Monday 
6:30 – 7:30pm 
Opening Banquet 
7:30 – 8:00pm 
Luis von Ahn Human Computation 
8:10 – 8:25pm 
SpotlightsSpotlights Czar:Dale Schuurmans 


K. Toutanova, M. Johnson
A Bayesian LDAbased model for semisupervised partofspeech tagging

M. Hoffman, A. Doucet, N. de Freitas, A. Jasra
Bayesian Policy Learning with TransDimensional MCMC

P. Long, R. Servedio
Boosting the Area under the ROC Curve

D. Lashkari, P. Golland
Convex Clustering with ExemplarBased Models

C. Teo, A. Globerson, S. Roweis, A. Smola
Convex Learning with Invariances

C. Frogner, A. Pfeffer
Discovering WeaklyInteracting Factors in a Complex Stochastic Process

S. Petrov, D. Klein
Discriminative LogLinear Grammars with Latent Variables

L. Nguyen, M. Wainwright, M. Jordan
Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization

A. Howard, T. Jebara
Learning Monotonic Transformations for Classification

C. Walder, O. Chapelle
Learning with Transformation Invariant Kernels

M. Zinkevich, M. Johanson, M. Bowling, C. Piccione
Regret Minimization in Games with Incomplete Information

B. Blum, D. Baker, M. Jordan, P. Bradley, R. Das, D. Kim
Resampling Methods for Protein Structure Prediction with Rosetta

J. Lafferty, L. Wasserman
Statistical Analysis of SemiSupervised Regression

A. Kulesza, F. Pereira
Structured Learning with Approximate Inference

K. Sinha, M. Belkin
The Value of Labeled and Unlabeled Examples when the Model is Imperfect

8:30pm – 12:00am 
Poster Session 


M. Zinkevich, M. Johanson, M. Bowling, C. Piccione
Regret Minimization in Games with Incomplete Information

M. Johanson, M. Zinkevich, M. Bowling
Computing Robust CounterStrategies

E. Hazan, S. Kale
Computational Equivalence of Fixed Points and No Regret Algorithms, and Convergence to Equilibria

J. Goldsmith, M. Mundhenk
Competition Adds Complexity

Y. Tassa, T. Erez, B. Smart
Receding Horizon Differential Dynamic Programming

C. Atkeson, B. Stephens
Random Sampling of States in Dynamic Programming

M. Hoffman, A. Doucet, N. de Freitas, A. Jasra
Bayesian Policy Learning with TransDimensional MCMC

S. Ross, J. Pineau, B. Chaibdraa
Theoretical Analysis of Heuristic Search Methods for Online POMDPs

A. Tewari, P. Bartlett
Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs

J. Langford, T. Zhang
The EpochGreedy Algorithm for Multiarmed Bandits with Side Information

A. Strehl, M. Littman
Online Linear Regression and Its Application to ModelBased Reinforcement Learning

V. Manfredi, J. Kurose
Scan Strategies for Meteorological Radars

B. Blum, D. Baker, M. Jordan, P. Bradley, R. Das, D. Kim
Resampling Methods for Protein Structure Prediction with Rosetta

