Tutorials (December 4, 2006)


Tutorials Program

The pre-Conference Tutorials will be held at the Hyatt Regency Vancouver, British Columbia, Canada on December 4, 2006.

The Tutorials provides a choice of six two-hour tutorials by leading scientists. The topics span a wide range of subjects including neuroscience, learning algorithms and theory, bioinformatics, image processing, and data mining.

Tutorial Schedule and Slides

9:30 – 11:30am
Slides:Slides (PDF)Video:QuickTime Movie (320x240)Video:QuickTime Movie (640x480)Video:QuickTime Movie (900x600)
Carl Rasmussen
Advances in Gaussian Processes
9:30 – 11:30am
Slides:Slides (PDF)Video:Part 1 - QuickTime Movie (320x240)Video:Part 1 - QuickTime Movie (640x480)Video:Part 1 - QuickTime Movie (900x600)Video:Part 2 - QuickTime Movie (320x240)Video:Part 2 - QuickTime Movie (640x480)Video:Part 2 - QuickTime Movie (900x600)
Dan Klein
Machine Learning for Natural Language Processing: New Developments and Challenges
1:00 – 3:00pm
Slides:Slides (PDF)Slides:Slides (PowerPoint)Video:QuickTime Movie (320x240)Video:QuickTime Movie (640x480)Video:QuickTime Movie (900x600)
Maya Schuldiner, Nir Friedman
The Role of Computational Methods in Creating a Systems Level View from Biological Data
1:02 – 3:00pm
Slides:Slides (PowerPoint)Video:QuickTime Movie (320x240)Video:QuickTime Movie (640x480)Video:QuickTime Movie (900x600)
Josh Tenenbaum
Bayesian Models of Human Learning and Inference
3:00 – 3:30pm Coffee Break
3:30 – 5:30pm
Slides:Slides (PDF)Video:QuickTime Movie (320x240)Video:QuickTime Movie (640x480)Video:QuickTime Movie (900x600)
Brian A Wandell
Diffusion Tensor Imaging and Fiber Tracking of Human Brain Pathways
3:30 – 5:30pm
Slides:Slides (DjVu)Slides:Slides (PDF)Video:QuickTime Movie (320x240)Video:QuickTime Movie (640x480)Video:QuickTime Movie (900x600)
Yann LeCun
Energy-Based Models: Structured Learning Beyond Likelihoods

Conference Sessions (December 4–7, 2006)

