Welcome to the first issue of the Journal of Machine Learning Video Abstracts. The first issue is dedicated to presenting the spotlight presentations of the 2010 Neural Information Processing Systems (NIPS) Conference held in Vancouver, Canada, on December 7-9. The presentations were lengthened to four minutes for this year’s conference with an allowance of 4 slides for each paper. The VideoLectures.NET team were on site to record the presentations and they post-processed the recordings to incorporate the slides into the video. The VideoLectures.NET portal provides the infrastructure for the journal pages. All of the abstracts have been reviewed for quality of recording and appropriateness of presentation, while the papers they describe were accepted to the highly prestigious and competitive NIPS event. At the conference itself there was also a poster session at which researchers could discuss the results with the authors and some of the presentations refer to these sessions at the end of their presentations. We are very conscious of the enormous effort that the authors have put into these presentations in order to communicate the results and main contributions of their papers to the community. We are therefore delighted to have been able to record them and make them available to a wider audience as a special issue of the Journal of Machine Learning Video Abstracts.
Journal Video Abstracts
Why are some word orders more common than others? A uniform information density account
Luke Maurits
Improving Human Judgments by Decontaminating Sequential Dependencies
Michael C. Mozer
Learning to localise sounds with spiking neural networks
Dan F. Goodman
SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex system
Sylvain Chevallier
Attractor Dynamics with Synaptic Depression
C. C. Alan Fung
Copula Processes
Andrew Gordon Wilson
A biologically plausible network for the computation of orientation dominance
Kritika Muralidharan<
LSTD with Random Projections
Mohammad Ghavamzadeh
Kernel Descriptors for Visual Recognition
Liefeng Bo
Minimum Average Cost Clustering
Kiyohito Nagano
Identifying Dendritic Processing
Aurel A. Lazar
Probabilistic Inference and Differential Privacy
Frank McSherry
Synergies in learning words and their referents
Mark Johnson
Learning concept graphs from text with stick-breaking priors
America Chambers
Efficient Minimization of Decomposable Submodular Functions
Peter G. Stobbe
Worst-case bounds on the quality of max-product fixed-points
Meritxell Vinyals
Learning To Count Objects in Images
Victor Lempitsky
Learning invariant features using the Transformed Indian Buffet Process
Joseph L. Austerweil
Multiple Kernel Learning and the SMO Algorithm
Manik Varma
Inductive Regularized Learning of Kernel Functions
Prateek Jain
Online Classification with Specificity Constraints
Andrey Bernstein
Exact inference and learning for cumulative
Jim C. Huang
Global Analytic Solution for Variational Bayesian
Shinichi Nakajima
Throttling Poisson Processes
Uwe Dick
Graph-Valued Regression
Xi Chen
Switched Latent Force Models for Movement Segmentation
Mauricio Alvarez
Distributed Dual Averaging In Networks
John Duchi
Online Learning for Latent Dirichlet Allocation
Matt Hoffman
Structured Determinantal Point Processes
Alex Kulesza
Supervised Clustering
Reza Bosagh Zadeh
Sample Complexity of Testing the Manifold Hypothesis
Hariharan Narayanan
Epitome driven 3-D Diffusion Tensor image segmentation: on extracting specific structures
Kamiya Motwani
Learning from Logged Implicit Exploration Data
Alexander Strehl
Deciphering subsampled data: adaptive compressive sampling as a principle of brain communication
Guy Isely
Feature Set Embedding for Incomplete Data
David Grangier