L. Cayton, S. Dasgupta
A learning framework for nearest neighbor search

N. Le Roux, P. Manzagol, Y. Bengio
Topmoumoute Online Natural Gradient Algorithm

M. Holmes, A. Gray, C. Isbell
MultiStage Monte Carlo Approximation for Fast Generalized Data Summations

D. Lashkari, P. Golland
Convex Clustering with ExemplarBased Models

C. Hegde, R. Baraniuk
Random Projections for Manifold Learning

Y. Freund, S. Dasgupta, M. Kabra, N. Verma
Learning the structure of manifolds using random projections

P. Li, T. Hastie
A Unified NearOptimal Estimator For Dimension Reduction in $l_\alpha$ ($0<\alpha\leq 2$) Using Sta

P. Hoff
Modeling homophily and stochastic equivalence in symmetric relational data

K. Sinha, M. Belkin
The Value of Labeled and Unlabeled Examples when the Model is Imperfect

Y. Guo, D. Schuurmans
Discriminative Batch Mode Active Learning

B. Settles, M. Craven, S. Ray
Multiple Instance Active Learning

E. Brochu, N. de Freitas, A. Ghosh
Active Preference Learning with Discrete Choice Data

L. Bottou, O. Bousquet
The Tradeoffs of Large Scale Learning

J. Blitzer, K. Crammer, A. Kulesza, F. Pereira, J. Vaughan
Learning Bounds for Domain Adaptation

M. Mohri, A. Rostamizadeh
Stability Bounds for Noni.i.d. Processes

A. Howard, T. Jebara
Learning Monotonic Transformations for Classification

S. Zhou, J. Lafferty, L. Wasserman
Compressed Regression

J. Lafferty, L. Wasserman
Statistical Analysis of SemiSupervised Regression

P. Long, R. Servedio
Boosting the Area under the ROC Curve

M. Barreno, A. Cárdenas, D. Tygar
Optimal ROC Curve for a Combination of Classifiers

Z. Harchaoui, C. LévyLeduc
Catching Changepoints with Lasso

D. Wipf, S. Nagarajan
A New View of Automatic Relevance Determination

R. Luss, A. d'Aspremont
Support Vector Machine Classification with Indefinite Kernels

F. Richardson, W. Campbell
Discriminative Keyword Selection Using Support Vector Machines

L. Nguyen, M. Wainwright, M. Jordan
Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization

C. Walder, O. Chapelle
Learning with Transformation Invariant Kernels

R. Salakhutdinov, G. Hinton
Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes

C. Do, C. Foo, A. Ng
Efficient multiple hyperparameter learning for loglinear models

A. Kulesza, F. Pereira
Structured Learning with Approximate Inference

Y. Guo, D. Schuurmans
Convex Relaxations of EM

A. Chechetka, C. Guestrin
Efficient Principled Learning of Thin Junction Trees

S. Sanghavi, D. Malioutov, A. Willsky
Linear programming analysis of loopy belief propagation for weighted matching

A. Globerson, T. Jaakkola
Fixing MaxProduct: Convergent Message Passing Algorithms for MAP LPRelaxations

K. Jung, D. Shah
Local Algorithms for Approximate Inference in MinorExcluded Graphs

V. Chandrasekaran, J. Johnson, A. Willsky
Adaptive Embedded Subgraph Algorithms using WalkSum Analysis

L. Ortiz
CPR for CSPs: A Probabilistic Relaxation of Constraint Propagation

J. Platt, E. Kiciman, D. Maltz
Fast Variational Inference for Largescale Internet Diagnosis

C. Frogner, A. Pfeffer
Discovering WeaklyInteracting Factors in a Complex Stochastic Process

V. Raykar, H. Steck, B. Krishnapuram, C. DehingOberije, P. Lambin
On Ranking in Survival Analysis: Bounds on the Concordance Index

M. Ranzato, Y. Boureau, Y. LeCun
Sparse Feature Learning for Deep Belief Networks

S. Osindero, G. Hinton
Modeling image patches with a directed hierarchy of Markov random fields

Z. Lu, M. CarreiraPerpinan, C. Sminchisescu
People Tracking with the Laplacian Eigenmaps Latent Variable Model

D. Tran, D. Forsyth
Configuration Estimates Improve Pedestrian Finding

Y. Chen, L. Zhu, C. Lin, A. Yuille, H. Zhang
Rapid Inference on a novel AND/OR graph: Detection, Segmentation and Parsing of Articulated Deformable Objects in Cluttered Backgrounds

X. Wang, E. Grimson
Spatial Latent Dirichlet Allocation

S. Boutemedjet, D. Ziou, N. Bouguila
A Unified Model for Content Based Image Suggestion and Feature Selection

C. Zhang, P. Viola
MultipleInstance Pruning For Learning Efficient Cascade Detectors

A. BouchardCôté, P. Liang, T. Griffiths, D. Klein
A Probabilistic Approach to Language Change

S. Petrov, D. Klein
Discriminative LogLinear Grammars with Latent Variables

K. Toutanova, M. Johnson
A Bayesian LDAbased model for semisupervised partofspeech tagging

B. Zhao, E. Xing
HMBiTAM: Bilingual Topic Exploration, Word Alignment, and Translation

D. Blei, J. McAuliffe
Supervised Topic Models

E. Linstead, P. Rigor, s. bajracharya, c. lopes, P. Baldi
Mining InternetScale Software Repositories

B. Carterette, R. Jones
Evaluating Search Engines by Modeling the Relationship Between Relevance and Clicks

D. Eck, P. Lamere, T. BertinMahieux, S. Green
Automatic Generation of Social Tags for Music Recommendation

E. Sudderth, M. Wainwright, A. Willsky
Loop Series and Bethe Variational Bounds in Attractive Graphical Models

C. Teo, A. Globerson, S. Roweis, A. Smola
Convex Learning with Invariances

8:30pm – 12:00am 
Demonstrations 


Y. Freund, E. Ettinger, B. McFee, D. Goshorn, S. Shivappa
Automatic Cameraman

A. Saxena, m. sun, A. Ng
Building a 3D Model From a Single Still Image

E. Neftci, E. Chicca, G. Indiveri, J. Slotine, R. Douglas
Contraction of VLSI Spiking Neurons

K. Gawande, A. Smola, V. S V N, L. Cheng, S. Guenter
Elefant

W. Xu, K. Yu, Y. Gong
Gender and Age Recognition

T. Graepel, P. Trelford, R. Herbrich, M. Kochenderfer
Learning To Race by ModelBased Reinforcement Learning with Adaptive Abstraction

