularization for Variational AutoEncoders
Xuezhe Ma, Chunting Zhou, Eduard Hovy
Many-to-Many Beam Alignment in Millimeter Wave Networks
Suraj Jog, Jiaming Wang, Junfeng Guan et al.
MARGINALIZED AVERAGE ATTENTIONAL NETWORK FOR WEAKLY-SUPERVISED LEARNING
Yuan Yuan, Yueming Lyu, Xi Shen et al.
Marginal Policy Gradients: A Unified Family of Estimators for Bounded Action Spaces with Applications
Carson Eisenach, Haichuan Yang, Ji Liu et al.
Maximal Divergence Sequential Autoencoder for Binary Software Vulnerability Detection
Tue Le, Tuan Nguyen, Trung Le et al.
Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds
Peng Cao*, Yilun Xu*, Yuqing Kong et al.
Measuring and regularizing networks in function space
Ari Benjamin, David Rolnick, Konrad Kording
Measuring Compositionality in Representation Learning
Jacob Andreas
Meta-Learning For Stochastic Gradient MCMC
Wenbo Gong, Yingzhen Li, José Miguel Hernández-Lobato