Papers
Learning Horizontal Connections in a Sparse Coding Model of Natural Images
Pierre Garrigues, Bruno A. Olshausen
Learning Monotonic Transformations for Classification
Andrew Howard, Tony Jebara
Learning the 2-D Topology of Images
Nicolas L. Roux, Yoshua Bengio, Pascal Lamblin et al.
Learning the structure of manifolds using random projections
Yoav Freund, Sanjoy Dasgupta, Mayank Kabra et al.
Learning to classify complex patterns using a VLSI network of spiking neurons
Srinjoy Mitra, Giacomo Indiveri, Stefano Fusi
Learning Visual Attributes
Vittorio Ferrari, Andrew Zisserman
Learning with Transformation Invariant Kernels
Christian Walder, Olivier Chapelle
Learning with Tree-Averaged Densities and Distributions
Sergey Kirshner
Linear programming analysis of loopy belief propagation for weighted matching
Sujay Sanghavi, Dmitry Malioutov, Alan S. Willsky
Local Algorithms for Approximate Inference in Minor-Excluded Graphs
Kyomin Jung, Devavrat Shah
Locality and low-dimensions in the prediction of natural experience from fMRI
Francois Meyer, Greg Stephens
Loop Series and Bethe Variational Bounds in Attractive Graphical Models
Alan S. Willsky, Erik B. Sudderth, Martin J. Wainwright
Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning
Gerald Tesauro, Rajarshi Das, Hoi Chan et al.
Markov Chain Monte Carlo with People
Adam Sanborn, Thomas L. Griffiths
McRank: Learning to Rank Using Multiple Classification and Gradient Boosting
Ping Li, Qiang Wu, Christopher J. Burges
Measuring Neural Synchrony by Message Passing
Justin Dauwels, François Vialatte, Tomasz Rutkowski et al.
Message Passing for Max-weight Independent Set
Sujay Sanghavi, Devavrat Shah, Alan S. Willsky
Mining Internet-Scale Software Repositories
Erik Linstead, Paul Rigor, Sushil Bajracharya et al.
Modeling image patches with a directed hierarchy of Markov random fields
Simon Osindero, Geoffrey E. Hinton
Modeling Natural Sounds with Modulation Cascade Processes
Richard Turner, Maneesh Sahani
Modelling motion primitives and their timing in biologically executed movements
Ben Williams, Marc Toussaint, Amos J. Storkey
Multiple-Instance Active Learning
Burr Settles, Mark Craven, Soumya Ray
Multiple-Instance Pruning For Learning Efficient Cascade Detectors
Cha Zhang, Paul A. Viola
Multi-task Gaussian Process Prediction
Edwin V. Bonilla, Kian M. Chai, Christopher Williams