M. Cerf, C. Koch
Predicting Human Gaze Using Lowlevel Saliency Combined with Face Detection

P. Forssen, D. Pai
Robotic Eye Model with Learning of PulseStep Saccades

Tuesday 
7:30 – 9:00am 
Breakfast 
8:00am – 6:00pm 
Registration 
8:30 – 9:50am 
Session 1: Structured Statistical ModelsSession Chair:Michael J Black 


9:50 – 10:00am 
SpotlightsSpotlights Czar:Stefan Schaal 


M. Weimer, A. Karatzoglou, Q. Le, A. Smola
COFI RANK  Maximum Margin Matrix Factorization for Collaborative Ranking

T. Jebara, Y. Song, K. Thadani
Density Estimation under Independent Similarly Distributed Sampling Assumptions

S. Oba, M. Kawanabe, K. Müller, S. Ishii
Heterogeneous Component Analysis

R. Silva, W. Chu, Z. Ghahramani
Hidden Common Cause Relations in Relational Learning

M. Welling, I. Porteous, E. Bart
Infinite State BayesNets for Structured Domains

Q. Liu, X. Liao, L. Carin
SemiSupervised Multitask Learning

P. Ravikumar, H. Liu, J. Lafferty, L. Wasserman
SpAM: Sparse Additive Models

P. Dangauthier, R. Herbrich, T. Minka, T. Graepel
TrueSkill Through Time: Revisiting the History of Chess

10:00 – 10:30am 
Break 
10:30 – 11:50am 
Session 2: Probabilistic OptimizationSession Chair:Francis Bach 


11:50am – 12:00pm 
SpotlightsSpotlights Czar:Stefan Schaal 


T. van Erven, P. Grunwald, S. de Rooij
Catching Up Faster in Bayesian Model Selection and Model Averaging

Y. Teh, K. Kurihara, M. Welling
Collapsed Variational Inference for HDP

D. Sheldon, M. Elmohamed, D. Kozen
Collective Inference on Markov Models for Modeling Bird Migration

D. Newman, A. Asuncion, P. Smyth, M. Welling
Distributed Inference for Latent Dirichlet Allocation

M. Szafranski, Y. Grandvalet, P. MorizetMahoudeaux
Hierarchical Penalization

S. Sanghavi, D. Shah, A. Willsky
Message Passing for Maxweight Independent Set

M. Kearns, J. Tan, J. Vaughan
PrivacyPreserving Belief Propagation and Sampling

A. NaishGuzman, S. Holden
The Generalized FITC Approximation

12:00 – 2:00pm 
Lunch 
2:00 – 3:00pm 
Yair Censor Projection Methods: Algorithmic Structures, Bregman Projections, and Acceleration Techniques 
3:00 – 3:20pm 
Peter L Bartlett, Elad Hazan, Sasha Rakhlin Adaptive Online Gradient Descent 
3:20 – 3:30pm 
SpotlightsSpotlights Czar:Dan Klein 


A. Gretton, K. Fukumizu, C. Teo, L. Song, B. Schölkopf, A. Smola
A Kernel Statistical Test of Independence

S. Esmeir, S. Markovitch
Anytime Induction of Costsensitive Trees

M. Warmuth, K. Glocer, G. Rätsch
Boosting Algorithms for Maximizing the Soft Margin

A. Smola, V. S V N, Q. Le
Bundle Methods for Machine Learning

J. Wright, Y. Tao, Z. Lin, Y. Ma, H. Shum
Classification via Minimum Incremental Coding Length (MICL)

M. Gashler, D. Ventura, T. Martinez
Iterative Nonlinear Dimensionality Reduction with Manifold Sculpting

P. Li, C. Burges, Q. Wu
McRank: Learning to Rank Using Multiple Classification and Gradient Boosting

a. rahimi, B. Recht
Random Features for LargeScale Kernel Machines

U. Von Luxburg, S. Bubeck, S. Jegelka, M. Kaufmann
Consistent Minimization of Clustering Objective Functions

3:30 – 4:00pm 
Break 
4:00 – 5:40pm 
Session 3: Theory and Sequential Decision MakingSession Chair:Sanjoy Dasgupta 


5:20 – 5:30pm 
SpotlightsSpotlights Czar:Dan Klein 


S. Dasgupta, D. Hsu, C. Monteleoni
A general agnostic active learning algorithm

S. Ross, B. Chaibdraa, J. Pineau
BayesAdaptive POMDPs

J. Kolter, P. Abbeel, A. Ng
Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion

S. Bhatnagar, R. Sutton, M. Ghavamzadeh, M. Lee
Incremental Natural ActorCritic Algorithms

G. Tesauro, R. Das, H. Chan, J. Kephart, D. Levine, F. Rawson, C. Lefurgy
Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning

