Papers
Learning shape correspondence with anisotropic convolutional neural networks
Davide Boscaini, Jonathan Masci, Emanuele Rodolà et al.
Learning Sparse Gaussian Graphical Models with Overlapping Blocks
Mohammad Javad Hosseini, Su-In Lee
Learning Structured Sparsity in Deep Neural Networks
Wei Wen, Chunpeng Wu, Yandan Wang et al.
Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods
Lev Bogolubsky, Pavel Dvurechenskii, Alexander Gasnikov et al.
Learning the Number of Neurons in Deep Networks
Jose M Alvarez, Mathieu Salzmann
Learning to Communicate with Deep Multi-Agent Reinforcement Learning
Jakob Foerster, Ioannis Alexandros Assael, Nando de Freitas et al.
Learning to learn by gradient descent by gradient descent
Marcin Andrychowicz, Misha Denil, Sergio Gómez et al.
Learning to Poke by Poking: Experiential Learning of Intuitive Physics
Pulkit Agrawal, Ashvin V Nair, Pieter Abbeel et al.
Learning Transferrable Representations for Unsupervised Domain Adaptation
Ozan Sener, Hyun Oh Song, Ashutosh Saxena et al.
Learning Tree Structured Potential Games
Vikas Garg, Tommi Jaakkola
Learning Treewidth-Bounded Bayesian Networks with Thousands of Variables
Mauro Scanagatta, Giorgio Corani, Cassio P de Campos et al.
Learning under uncertainty: a comparison between R-W and Bayesian approach
He Huang, Martin Paulus
Learning User Perceived Clusters with Feature-Level Supervision
Ting-Yu Cheng, Guiguan Lin, xinyang gong et al.
Learning values across many orders of magnitude
Hado P van Hasselt, Arthur Guez, Arthur Guez et al.
Learning What and Where to Draw
Scott E Reed, Zeynep Akata, Santosh Mohan et al.
Leveraging Sparsity for Efficient Submodular Data Summarization
Erik Lindgren, Shanshan Wu, Alexandros G Dimakis
Lifelong Learning with Weighted Majority Votes
Anastasia Pentina, Ruth Urner
LightRNN: Memory and Computation-Efficient Recurrent Neural Networks
Xiang Li, Tao Qin, Jian Yang et al.
Linear Contextual Bandits with Knapsacks
Shipra Agrawal, Nikhil Devanur
Linear dynamical neural population models through nonlinear embeddings
Yuanjun Gao, Evan W Archer, Liam Paninski et al.
Linear Feature Encoding for Reinforcement Learning
Zhao Song, Ronald E Parr, Xuejun Liao et al.
Linear-Memory and Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes
Dan Garber, Dan Garber, Ofer Meshi
Linear Relaxations for Finding Diverse Elements in Metric Spaces
Aditya Bhaskara, Mehrdad Ghadiri, Vahab Mirrokni et al.
Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences
Chi Jin, Yuchen Zhang, Sivaraman Balakrishnan et al.
Local Minimax Complexity of Stochastic Convex Optimization
sabyasachi chatterjee, John C. Duchi, John Lafferty et al.