Papers
Learning Efficient Random Maximum A-Posteriori Predictors with Non-Decomposable Loss Functions
Tamir Hazan, Subhransu Maji, Joseph Keshet et al.
Learning Feature Selection Dependencies in Multi-task Learning
Daniel Hernández-Lobato, José Miguel Hernández-Lobato
Learning from Limited Demonstrations
Beomjoon Kim, Amir-massoud Farahmand, Joelle Pineau et al.
Learning Gaussian Graphical Models with Observed or Latent FVSs
Ying Liu, Alan Willsky
Learning Hidden Markov Models from Non-sequence Data via Tensor Decomposition
Tzu-Kuo Huang, Jeff Schneider
Learning invariant representations and applications to face verification
Qianli Liao, Joel Z. Leibo, Tomaso Poggio
Learning Kernels Using Local Rademacher Complexity
Corinna Cortes, Marius Kloft, Mehryar Mohri
Learning Multi-level Sparse Representations
Ferran Diego Andilla, Fred A. Hamprecht
Learning Multiple Models via Regularized Weighting
Daniel Vainsencher, Shie Mannor, Huan Xu
Learning Prices for Repeated Auctions with Strategic Buyers
Kareem Amin, Afshin Rostamizadeh, Umar Syed
Learning Stochastic Feedforward Neural Networks
Charlie Tang, Ruslan Salakhutdinov
Learning Stochastic Inverses
Andreas Stuhlmüller, Jacob Taylor, Noah Goodman
Learning the Local Statistics of Optical Flow
Dan Rosenbaum, Daniel Zoran, Yair Weiss
Learning to Pass Expectation Propagation Messages
Nicolas Heess, Daniel Tarlow, John Winn
Learning to Prune in Metric and Non-Metric Spaces
Leonid Boytsov, Bilegsaikhan Naidan
Learning Trajectory Preferences for Manipulators via Iterative Improvement
Ashesh Jain, Brian Wojcik, Thorsten Joachims et al.
Learning with Invariance via Linear Functionals on Reproducing Kernel Hilbert Space
Xinhua Zhang, Wee Sun Lee, Yee Whye Teh
Learning with Noisy Labels
Nagarajan Natarajan, Inderjit S Dhillon, Pradeep K Ravikumar et al.
Learning word embeddings efficiently with noise-contrastive estimation
Andriy Mnih, Koray Kavukcuoglu
Least Informative Dimensions
Fabian Sinz, Anna Stockl, Jan Grewe et al.
Lexical and Hierarchical Topic Regression
Viet-An Nguyen, Jordan L Ying, Philip Resnik
Linear Convergence with Condition Number Independent Access of Full Gradients
Lijun Zhang, Mehrdad Mahdavi, Rong Jin
Locally Adaptive Bayesian Multivariate Time Series
Daniele Durante, Bruno Scarpa, David B Dunson
Local Privacy and Minimax Bounds: Sharp Rates for Probability Estimation
John Duchi, Martin J. Wainwright, Michael I Jordan