6:30 – 8:30pm Opening Banquet
7:30pm – 12:00am Poster Session
7:30pm – 12:00am Demonstrations
8:30am Dan Ariely
Free Lunches: Insights from Behavioral Economics
9:30am Charles Kemp, Patrick Shafto, Allison Berke, Josh Tenenbaum
Combining causal and similarity-based reasoning
9:50am Eli Ben-Sasson, Adam T Kalai, Ehud Kalai
An Approach to Bounded Rationality
10:10am Michael D Lee, Ian Fuss, Daniel Navarro
A Bayesian Approach to Diffusion Models of Decision-Making and Response Time
10:10am Mohammad Ghavamzadeh, Yaakov Engel
Bayesian Policy Gradient Algorithms
10:10am Steffen Bickel, Tobias Scheffer
Dirichlet-Enhanced Spam Filtering based on Biased Samples
10:10am Sandeep Pandey, Christopher Olston
Handling Advertisements of Unknown Quality in Search Advertising
10:10am Huan Xu, Shie Mannor
The Robustness-Performance Tradeoff in Markov Decision Processes
10:20am Coffee Break
10:50am Nathan D Ratliff, David M Bradley, Drew Bagnell, Joel Chestnutt
Boosting Structured Prediction for Imitation Learning
11:10am Pieter Abbeel, Adam P Coates, Andrew Y Ng, Morgan Quigley
An Application of Reinforcement Learning to Aerobatic Helicopter Flight
11:30am Lorenzo Torresani, Peggy Hackney, Christoph Bregler
Learning Motion Style Synthesis from Perceptual Observations
11:50am Graham W Taylor, Geoffrey E Hinton, Sam T Roweis
Modeling Human Motion Using Binary Latent Variables
11:50am Konrad P Kording, Josh Tenenbaum, Reza Shadmehr
Multiple timescales and uncertainty in motor adaptation
11:50am Ashutosh Saxena, Justin Driemeyer, Justin Kearns, Andrew Y Ng
Robotic Grasping of Novel Objects
12:00 – 2:00pm Lunch (2 hours)
2:00pm Ralf Herbrich, Tom Minka, Thore K Graepel
TrueSkill: A Bayesian Skill Rating System
2:20pm Lin Wu, Pierre Baldi
A Scalable Machine Learning Approach to Go
2:40pm Cheng-Tao Chu, Sang Kyun Kim, Yi-An Lin, YuanYuan Yu, Gary N Bradski, Andrew Y Ng, Kunle Olukotun
Map-Reduce for Machine Learning on Multicore
3:00pm Geoffrey J Gordon
No-regret algorithms for Online Convex Programs
3:20pm Shai Shalev-Shwartz, Yoram Singer
Convex Repeated Games and Fenchel Duality
3:20pm Mark J Herbster, Massimiliano Pontil
Prediction on a Graph with a Perceptron
3:20pm Ofer Dekel, Yoram Singer
Support Vector Machines on a Budget
3:30pm Coffee Break
4:00pm Daniel M Roy, Charles Kemp, Vikash K Mansinghka, Josh Tenenbaum
Learning annotated hierarchies from relational data
4:20pm Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle
Greedy Layer-Wise Training of Deep Networks
4:40pm Arthur Gretton, Karsten Borgwardt, Malte J Rasch, Bernhard Schölkopf, Alex J Smola
A Kernel Method for the Two-Sample-Problem
5:00pm Kenichi Kurihara, Max Welling, Nikos Vlassis
Accelerated Variational Dirichlet Process Mixtures
5:00pm Jiayuan Huang, Alex J Smola, Arthur Gretton, Karsten Borgwardt, Bernhard Schölkopf
Correcting Sample Selection Bias by Unlabeled Data
5:00pm Martin J Wainwright, Pradeep K Ravikumar, John Lafferty
Inferring Graphical Model Structure using $\ell_1$-Regularized Pseudo-Likelihood
5:00pm Ted Meeds, Zoubin Ghahramani, Radford M Neal, Sam T Roweis
Modeling Dyadic Data with Binary Latent Features
5:00pm Alexandre Lacasse, Francois Laviolette, Mario Marchand, Pascal Germain, Nicolas Usunier
PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier
5:00pm David Barber, Silvia Chiappa
Unified Inference for Variational Bayesian Linear Gaussian State-Space Models
5:00pm John Duchi, Daniel Tarlow, Gal Elidan, Daphne Koller
Using Combinatorial Optimization within Max-Product Belief Propagation
7:30pm – 12:00am Poster Session
7:30pm – 12:00am Demonstrations
8:30am George Ojemann
Examining the Human Brain Mechanisms for Language, Memory, and Learning During Awake Neurosurgery
9:30am Mate Lengyel, Peter Dayan
Uncertainty, phase and oscillatory hippocampal recall
9:50am Jeremy Lewi, Robert Butera, Liam M Paninski
Real-time adaptive information-theoretic optimization of neurophysiological experiments
10:10am Alexis Battle, Gal Chechik, Daphne Koller
Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Task
10:30am Coffee Break
11:00am Matthias Hein, Markus M Maier
Manifold Denoising
11:20am Ivor W Tsang, James T Kwok
Large-Scale Sparsified Manifold Regularization
11:40am Marc'Aurelio Ranzato, Christopher Poultney, Sumit Chopra, Yann LeCun
Efficient Learning of Sparse Representations with an Energy-Based Model
11:40am Yi Li, Phil Long
Learnability and the doubling dimension
11:40am Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller
Max-margin classification of incomplete data
11:40am Zhi-Hua Zhou, Min-Ling Zhang
Multi-Instance Multi-Label Learning with Application to Scene Classification
11:40am Ling Li, Hsuan-Tien Lin
Ordinal Regression by Extended Binary Classification
11:40am Joseph Turian, Benjamin Wellington, Dan Melamed
Scalable Discriminative Learning for Natural Language Parsing and Translation
12:00 – 2:00pm Lunch (2 hours)
2:00pm David Baker
Global Optimization Challenges in High Resolution Protein Structure Prediction
3:00pm KyungAh Sohn, Eric P Xing
A Hidden Markov Dirichlet Process Model for Genetic Recombination in Open Ancestral Space
3:20pm David P Wipf, Rey R Ramirez, Jason A Palmer, Scott Makeig, Bhaskar Rao
Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization
3:20pm Hideaki Shimazaki, Shigeru Shinomoto
A recipe for optimizing a time-histogram
3:20pm Jennifer Listgarten, Radford M Neal, Sam T Roweis, Rachel Puckrin, Sean Cutler
Bayesian Detection of Infrequent Differences in Sets of Time Series with Shared Structure
3:20pm Elisabetta Chicca, Giacomo Indiveri, Rodney J Douglas
Context dependent amplification of both rate and event-correlation in a VLSI network of spiking neurons
3:20pm Luis Perez-Breva, Luis E Ortiz, Chen-Hsiang Yeang, Tommi Jaakkola
Game Theoretic Algorithms for Protein-DNA binding
3:20pm Ryota Tomioka, Kazuyuki Aihara, Klaus-Robert Müller
Logistic Regression for Single Trial EEG Classification
3:20pm Tobias Sing, Niko Beerenwinkel
Mutagenetic tree Fisher kernel improves prediction of HIV drug resistance from viral genotype
3:30pm Coffee Break
4:00pm Anitha Kannan, John Winn, Carsten Rother
Clustering appearance and shape by learning jigsaws
4:20pm Jonathan Harel, Christof Koch, Pietro Perona
Graph-Based Visual Saliency
4:40pm Ce Liu, William Freeman, Edward Adelson
Analysis of Contour Motions
5:00pm Fei Sha, Lawrence Saul
Large Margin Gaussian Mixture Models for Automatic Speech Recognition
5:20pm Amit Kagian, Gideon Dror, Tommer Leyvand, Daniel Cohen-Or, Eytan Ruppin
A Humanlike Predictor of Facial Attractiveness
5:20pm Kristen Grauman, Trevor Darrell
Approximate Correspondences in High Dimensions
5:20pm Eizaburo Doi, Michael S Lewicki
A Theory of Retinal Population Coding
5:20pm Lyndsey C Pickup, David Capel, Stephen J Roberts, Andrew Zisserman
Bayesian Image Super-resolution, Continued
5:20pm John R Hershey, Trausti Kristjansson, Steven J Rennie, Peder A Olsen
Single Channel Speech Separation Using Layered Hidden Markov Models
5:20pm Roger Levy, T. Florian Jaeger
Speakers optimize information density through syntactic reduction
5:20pm Aharon Bar Hillel, Daphna Weinshall
Subordinate class recognition using relational object models
7:30pm – 12:00am Poster Session
8:30am Daniel Margoliash
Neural Mechanisms of Auditory Pattern Processing and Pattern Learning in Songbirds
8:30 – 11:00am Morning session - speaker information will be available soon
9:30am Long Zhu, Yuanhao Chen, Alan L Yuille
Unsupervised Learning of a Probabilistic Grammar for Object Detection and Parsing
9:50am Coffee Break
10:20am Hugh Chipman, Edward George, Robert McCulloch
Bayesian Ensemble Learning
10:40am Amir Globerson, Tommi Jaakkola
Approximate inference using planar graph decomposition
11:00am James S Clark
Emerging Capacity to Synthesize Data and Process: Application to the Biodiversity Paradox
11:00am Conference End