A. Lazaric, M. Restelli, A. Bonarini
Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods

A. Krause, H. McMahan, C. Guestrin, A. Gupta
Selecting Observations against Adversarial Objectives

T. Wang, D. Lizotte, M. Bowling, D. Schuurmans
Stable Dual Dynamic Programming

D. Hsu, W. Lee, N. Rong
What makes some POMDP problems easy to approximate?

7:30pm – 12:00am 
Poster Session 


T. Wang, D. Lizotte, M. Bowling, D. Schuurmans
Stable Dual Dynamic Programming

S. Ross, B. Chaibdraa, J. Pineau
BayesAdaptive POMDPs

D. Hsu, W. Lee, N. Rong
What makes some POMDP problems easy to approximate?

S. Bhatnagar, R. Sutton, M. Ghavamzadeh, M. Lee
Incremental Natural ActorCritic Algorithms

A. Lazaric, M. Restelli, A. Bonarini
Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods

A. Antos, R. Munos, C. Szepesvari
Fitted Qiteration in continuous actionspace MDPs

M. Hutter, S. Legg
Temporal Difference with Eligibility Traces Derived from First Principles

G. Tesauro, R. Das, H. Chan, J. Kephart, D. Levine, F. Rawson, C. Lefurgy
Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning

J. Kolter, P. Abbeel, A. Ng
Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion

U. Syed, R. Schapire
A Multiplicative Weights Algorithm for Apprenticeship Learning

V. Dani, T. Hayes, S. Kakade
The Price of Bandit Information for Online Optimization

P. Bartlett, E. Hazan, S. Rakhlin
Adaptive Online Gradient Descent

S. Dasgupta, D. Hsu, C. Monteleoni
A general agnostic active learning algorithm

J. Audibert
Progressive mixture rules are deviation suboptimal

M. Warmuth, K. Glocer, G. Rätsch
Boosting Algorithms for Maximizing the Soft Margin

K. Pelckmans, J. Suykens, B. De Moor
A Risk Minimization Principle for a Class of Parzen Estimators

A. Smola, V. S V N, Q. Le
Bundle Methods for Machine Learning

U. Von Luxburg, S. Bubeck, S. Jegelka, M. Kaufmann
Consistent Minimization of Clustering Objective Functions

O. Shamir, N. Tishby
Cluster Stability for Finite Samples

R. Salakhutdinov, A. Mnih
Probabilistic Matrix Factorization

M. Weimer, A. Karatzoglou, Q. Le, A. Smola
COFI RANK  Maximum Margin Matrix Factorization for Collaborative Ranking

L. Song, A. Smola, K. Borgwardt, A. Gretton
Colored Maximum Variance Unfolding

M. Gashler, D. Ventura, T. Martinez
Iterative Nonlinear Dimensionality Reduction with Manifold Sculpting

G. Burghouts, A. Smeulders, J. Geusebroek
The Distribution Family of Similarity Distances

S. Oba, M. Kawanabe, K. Müller, S. Ishii
Heterogeneous Component Analysis

J. Ye, Z. Zhao, M. Wu
Discriminative Kmeans for Clustering

F. Bach, Z. Harchaoui
DIFFRAC: a discriminative and flexible framework for clustering

K. Chen, S. Wang
Regularized Boost for SemiSupervised Learning

Q. Liu, X. Liao, L. Carin
SemiSupervised Multitask Learning

Z. Xu, R. Jin, J. Zhu, I. King, M. Lyu
Efficient Convex Relaxation for Transductive Support Vector Machine

K. Kumar, C. Bhattacharyya, R. Hariharan
A Randomized Algorithm for Large Scale Support Vector Learning

a. rahimi, B. Recht
Random Features for LargeScale Kernel Machines

T. Kato, H. Kashima, M. Sugiyama, K. Asai
MultiTask Learning via Conic Programming

S. Esmeir, S. Markovitch
Anytime Induction of Costsensitive Trees

E. Chang, K. Zhu, H. Wang, h. Bai, J. Li, Z. Qiu, H. Cui
Parallelizing Support Vector Machines on Distributed Computers

J. Bradley, R. Schapire
FilterBoost: Regression and Classification on Large Datasets

P. Li, C. Burges, Q. Wu
McRank: Learning to Rank Using Multiple Classification and Gradient Boosting

Z. Zheng, H. Zha, T. Zhang, O. Chapelle, K. Chen, G. Sun
A General Boosting Method and its Application to Learning Ranking Functions for Web Search

