Conference Program
TUESDAY -- December 9, 2003:
8:30--9:20 INVITED SPEAKER
David Salesin
The Need for Machine Learning in Computer Graphics
9:20--9:40 ORAL
VM 01
Salvador Ruiz-Correa, Linda G. Shapiro, Marina Meila, Gabriel Berson
Discriminating Deformable Shape Classes
9:40-10:00 ORAL
VM 02
Kevin Murphy, Antonio Torralba, William T. Freeman
Using the Forest to See the Trees: A Graphical Model Relating Features, Objects, and Scenes
10:00-10:40 BREAK
10:40-11:00 ORAL
VB 01
Zhou Wang, Eero P. Simoncelli
Local Phase Coherence and the Perception of Blur
11:00-11:20 ORAL
VB 02
Vincent Bonin, Valerio Mante, Matteo Carandini
Nonlinear Processing in LGN Neurons
11:20-11:40 ORAL
ET 01
Reid R. Harrison
A Low-Power Analog VLSI Visual Collision Detector
11:40-12:00 SPOTLIGHTS
ET 02
Paul Merolla, Kwabena Boahen
A Recurrent Model of Orientation Maps with Simple and Complex Cells
VB 03
Scott A. Beardsley, Lucia M. Vaina
A Functional Architecture for Motion Pattern Processing in MSTd
VB 04
Alan Yuille, Fang Fang, Paul Schrater, Daniel Kersten
Human and Ideal Observers for Detecting Image Curves
VB 05
Nathan Sprague, Dana Ballard
Eye Movements for Reward Maximization
VM 03
Amit Gruber, Yair Weiss
Factorization with Uncertainty and Missing Data: Exploiting Temporal Coherence
VM 04
Michael Fink, Pietro Perona
Mutual Boosting for Contextual Inference
VM 05
Jianxin Wu, James M. Rehg, Matthew D. Mullin
Learning A Rare Event Detection Cascade by Direct Feature Selection
VM 06
Sanjiv Kumar, Martial Hebert
Discriminative Fields for Modeling Spatial Dependencies in Natural Images
AA 01
Alexander T. Ihler, Erik B. Sudderth, William T. Freeman, Alan S. Willsky
Efficient Multiscale Sampling from Products of Gaussian Mixtures
12:00--2:00 BREAK
2:00--2:20 ORAL
AP 01
John C. Platt
Fast Embedding of Sparse Similarity Graphs
2:20--2:40 ORAL
AA 02
Mark Girolami, Ata Kaban
Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles
2:40--3:00 ORAL
AP 02
Anton Schwaighofer, Marian Grigoras, V. Tresp, Clemens Hoffmann
GPPS: A Gaussian Process Positioning System for Cellular Networks
3:00--3:20 ORAL
AA 03
David M. Blei, Thomas L. Griffiths, Michael I. Jordan, Joshua B. Tenenbaum
Hierarchical Topic Models and the Nested Chinese Restaurant Process
3:20--3:30 SPOTLIGHTS
AP 03
David Ferguson, Aaron Morris, Dirk Haehnel, Christopher Baker, Zachary Omohundro, Carlos Reverte, Scott Thayer, Charles Whittaker, William Whittaker, Wolfram Burgard, Sebastian Thrun
An Autonomous Robotic System for Mapping Abandoned Mines
AP 04
Jason Weston, Christina Leslie, Dengyong Zhou, Andre Elisseeff, William S. Noble
Semi-supervised Protein Classification Using Cluster Kernels
AP 05
Alice X. Zheng, Michael I. Jordan, Ben Liblit, Alex Aiken
Statistical Debugging of Sampled Programs
AP 06
Nicholas P. Hughes, Lionel Tarassenko, Stephen J. Roberts
Markov Models for Automated ECG Interval Analysis
3:30--4:00 BREAK
4:00--4:20 ORAL
AA 04
Ben Taskar, Carlos Guestrin, Daphne Koller
Max-Margin Markov Networks
4:20--4:40 ORAL
AA 05
Thore Graepel, Ralf Herbrich
Invariant Pattern Recognition by Semidefinite Programming Machines
4:40--5:00 ORAL
SP 01
William M. Campbell, Joseph P. Campbell, Douglas A. Reynolds, Douglas A. Jones, Timothy R. Leek
Phonetic Speaker Recognition with Support Vector Machines
5:00--5:20 ORAL
LT 01
Ingo Steinwart
Sparseness of Support Vector Machines---Some Asymptotically Sharp Bounds
5:20--5:30 SPOTLIGHTS
AA 06
Matthew Schultz, Thorsten Joachims
Learning a Distance Metric from Relative Comparison
SP 02
Pedro J. Moreno, Purdy P. Ho, Nuno Vasconcelos
A Kullback-Leibler Divergence Based Kernel for SVM Classification in Multimedia Applications
AA 07
Ji Zhu, Saharon Rosset, Trevor Hastie, Rob Tibshirani
1-norm Support Vector Machines
AA 08
Koji Tsuda, Gunnar Ratsch
Image Reconstruction by Linear Programming
WEDNESDAY – December 10, 2003:
8:30--9:20 INVITED SPEAKER
Michale Fee
Time and Sequence in the Brain: Insights from a Songbird
9:20--9:40 ORAL
NS 08
Peter Dayan, Michael Hausser, Michael London
Plasticity Kernels and Temporal Statistics
9:40-10:00 ORAL
ET 06
Adria Bofill-i-Petit, Alan Murray
Synchrony Detection by Analogue VLSI Neurons with Bimodal STDP Synapses
10:00-10:40BREAK
10:40-11:00 ORAL
AA 37
Chen Yanover, Yair Weiss
Finding the M Most Probable Configurations using Loopy Belief Propagation
11:00-11:20 ORAL
AA 38
Jakob J. Verbeek, Sam T. Roweis, Nikos Vlassis
Non-linear CCA and PCA by Alignment of Local Models
11:20-11:40 ORAL
LT 10
David Donoho, Victoria Stodden
When Does Non-Negative Matrix Factorization Give a Correct Decomposition Into Parts?
