Papers
High Order Regularization for Semi-Supervised Learning of Structured Output Problems
Yujia Li, Rich Zemel
Improving offline evaluation of contextual bandit algorithms via bootstrapping techniques
Jérémie Mary, Philippe Preux, Olivier Nicol
Inferning with High Girth Graphical Models
Uri Heinemann, Amir Globerson
Influence Function Learning in Information Diffusion Networks
Nan Du, Yingyu Liang, Maria Balcan et al.
Input Warping for Bayesian Optimization of Non-Stationary Functions
Jasper Snoek, Kevin Swersky, Rich Zemel et al.
Joint Inference of Multiple Label Types in Large Networks
Deepayan Chakrabarti, Stanislav Funiak, Jonathan Chang et al.
Kernel Adaptive Metropolis-Hastings
Dino Sejdinovic, Heiko Strathmann, Maria Lomeli Garcia et al.
Kernel Mean Estimation and Stein Effect
Krikamol Muandet, Kenji Fukumizu, Bharath Sriperumbudur et al.
K-means recovers ICA filters when independent components are sparse
Alon Vinnikov, Shai Shalev-Shwartz
Large-Margin Metric Learning for Constrained Partitioning Problems
Rémi Lajugie, Francis Bach, Sylvain Arlot
Large-margin Weakly Supervised Dimensionality Reduction
Chang Xu, Dacheng Tao, Chao Xu et al.
Large-scale Multi-label Learning with Missing Labels
Hsiang-Fu Yu, Prateek Jain, Purushottam Kar et al.
Latent Bandits.
Odalric-Ambrym Maillard, Shie Mannor
Latent Confusion Analysis by Normalized Gamma Construction
Issei Sato, Hisashi Kashima, Hiroshi Nakagawa
Latent Semantic Representation Learning for Scene Classification
Xin Li, Yuhong Guo
Latent Variable Copula Inference for Bundle Pricing from Retail Transaction Data
Benjamin Letham, Wei Sun, Anshul Sheopuri
Learnability of the Superset Label Learning Problem
Liping Liu, Thomas Dietterich
Learning by Stretching Deep Networks
Gaurav Pandey, Ambedkar Dukkipati
Learning Character-level Representations for Part-of-Speech Tagging
Cicero Dos Santos, Bianca Zadrozny
Learning Complex Neural Network Policies with Trajectory Optimization
Sergey Levine, Vladlen Koltun
Learning from Contagion (Without Timestamps)
Kareem Amin, Hoda Heidari, Michael Kearns
Learning Graphs with a Few Hubs
Rashish Tandon, Pradeep Ravikumar
Learning Latent Variable Gaussian Graphical Models
Zhaoshi Meng, Brian Eriksson, Al Hero
Learning Mixtures of Linear Classifiers
Yuekai Sun, Stratis Ioannidis, Andrea Montanari
Learning Modular Structures from Network Data and Node Variables
Elham Azizi, Edoardo Airoldi, James Galagan