J. Wright, Y. Tao, Z. Lin, Y. Ma, H. Shum
Classification via Minimum Incremental Coding Length (MICL)

C. Gentile, F. Vitale, C. Brotto
On higherorder perceptron algorithms

M. Szafranski, Y. Grandvalet, P. MorizetMahoudeaux
Hierarchical Penalization

D. Sontag, T. Jaakkola
New Outer Bounds on the Marginal Polytope

P. Mudigonda, V. Kolmogorov, P. Torr
An Analysis of Convex Relaxations for MAP Estimation

S. Sanghavi, D. Shah, A. Willsky
Message Passing for Maxweight Independent Set

M. Kearns, J. Tan, J. Vaughan
PrivacyPreserving Belief Propagation and Sampling

J. Verbeek, B. Triggs
Scene Segmentation with CRFs Learned from Partially Labeled Images

M. Mahdaviani, T. Choudhury
Fast and Scalable Training of SemiSupervised CRFs with Application to Activity Recognition

D. Sheldon, M. Elmohamed, D. Kozen
Collective Inference on Markov Models for Modeling Bird Migration

P. Dangauthier, R. Herbrich, T. Minka, T. Graepel
TrueSkill Through Time: Revisiting the History of Chess

J. HernándezLobato, T. Dijkstra, T. Heskes
Regulator Discovery from Gene Expression Time Series of Malaria Parasites: a Hierachical Approach

C. Archambeau, M. Opper, Y. Shen, D. Cornford, J. ShaweTaylor
Variational Inference for Diffusion Processes

M. Opper, G. Sanguinetti
Variational inference for Markov jump processes

Y. Teh, K. Kurihara, M. Welling
Collapsed Variational Inference for HDP

D. Newman, A. Asuncion, P. Smyth, M. Welling
Distributed Inference for Latent Dirichlet Allocation

M. Welling, I. Porteous, E. Bart
Infinite State BayesNets for Structured Domains

M. Titsias
The Infinite GammaPoisson Feature Model

M. Shashanka, B. Raj, P. Smaragdis
Sparse Overcomplete Latent Variable Decomposition of Counts Data

T. Jebara, Y. Song, K. Thadani
Density Estimation under Independent Similarly Distributed Sampling Assumptions

M. Sugiyama, S. Nakajima, H. Kashima, P. von Buenau, M. Kawanabe
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation

T. van Erven, P. Grunwald, S. de Rooij
Catching Up Faster in Bayesian Model Selection and Model Averaging

R. Silva, W. Chu, Z. Ghahramani
Hidden Common Cause Relations in Relational Learning

S. Zhu, K. Yu, Y. Gong
Predictive MatrixVariate t Models

P. Ravikumar, H. Liu, J. Lafferty, L. Wasserman
SpAM: Sparse Additive Models

A. NaishGuzman, S. Holden
The Generalized FITC Approximation

K. Yu, W. Chu
Gaussian Process Models for Link Analysis and Transfer Learning

A. NaishGuzman, S. Holden
Robust Regression with Twinned Gaussian Processes

A. Krause, H. McMahan, C. Guestrin, A. Gupta
Selecting Observations against Adversarial Objectives

A. Gretton, K. Fukumizu, C. Teo, L. Song, B. Schölkopf, A. Smola
A Kernel Statistical Test of Independence

Z. Harchaoui, F. Bach, M. Eric
Testing for Homogeneity with Kernel Fisher Discriminant Analysis

A. LecchiniVisintini, J. Lygeros, J. Maciejowski
Simulated Annealing: Rigorous finitetime guarantees for optimization on continuous domains

7:30pm – 12:00am 
Demonstrations 


K. Adiloglu, R. Anniés, Y. Visell, K. Franinovic, C. Drioli
Adaptive Bottle

R. Hearn, R. Granger
Basalgangliainspired Hierarchical Reinforcement Learning in an AIBO robot

A. Saffari Azar Alamdari, I. Guyon, H. Escalante, G. Bakir, G. Cawley
CLOP: a Matlab Learning Object Package

S. Gould, M. Quigley, A. Ng, D. Koller
Holistic Scene Understanding from Visual and Range Data

M. van de Panne, K. Yin, S. Coros, K. Loken
Robust Biped Locomotion Using Simple Lowdimensional Control Policies

D. Touretzky, E. TiraThompson
Tekkotsu Cognitive Robotics

E. Tsang, S. LAM, B. Shi
Visualization of DepthMotion Perception by Model Cortical Neurons

Wednesday 
7:30 – 9:00am 
Breakfast 
8:00am – 6:00pm 
Registration 
8:30 – 9:50am 
Session 4: Probabilistic Models and MethodsSession Chair:William S Noble 


