Papers
Information Retrieval Perspective to Nonlinear Dimensionality Reduction for Data Visualization
Jarkko Venna, Jaakko Peltonen, Kristian Nybo et al.
Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance
Nguyen Xuan Vinh, Julien Epps, James Bailey
Inter-time segment information sharing for non-homogeneous dynamic Bayesian networks
Dirk Husmeier, Frank Dondelinger, Sophie Lebre
Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains
Martha White, Adam White
Introduction to Causal Inference
Peter Spirtes
Iterative Scaling and Coordinate Descent Methods for Maximum Entropy Models
Fang-Lan Huang, Cho-Jui Hsieh, Kai-Wei Chang et al.
Joint Analysis of Time-Evolving Binary Matrices and Associated Documents
Eric Wang, Dehong Liu, Jorge Silva et al.
Joint Cascade Optimization Using A Product Of Boosted Classifiers
Leonidas Lefakis, Francois Fleuret
Kernel Descriptors for Visual Recognition
Liefeng Bo, Xiaofeng Ren, Dieter Fox
Kernel Partial Least Squares is Universally Consistent
Gilles Blanchard, Nicole Krämer
Kronecker Graphs: An Approach to Modeling Networks
Jure Leskovec, Deepayan Chakrabarti, Jon Kleinberg et al.
Label Embedding Trees for Large Multi-Class Tasks
Samy Bengio, Jason Weston, David Grangier
Large Margin Learning of Upstream Scene Understanding Models
Jun Zhu, Li-jia Li, Li Fei-fei et al.
Large Margin Multi-Task Metric Learning
Shibin Parameswaran, Kilian Q. Weinberger
Large-Scale Matrix Factorization with Missing Data under Additional Constraints
Kaushik Mitra, Sameer Sheorey, Rama Chellappa
Large Scale Online Learning of Image Similarity Through Ranking
Gal Chechik, Varun Sharma, Uri Shalit et al.
Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development
Diane Hu, Laurens Maaten, Youngmin Cho et al.
Layered image motion with explicit occlusions, temporal consistency, and depth ordering
Deqing Sun, Erik B. Sudderth, Michael J. Black
Layer-wise analysis of deep networks with Gaussian kernels
Grégoire Montavon, Klaus-Robert Müller, Mikio L. Braun
Learnability, Stability and Uniform Convergence
Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro et al.
Learning Bayesian Network Structure using LP Relaxations
Tommi Jaakkola, David Sontag, Amir Globerson et al.
Learning Bounds for Importance Weighting
Corinna Cortes, Yishay Mansour, Mehryar Mohri
Learning Causal Structure from Overlapping Variable Sets
Sofia Triantafillou, Ioannis Tsamardinos, Ioannis Tollis
Learning concept graphs from text with stick-breaking priors
America Chambers, Padhraic Smyth, Mark Steyvers
Learning Convolutional Feature Hierarchies for Visual Recognition
Koray Kavukcuoglu, Pierre Sermanet, Y-lan Boureau et al.