Papers
Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning
Peter Auer, Ronald Ortner
Inferring Network Structure from Co-Occurrences
Michael G. Rabbat, Mário Figueiredo, Robert Nowak
Clustering Under Prior Knowledge with Application to Image Segmentation
Dong S. Cheng, Vittorio Murino, Mário Figueiredo
Generalized Maximum Margin Clustering and Unsupervised Kernel Learning
Hamed Valizadegan, Rong Jin
Fundamental Limitations of Spectral Clustering
Boaz Nadler, Meirav Galun
An Approach to Bounded Rationality
Eli Ben-sasson, Ehud Kalai, Adam Kalai
A Theory of Retinal Population Coding
Eizaburo Doi, Michael S. Lewicki
Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons
Stefan Klampfl, Wolfgang Maass, Robert A. Legenstein
A Novel Gaussian Sum Smoother for Approximate Inference in Switching Linear Dynamical Systems
David Barber, Bertrand Mesot
Effects of Stress and Genotype on Meta-parameter Dynamics in Reinforcement Learning
Gediminas Lukšys, Jérémie Knüsel, Denis Sheynikhovich et al.
AdaBoost is Consistent
Peter L. Bartlett, Mikhail Traskin
A Complexity-Distortion Approach to Joint Pattern Alignment
Andrea Vedaldi, Stefano Soatto
Gaussian and Wishart Hyperkernels
Risi Kondor, Tony Jebara
Sparse Multinomial Logistic Regression via Bayesian L1 Regularisation
Gavin C. Cawley, Nicola L. Talbot, Mark Girolami
Neurophysiological Evidence of Cooperative Mechanisms for Stereo Computation
Jason M. Samonds, Brian R. Potetz, Tai S. Lee
Analysis of Representations for Domain Adaptation
Shai Ben-David, John Blitzer, Koby Crammer et al.
Learning to Rank with Nonsmooth Cost Functions
Christopher J. Burges, Robert Ragno, Quoc V. Le
Optimal Single-Class Classification Strategies
Ran El-Yaniv, Mordechai Nisenson
Multi-Robot Negotiation: Approximating the Set of Subgame Perfect Equilibria in General-Sum Stochastic Games
Chris Murray, Geoffrey J. Gordon
Conditional Random Sampling: A Sketch-based Sampling Technique for Sparse Data
Ping Li, Kenneth W. Church, Trevor J. Hastie
PG-means: learning the number of clusters in data
Yu Feng, Greg Hamerly
implicit Online Learning with Kernels
Li Cheng, Dale Schuurmans, Shaojun Wang et al.
Mixture Regression for Covariate Shift
Masashi Sugiyama, Amos J. Storkey
Attribute-efficient learning of decision lists and linear threshold functions under unconcentrated distributions
Philip M. Long, Rocco Servedio