9:50 – 10:00am 
SpotlightsSpotlights Czar:Ulrike Von Luxburg 


P. Liang, D. Klein, M. Jordan
AgreementBased Learning

F. Sinz, O. Chapelle, A. Agarwal, B. Schölkopf
An Analysis of Inference with the Universum

N. Chapados, Y. Bengio
Augmented Functional Time Series Representation and Forecasting with Gaussian Processes

S. Yu, B. Krishnapuram, R. Rosales, H. Steck, R. Rao
Bayesian MultiView Learning

L. Sigal, A. Balan, M. Black
Combined discriminative and generative articulated pose and nonrigid shape estimation

H. Chieu, W. Lee, Y. Teh
Cooled and Relaxed Survey Propagation for MRFs

O. Sumer, U. Acar, A. Ihler, R. Mettu
Efficient Bayesian Inference for Dynamically Changing Graphs

K. Ganchev, J. Graca, B. Taskar
Expectation Maximization, Posterior Constraints, and Statistical Alignment

E. Bonilla, K. Chai, C. Williams
Multitask Gaussian Process Prediction

A. LecchiniVisintini, J. Lygeros, J. Maciejowski
Simulated Annealing: Rigorous finitetime guarantees for optimization on continuous domains

10:00 – 10:30am 
Break 
10:30 – 11:50am 
Session 5: Probabilistic Representations and LearningSession Chair:Yee Whye Teh 


11:50am – 12:00pm 
SpotlightsSpotlights Czar:Ulrike Von Luxburg 


A. Argyriou, C. Micchelli, M. Pontil, Y. Ying
A Spectral Regularization Framework for MultiTask Structure Learning

T. Sharpee
Better than least squares: comparison of objective functions for estimating linearnonlinear models

V. Singh, L. Mukherjee, J. Peng, J. Xu
Ensemble Clustering using Semidefinite Programming

M. Mozer, D. Baldwin
ExperienceGuided Search: A Theory of Attentional Control

A. Christmann, I. Steinwart
How SVMs can estimate quantiles and the median

K. Fukumizu, A. Gretton, X. Sun, B. Schölkopf
Kernel Measures of Conditional Dependence

J. He, J. Carbonell
NearestNeighborBased Active Learning for Rare Category Detection

Z. Barutcuoglu, P. Long, R. Servedio
OnePass Boosting

M. Mahmud, S. Ray
Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations

12:00 – 2:00pm 
Lunch 
2:00 – 3:20pm 
Session 6: Cognitive ProcessesSession Chair:Mark Steyvers 


3:20 – 3:30pm 
SpotlightsSpotlights Czar:Chris Williams 


M. Frank, N. Goodman, J. Tenenbaum
A Bayesian Framework for CrossSituational WordLearning

U. Beierholm, K. Kording, L. Shams, W. Ma
Comparing Bayesian models for multisensory cue combination without mandatory integration

R. Peters, L. Itti
Congruence between model and human attention reveals unique signatures of critical visual events

V. Ferrari, A. Zisserman
Learning Visual Attributes

B. Russell, A. Torralba, C. Liu, R. Fergus, W. Freeman
Object Recognition by Scene Alignment

V. Rao, M. Howard
Retrieved context and the discovery of semantic structure

P. Frazier, A. Yu
Sequential Hypothesis Testing under Stochastic Deadlines

M. Figueroa, G. Carvajal, W. Valenzuela
SubspaceBased Face Recognition in Analog VLSI

R. Legenstein, D. Pecevski, W. Maass
Theoretical Analysis of Learning with RewardModulated SpikeTimingDependent Plasticity

3:30 – 4:00pm 
Break 
4:00 – 5:30pm 
Session 7: Systems and ApplicationsSession Chair:Fei Sha 


5:20 – 5:30pm 
SpotlightsSpotlights Czar:Chris Williams 


D. Sridharan, B. Percival, j. arthur, K. Boahen
An insilico Neural Model of Dynamic Routing through Neuronal Coherence

E. Neftci, E. Chicca, G. Indiveri, J. Slotine, R. Douglas
Contraction Properties of VLSI Cooperative Competitive Neural Networks of Spiking Neurons

S. LAM, B. Shi
Extending position/phaseshift tuning to motion energy neurons improves velocity discrimination

J. Cunningham, B. Yu, K. Shenoy, M. Sahani
Inferring Neural Firing Rates from Spike Trains Using Gaussian Processes

B. Blankertz, M. Kawanabe, R. Tomioka, F. Hohlefeld, V. Nikulin, K. Müller
Invariant Common Spatial Patterns: Alleviating Nonstationarities in BrainComputer Interfacing

