Papers
Sampling Methods for the Nyström Method
Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar
Mal-ID: Automatic Malware Detection Using Common Segment Analysis and Meta-Features
Gil Tahan, Lior Rokach, Yuval Shahar
Stability of Density-Based Clustering
Alessandro Rinaldo, Aarti Singh, Rebecca Nugent et al.
Algebraic Geometric Comparison of Probability Distributions
Franz J. Király, Paul von Bünau, Frank C. Meinecke et al.
NIMFA : A Python Library for Nonnegative Matrix Factorization
Marinka Žitnik, Blaž Zupan
Causal Bounds and Observable Constraints for Non-deterministic Models
Roland R. Ramsahai
Algorithms for Learning Kernels Based on Centered Alignment
Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh
Exact Covariance Thresholding into Connected Components for Large-Scale Graphical Lasso
Rahul Mazumder, Trevor Hastie
GPLP: A Local and Parallel Computation Toolbox for Gaussian Process Regression
Chiwoo Park, Jianhua Z. Huang, Yu Ding
A Kernel Two-Sample Test
Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch et al.
A Case Study on Meta-Generalising: A Gaussian Processes Approach
Grigorios Skolidis, Guido Sanguinetti
Structured Sparsity and Generalization
Andreas Maurer, Massimiliano Pontil
Learning Algorithms for the Classification Restricted Boltzmann Machine
Hugo Larochelle, Michael Mandel, Razvan Pascanu et al.
Non-Sparse Multiple Kernel Fisher Discriminant Analysis
Fei Yan, Josef Kittler, Krystian Mikolajczyk et al.
A Primal-Dual Convergence Analysis of Boosting
Matus Telgarsky
ML-Flex: A Flexible Toolbox for Performing Classification Analyses In Parallel
Stephen R. Piccolo, Lewis J. Frey
MULTIBOOST: A Multi-purpose Boosting Package
Djalel Benbouzid, Róbert Busa-Fekete, Norman Casagrande et al.
Metric and Kernel Learning Using a Linear Transformation
Prateek Jain, Brian Kulis, Jason V. Davis et al.
Eliminating Spammers and Ranking Annotators for Crowdsourced Labeling Tasks
Vikas C. Raykar, Shipeng Yu
Multi-Assignment Clustering for Boolean Data
Mario Frank, Andreas P. Streich, David Basin et al.
Online Learning in the Embedded Manifold of Low-rank Matrices
Uri Shalit, Daphna Weinshall, Gal Chechik
Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
Bounding the Probability of Error for High Precision Optical Character Recognition
Gary B. Huang, Andrew Kae, Carl Doersch et al.
Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics
Michael U. Gutmann, Aapo Hyvärinen
Random Search for Hyper-Parameter Optimization
James Bergstra, Yoshua Bengio