Workshops (December 8–9, 2006)



The post-Conference Workshops will be held at the Westin Resort and Spa and the Westin Hilton in Whistler, British Columbia, Canada on December 8 and 9, 2006.

The Workshops provide multi-track intensive sessions on a wide range of topics. The venue and schedule facilitate informality and depth. Please see a list of Workshops below, along with links to further information for each.


Andre Elisseeff
Causality and feature selection
Si Wu, Thomas Trappenberg
Continuous Attractor Neural Networks
Leonid Sigal, Ming-Hsuan Yang, Michael J Black
EHuM: Evaluation of Articulated Human Motion and Pose Estimation
Michael James, David Wingate, Brian Tanner
Grounding Perception, Knowledge and Cognition in Sensori-Motor Experience
David Grangier, Samy Bengio
Learning to Compare Examples
John-Dylan Haynes, Tom M Mitchell, Francisco Pereira
New directions on decoding mental states from fMRI data
Quaid D Morris, Gal Chechik, Koji Tsuda, Gunnar Rätsch, Christina S Leslie, William S Noble
New Problems and Methods in Computational Biology
Peter Auer
On-line Trading of Exploration and Exploitation
Naftali Tishby
Revealing Hidden Elements of Dynamical Systems
Kiri L Wagstaff, Chris Drummond, Dragos D Margineantu
Testing of Deployable Learning & Decision Systems
Jan R Peters, Stefan Schaal, Drew Bagnell
Towards a New Reinforcement Learning?
Shie Mannor
User Adaptive Systems
6:30 – 8:30am Breakfast
7:30 – 10:30am Morning Session
10:30am – 3:30pm Break
3:30 – 6:30pm Afternoon Session
6:30 – 8:00pm Reception and Registration
David Barber
Advances in Models for Acoustic Processing
Klaus-Robert Müller, José del R. Millán, Matthias Krauledat, Roderick Murray-Smith, Benjamin Blankertz
Current Trends in Brain-Computer Interfacing
Eric Thomson, Bill Kristan, Terrence J Sejnowski
Decoding the neural code
Manfred Opper, Cedric Archambeau, John S Shawe-Taylor
Dynamical Systems, Stochastic Processes and Bayesian Inference
Herbert Jaeger, Wolfgang Maass, Jose C Principe
Echo State Networks and Liquid State Machines
Greg Grudic
Learning Applied to Ground Robots: Sensing and Locomotion
Joaquin Quiñonero Candela, Masashi Sugiyama, Anton Schwaighofer, Neil D Lawrence
Learning when test and training inputs have different distributions
Cyril Goutte
Machine Learning for Multilingual Information Access
Isabelle Guyon
Multi-level Inference Workshop and Model Selection Game
John Blitzer, Rajarshi Das, Irina Rish, Kilian Q Weinberger
Novel Applications of Dimensionality Reduction
Adam M White
The First Annual Reinforcement Learning Competition
Soeren Sonnenburg
Workshop On Machine Learning Open Source Software
6:30 – 8:30am Breakfast
7:30 – 10:30am Morning Session
10:30am – 3:30pm Break
3:30 – 6:30pm Afternoon Session
7:30 – 11:30pm Closing Banquet

The schedule was last modified on 2014-2-23 21:02 PST