J. Dauwels, F. Vialatte, T. Rutkowski, A. CICHOCKI
Measuring Neural Synchrony by Message Passing

M. Bethge, P. Berens
NearMaximum Entropy Models for Binary Neural Representations of Natural Images

N. Daw, A. Courville
The rat as particle filter

7:30pm – 12:00am 
Poster Session 


M. Mozer, D. Baldwin
ExperienceGuided Search: A Theory of Attentional Control

A. Yuille, H. Lu
The NoisyLogical Distribution and its Application to Causal Inference

Z. Barutcuoglu, P. Long, R. Servedio
OnePass Boosting

V. Singh, L. Mukherjee, J. Peng, J. Xu
Ensemble Clustering using Semidefinite Programming

K. Fukumizu, A. Gretton, X. Sun, B. Schölkopf
Kernel Measures of Conditional Dependence

A. Christmann, I. Steinwart
How SVMs can estimate quantiles and the median

T. Sharpee
Better than least squares: comparison of objective functions for estimating linearnonlinear models

M. Mahmud, S. Ray
Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations

A. Argyriou, C. Micchelli, M. Pontil, Y. Ying
A Spectral Regularization Framework for MultiTask Structure Learning

J. He, J. Carbonell
NearestNeighborBased Active Learning for Rare Category Detection

P. Liang, D. Klein, M. Jordan
AgreementBased Learning

K. Ganchev, J. Graca, B. Taskar
Expectation Maximization, Posterior Constraints, and Statistical Alignment

Y. Teh, H. Daume III, D. Roy
Bayesian Agglomerative Clustering with Coalescents

S. Kirshner
Learning with TreeAveraged Densities and Distributions

D. Endres, M. Oram, J. Schindelin, P. Foldiak
Bayesian binning beats approximate alternatives: estimating peristimulus time histograms

H. Chieu, W. Lee, Y. Teh
Cooled and Relaxed Survey Propagation for MRFs

S. Yu, B. Krishnapuram, R. Rosales, H. Steck, R. Rao
Bayesian MultiView Learning

O. Sumer, U. Acar, A. Ihler, R. Mettu
Efficient Bayesian Inference for Dynamically Changing Graphs

F. Sinz, O. Chapelle, A. Agarwal, B. Schölkopf
An Analysis of Inference with the Universum

G. Lebanon, Y. Mao
Nonparametric Modeling of Partially Ranked Data

J. Huang, C. Guestrin, L. Guibas
Efficient Inference forDistributions on Permutations

E. Bonilla, K. Chai, C. Williams
Multitask Gaussian Process Prediction

N. Chapados, Y. Bengio
Augmented Functional Time Series Representation and Forecasting with Gaussian Processes

S. Siddiqi, B. Boots, G. Gordon
A Constraint Generation Approach to Learning Stable Linear Dynamical Systems

D. Wingate, S. Singh
Exponential Family Predictive Representations of State

D. Mochihashi, E. Sumita
The Infinite Markov Model

A. Graves, S. Fernandez, M. Liwicki, H. Bunke, J. Schmidhuber
Unconstrained Online Handwriting Recognition with Recurrent Neural Networks

G. Englebienne, T. Cootes, M. Rattray
A probabilistic model for generating realistic lip movements from speech

Y. Lin, J. Chen, Y. Kim, D. Lee
Blind channel identification for speech dereverberation using l1norm sparse learning

R. Turner, M. Sahani
Modeling Natural Sounds with Modulation Cascade Processes

U. Beierholm, K. Kording, L. Shams, W. Ma
Comparing Bayesian models for multisensory cue combination without mandatory integration