11:40-12:00 SPOTLIGHTS
LT 11
Tong Zhang
Learning Bounds for a Generalized Family of Bayesian Posterior Distributions
LT 12
Manfred Opper, Ole Winther
Variational Linear Response
LT 13
Susanne Still, William Bialek, Leon Bottou
Geometric Clustering using the Information Bottleneck Method
AA 39
Francis R. Bach, Michael I. Jordan
Learning Spectral Clustering
AA 40
Corinna Cortes, Mehryar Mohri
AUC Optimization vs. Error Rate Minimization
AA 41
Dengyong Zhou, Olivier Bousquet, Thomas N. Lal, Jason Weston, Bernhard Schölkopf
Learning with Local and Global Consistency
AA 42
Neil D. Lawrence
Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data
AA 43
Edward Snelson, Carl E. Rasmussen, Zoubin Ghahramani
Warped Gaussian Processes
12:00--2:00 BREAK
2:00--2:20 ORAL
CN 08
Yu-Han Chang, Tracey Ho, Leslie Pack Kaelbling
All Learning is Local: Multi-agent Learning in Global Reward Games
2:20--2:40 ORAL
CN 09
Daniela Pucci de Farias, Nimrod Megiddo
How to Combine Expert (or Novice) Advice when Actions Impact the Environment?
2:40--3:00 ORAL
CN 10
Pascal Poupart, Craig Boutilier
Bounded Finite State Controllers
3:00--3:10 SPOTLIGHTS
CN 11
J. Andrew Bagnell, Sham Kakade, Andrew Y. Ng, Jeff Schneider
Policy Search by Dynamic Programming
CN 12
Arnab Nilim, Laurent El Ghaoui
Robust Markov Decision Problems with Uncertain Transition Matrices
CN 13
Alan Fern, SungWook Yoon, Robert Givan
Approximate Policy Iteration with a Policy Language Bias
CN 14
Matthew R. Rudary, Satinder Singh
A Nonlinear Predictive State Representation
3:10--3:30 ORAL
NS 09
Jonathan W. Pillow, Liam Paninski, Eero P. Simoncelli
Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model
3:30--4:00 BREAK
4:00--4:50 INVITED SPEAKER
Anders Dale
Relating Brain Imaging Signals to Biophysical Models of Neuronal Circuits
4:50--5:10 ORAL
BI 01
Maneesh Sahani, Srikantan S. Nagarajan
Reconstructing MEG Sources with Unknown Correlations
5:10--5:30 SPOTLIGHTS
BI 02
Saori Tanaka, Kenji Doya, Go Okada, Kazutaka Ueda, Yasumasa Okamoto, Shigeto Yamawaki
Different Cortico-Basal Ganglia Loops Specialize in Reward Prediction on Different Time Scales
BI 03
Xuerui Wang, Rebecca Hutchinson, Tom M. Mitchell
Training fMRI Classifiers to Detect Cognitive States Across Multiple Human Subjects
NS 10
Liam Paninski
Design of Experiments via Information Theory
NS 11
Konrad P. Koerding, Daniel M. Wolpert
Probabilistic Inference in Human Sensorimotor Learning
NS 12
Kazuyuki Samejima, Kenji Doya, Yasumasa Ueda, Minoru Kimura
Estimating Internal Variables and Parameters of a Learning Agent by a Particle Filter
NS 13
Bernd Porr, Ausra Saudargiene, Florentin Woergoetter
Analytical Solution of Spike-Timing Dependent Plasticity Based on Synaptic Biophysics
NS 14
Brian J. Fischer, Charles H. Anderson
A Probabilistic Model of Auditory Space Representation in the Barn Owl
SP 05
Jeff Bondy, Ian C. Bruce, Suzanna Becker, Simon Haykin
Predicting Speech Intelligibility from a Population of Neurons
CS 05
Woojae Kim, Daniel J. Navarro, Mark A. Pitt, In Jae Myung
An MCMC-based Method of Comparing Connectionist Models in Cognitive Science
THURSDAY – December 11, 2003:
8:30--9:20 INVITED SPEAKER
Elissa Newport
Statistical Language Learning in Human Infants and Adults
9:20--9:40 ORAL
CS 06
David Philipona, J. Kevin O'Regan, Jean-Pierre Nadal, Olivier J.-M. D. Coenen
Perception of the Structure of the Physical World using Unknown Multimodal Sensors and Effectors
9:40-10:00 ORAL
CS 07
Thomas L. Griffiths, Joshua B. Tenenbaum
From Algorithmic to Subjective Randomness
10:00-10:50 BREAK
10:50-11:10 ORAL
AA 44
Allan Borodin, Ran El-Yaniv, Vincent Gogan
Can We Learn to Beat the Best Stock
11:10-12:00 INVITED SPEAKER
Marc Mezard
Analytic and Algorithmic Solutions of Random Satisfiability Problems