Papers
Importance Weighting Without Importance Weights: An Efficient Algorithm for Combinatorial Semi-Bandits
Gergely Neu, Gábor Bartók
Improving Structure MCMC for Bayesian Networks through Markov Blanket Resampling
Chengwei Su, Mark E. Borsuk
Input Output Kernel Regression: Supervised and Semi-Supervised Structured Output Prediction with Operator-Valued Kernels
Céline Brouard, Marie Szafranski, Florence d'Alché-Buc
Integrative Analysis using Coupled Latent Variable Models for Individualizing Prognoses
Peter Schulam, Suchi Saria
Interleaved Text/Image Deep Mining on a Large-Scale Radiology Database for Automated Image Interpretation
Hoo-Chang Shin, Le Lu, Lauren Kim et al.
Iterative Hessian Sketch: Fast and Accurate Solution Approximation for Constrained Least-Squares
Mert Pilanci, Martin J. Wainwright
Iterative Regularization for Learning with Convex Loss Functions
Junhong Lin, Lorenzo Rosasco, Ding-Xuan Zhou
JCLAL: A Java Framework for Active Learning
Oscar Reyes, Eduardo Pérez, María del Carmen Rodríguez-Hernández et al.
Jointly Informative Feature Selection Made Tractable by Gaussian Modeling
Leonidas Lefakis, François Fleuret
Joint Structural Estimation of Multiple Graphical Models
Jing Ma, George Michailidis
Kernel Estimation and Model Combination in A Bandit Problem with Covariates
Wei Qian, Yuhong Yang
Kernel Mean Shrinkage Estimators
Krikamol Muandet, Bharath Sriperumbudur, Kenji Fukumizu et al.
Knowledge Matters: Importance of Prior Information for Optimization
Çağlar Gülçehre, Yoshua Bengio
L1-Regularized Least Squares for Support Recovery of High Dimensional Single Index Models with Gaussian Designs
Matey Neykov, Jun S. Liu, Tianxi Cai
Large Scale Online Kernel Learning
Jing Lu, Steven C.H. Hoi, Jialei Wang et al.
Large Scale Visual Recognition through Adaptation using Joint Representation and Multiple Instance Learning
Judy Hoffman, Deepak Pathak, Eric Tzeng et al.
Latent Space Inference of Internet-Scale Networks
Qirong Ho, Junming Yin, Eric P. Xing
Learning Algorithms for Second-Price Auctions with Reserve
Mehryar Mohri, Andres Munoz Medina
Learning Latent Variable Models by Pairwise Cluster Comparison: Part II - Algorithm and Evaluation
Nuaman Asbeh, Boaz Lerner
Learning Latent Variable Models by Pairwise Cluster Comparison: Part I - Theory and Overview
Nuaman Asbeh, Boaz Lerner
Learning Planar Ising Models
Jason K. Johnson, Diane Oyen, Michael Chertkov et al.
Learning Taxonomy Adaptation in Large-scale Classification
Rohit Babbar, Ioannis Partalas, Eric Gaussier et al.
Learning Theory for Distribution Regression
Zoltán Szabó, Bharath K. Sriperumbudur, Barnabás Póczos et al.
Learning the Variance of the Reward-To-Go
Aviv Tamar, Dotan Di Castro, Shie Mannor