R. Peters, L. Itti
Congruence between model and human attention reveals unique signatures of critical visual events

A. Sanborn, T. Griffiths
Markov Chain Monte Carlo with People

M. Frank, N. Goodman, J. Tenenbaum
A Bayesian Framework for CrossSituational WordLearning

C. Kemp, N. Goodman, J. Tenenbaum
A complexity measure for intuitive theories

P. Frazier, A. Yu
Sequential Hypothesis Testing under Stochastic Deadlines

V. Rao, M. Howard
Retrieved context and the discovery of semantic structure

N. Daw, A. Courville
The rat as particle filter

B. Fischer
Optimal models of sound localization by barn owls

B. Williams, M. Toussaint, A. Storkey
Modelling motion primitives and their timing in biologically executed movements

B. Russell, A. Torralba, C. Liu, R. Fergus, W. Freeman
Object Recognition by Scene Alignment

V. Ferrari, A. Zisserman
Learning Visual Attributes

L. Sigal, A. Balan, M. Black
Combined discriminative and generative articulated pose and nonrigid shape estimation

N. Le Roux, Y. Bengio, P. Lamblin, M. Joliveau, B. Kégl
Learning the 2D Topology of Images

M. Parsana, S. Bhattacharya, C. Bhattacharyya, K. Ramakrishnan
Kernels on Attributed Pointsets with Applications

M. Bethge, P. Berens
NearMaximum Entropy Models for Binary Neural Representations of Natural Images

P. Berkes, R. Turner, M. Sahani
On Sparsity and Overcompleteness in Image Models

D. Gao, V. Mahadevan, N. Vasconcelos
The discriminant centersurround hypothesis for bottomup saliency

M. Cerf, J. Harel, W. Einhäuser, C. Koch
Predicting human gaze using lowlevel saliency combined with face detection

M. Ross, A. Cohen
GRIFT: A graphical model for inferring visual classification features from human data

H. Lee, E. Chaitanya, A. Ng
Sparse deep belief net model for visual area V2

E. Tsang, B. Shi
Estimating disparity with confidence from energy neurons

P. Garrigues, B. Olshausen
Learning Horizontal Connections in a Sparse Coding Model of Natural Images

A. Stocker, E. Simoncelli
A Bayesian Model of Conditioned Perception

J. Macke, G. Zeck, M. Bethge
Receptive Fields without SpikeTriggering

C. Clopath, A. Longtin, W. Gerstner
An online Hebbian learning rule that performs Independent Component Analysis

S. Gerwinn, J. Macke, M. Seeger, M. Bethge
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior

O. Bobrowski, R. Meir, S. Shoham, Y. Eldar
A neural network implementing optimal state estimation based on dynamic spike train decoding

M. Lengyel, P. Dayan
Hippocampal Contributions to Control: The Third Way

J. Dauwels, F. Vialatte, T. Rutkowski, A. CICHOCKI
Measuring Neural Synchrony by Message Passing

J. Pillow, P. Latham
Neural characterization in partially observed populations of spiking neurons

L. Buesing, W. Maass
Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons

S. LAM, B. Shi
Extending position/phaseshift tuning to motion energy neurons improves velocity discrimination

R. Legenstein, D. Pecevski, W. Maass
Theoretical Analysis of Learning with RewardModulated SpikeTimingDependent Plasticity

M. Ahrens, M. Sahani
Inferring Elapsed Time from Stochastic Neural Processes

J. Cunningham, B. Yu, K. Shenoy, M. Sahani
Inferring Neural Firing Rates from Spike Trains Using Gaussian Processes

B. Blankertz, M. Kawanabe, R. Tomioka, F. Hohlefeld, V. Nikulin, K. Müller
Invariant Common Spatial Patterns: Alleviating Nonstationarities in BrainComputer Interfacing

P. Ferrez, J. Millán
EEGBased BrainComputer Interaction: Improved Accuracy by Automatic SingleTrial Error Detection

C. Christoforou, P. Sajda, L. Parra
Second Order Bilinear Discriminant Analysis for single trial EEG analysis

S. Ghebreab, A. Smeulders, P. Adriaans
Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression

F. Meyer, G. Stephens
Locality and lowdimensions in the prediction of natural experience from fMRI

L. Murray, A. Storkey
Continuous Time Particle Filtering for fMRI

D. Sridharan, B. Percival, j. arthur, K. Boahen
An insilico Neural Model of Dynamic Routing through Neuronal Coherence

S. Mitra, G. Indiveri, S. Fusi
Learning to classify complex patterns using a VLSI network of spiking neurons

M. Giulioni, m. pannunzi, D. Badoni, V. Dante, p. del giudice
A configurable analog VLSI neural network with spiking neurons and selfregulating plastic synapses

E. Neftci, E. Chicca, G. Indiveri, J. Slotine, R. Douglas
Contraction Properties of VLSI Cooperative Competitive Neural Networks of Spiking Neurons

M. Figueroa, G. Carvajal, W. Valenzuela
SubspaceBased Face Recognition in Analog VLSI

Thursday 
7:30 – 9:00am 
Breakfast 
8:00am – 1:00pm 
Registration (Hyatt) 
8:30 – 10:10am 
Session 8: Neuroscience ISession Chair:Alan A Stocker 


M. Ahrens, M. Sahani
Inferring Elapsed Time from Stochastic Neural Processes

O. Bobrowski, R. Meir, S. Shoham, Y. Eldar
A neural network implementing optimal state estimation based on dynamic spike train decoding

S. Gerwinn, J. Macke, M. Seeger, M. Bethge
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior

J. Pillow, P. Latham
Neural characterization in partially observed populations of spiking neurons

S. Mitra, G. Indiveri, S. Fusi
Learning to classify complex patterns using a VLSI network of spiking neurons

10:10 – 10:40am 
Break 
10:40am – 12:00pm 
Session 9: Neuroscience IISession Chair:Odelia Schwartz 


5:00 – 8:30pm 
Registration (Westin) 