Papers
Image Retrieval and Classification Using Local Distance Functions
Andrea Frome, Yoram Singer, Jitendra Malik
implicit Online Learning with Kernels
Li Cheng, Dale Schuurmans, Shaojun Wang et al.
Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions
Christian Walder, Olivier Chapelle, Bernhard Schölkopf
Inducing Metric Violations in Human Similarity Judgements
Julian Laub, Klaus-Robert Müller, Felix A. Wichmann et al.
Inferring Network Structure from Co-Occurrences
Michael G. Rabbat, Mário Figueiredo, Robert Nowak
Information Bottleneck for Non Co-Occurrence Data
Yevgeny Seldin, Noam Slonim, Naftali Tishby
Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons
Stefan Klampfl, Wolfgang Maass, Robert A. Legenstein
In-Network PCA and Anomaly Detection
Ling Huang, Xuanlong Nguyen, Minos Garofalakis et al.
Isotonic Conditional Random Fields and Local Sentiment Flow
Yi Mao, Guy Lebanon
Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm
Robert Jenssen, Torbjørn Eltoft, Mark Girolami et al.
Kernels on Structured Objects Through Nested Histograms
Marco Cuturi, Kenji Fukumizu
Large Margin Component Analysis
Lorenzo Torresani, Kuang-chih Lee
Large Margin Hidden Markov Models for Automatic Speech Recognition
Fei Sha, Lawrence K. Saul
Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural Prosthesis
Amit Gore, Shantanu Chakrabartty
Large Scale Hidden Semi-Markov SVMs
Gunnar Rätsch, Sören Sonnenburg
Large-Scale Sparsified Manifold Regularization
Ivor W. Tsang, James T. Kwok
Learnability and the doubling dimension
Yi Li, Philip M. Long
Learning annotated hierarchies from relational data
Daniel M. Roy, Charles Kemp, Vikash K. Mansinghka et al.
Learning Dense 3D Correspondence
Florian Steinke, Volker Blanz, Bernhard Schölkopf
Learning from Multiple Sources
Koby Crammer, Michael Kearns, Jennifer Wortman
Learning Motion Style Synthesis from Perceptual Observations
Lorenzo Torresani, Peggy Hackney, Christoph Bregler
Learning Nonparametric Models for Probabilistic Imitation
David B. Grimes, Daniel R. Rashid, Rajesh P. Rao
Learning on Graph with Laplacian Regularization
Rie K. Ando, Tong Zhang
Learning Structural Equation Models for fMRI
Enrico Simonotto, Heather Whalley, Stephen Lawrie et al.
Learning Time-Intensity Profiles of Human Activity using Non-Parametric Bayesian Models
Alexander T. Ihler, Padhraic Smyth