Papers
Nonextensive Information Theoretic Kernels on Measures
André F. T. Martins, Noah A. Smith, Eric P. Xing et al.
Java-ML: A Machine Learning Library
Thomas Abeel, Yves Van de Peer, Yvan Saeys
Polynomial-Delay Enumeration of Monotonic Graph Classes
Jan Ramon, Siegfried Nijssen
Estimation of Sparse Binary Pairwise Markov Networks using Pseudo-likelihoods
Holger Höfling, Robert Tibshirani
Stable and Efficient Gaussian Process Calculations
Leslie Foster, Alex Waagen, Nabeela Aijaz et al.
Consistency and Localizability
Alon Zakai, Ya'acov Ritov
A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
Jacob Abernethy, Francis Bach, Theodoros Evgeniou et al.
Sparse Online Learning via Truncated Gradient
John Langford, Lihong Li, Tong Zhang
Similarity-based Classification: Concepts and Algorithms
Yihua Chen, Eric K. Garcia, Maya R. Gupta et al.
Nieme: Large-Scale Energy-Based Models
Francis Maes
On Efficient Large Margin Semisupervised Learning: Method and Theory
Junhui Wang, Xiaotong Shen, Wei Pan
Properties of Monotonic Effects on Directed Acyclic Graphs
Tyler J. VanderWeele, James M. Robins
Nearest Neighbor Clustering: A Baseline Method for Consistent Clustering with Arbitrary Objective Functions
Sébastien Bubeck, Ulrike von Luxburg
Scalable Collaborative Filtering Approaches for Large Recommender Systems
Gábor Takács, István Pilászy, Bottyán Németh et al.
NEUROSVM: An Architecture to Reduce the Effect of the Choice of Kernel on the Performance of SVM
Pradip Ghanty, Samrat Paul, Nikhil R. Pal
Online Learning with Sample Path Constraints
Shie Mannor, John N. Tsitsiklis, Jia Yuan Yu
Identification of Recurrent Neural Networks by Bayesian Interrogation Techniques
Barnabás Póczos, András Loőrincz
Generalization Bounds for Ranking Algorithms via Algorithmic Stability
Shivani Agarwal, Partha Niyogi
Particle Swarm Model Selection
Hugo Jair Escalante, Manuel Montes, Luis Enrique Sucar
Supervised Descriptive Rule Discovery: A Unifying Survey of Contrast Set, Emerging Pattern and Subgroup Mining
Petra Kralj Novak, Nada Lavrač
Low-Rank Kernel Learning with Bregman Matrix Divergences
Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon
Improving the Reliability of Causal Discovery from Small Data Sets Using Argumentation
Facundo Bromberg, Dimitris Margaritis
Analysis of Perceptron-Based Active Learning
Sanjoy Dasgupta, Adam Tauman Kalai, Claire Monteleoni