Monday, December 7 
8:00am – 6:00pm 
Registration Desk, Internet Cafe 
6:15 – 6:30pm 
Opening Remarks and Awards 
6:30 – 6:50pm 
Spotlights 


H. Valizadegan, R. Jin, R. Zhang, J. Mao
Learning to Rank by Optimizing NDCG Measure

R. Arora
On Learning Rotations

M. Kolar, L. Song, E. Xing
Sparsistent Learning of Varyingcoefficient Models with Structural Changes

S. Klampfl, W. Maass
Replacing supervised classification learning by Slow Feature Analysis in spiking neural networks

Z. Yang, I. King, Z. Xu, E. Oja
HeavyTailed Symmetric Stochastic Neighbor Embedding

V. Rao, Y. Teh
Spatial Normalized Gamma Processes

H. Wallach, D. Mimno, A. McCallum
Rethinking LDA: Why Priors Matter

K. Miller, T. Griffiths, M. Jordan
Nonparametric Latent Feature Models for Link Prediction

A. Gretton, K. Fukumizu, Z. Harchaoui, B. Sriperumbudur
A Fast, Consistent Kernel TwoSample Test

A. Subramanya, J. Bilmes
Entropic Graph Regularization in NonParametric SemiSupervised Classification

S. Rangan, A. Fletcher, V. Goyal
Asymptotic Analysis of MAP Estimation via the Replica Method and Compressed Sensing

I. Steinwart, A. Christmann
Fast Learning from Noni.i.d. Observations

H. Maei, C. Szepesvari, S. Batnaghar, D. Precup, D. Silver, R. Sutton
Convergent TemporalDifference Learning with Arbitrary Smooth Function Approximation

7:00 – 11:59pm 
Poster Session 


A. Subramanya, J. Bilmes
M1
Entropic Graph Regularization in NonParametric SemiSupervised Classification

P. Smaragdis, M. Shashanka, B. Raj
M2
A Sparse NonParametric Approach for Single Channel Separation of Known Sounds

J. Honorio, L. Ortiz, D. Samaras, N. Paragios, R. Goldstein
M3
Sparse and Locally Constant Gaussian Graphical Models

P. Carbonetto, M. King, F. Hamze
M4
A Stochastic approximation method for inference in probabilistic graphical models

C. Wang, D. Blei
M5
Variational Inference for the Nested Chinese Restaurant Process

J. Vanhatalo, P. Jylänki, A. Vehtari
M6
Gaussian process regression with Studentt likelihood

R. Socher, S. Gershman, A. Perotte, P. Sederberg, D. Blei, K. Norman
M7
A Bayesian Analysis of Dynamics in Free Recall

B. Van Durme, A. Lall
M8
Streaming Pointwise Mutual Information

M. Grzegorczyk, D. Husmeier
M9
Nonstationary continuous dynamic Bayesian networks

V. Rao, Y. Teh
M10
Spatial Normalized Gamma Processes

M. Kumar, D. Koller
M11
Learning a Small Mixture of Trees

A. Montanari, J. Bento
M12
Which graphical models are difficult to learn?

S. Mohamed, D. Knowles, Z. Ghahramani, F. DoshiVelez
M13
Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process

I. Sutskever, R. Salakhutdinov, J. Tenenbaum
M14
Modelling Relational Data using Bayesian Clustered Tensor Factorization

K. Miller, T. Griffiths, M. Jordan
M15
Nonparametric Latent Feature Models for Link Prediction

S. Rangan, A. Fletcher, V. Goyal
M16
Asymptotic Analysis of MAP Estimation via the Replica Method and Compressed Sensing

M. Wilder, M. Jones, M. Mozer
M17
Sequential effects reflect parallel learning of multiple environmental regularities

Z. Yang, Q. Zhao, E. Keefer, W. Liu
M18
Noise Characterization, Modeling, and Reduction for In Vivo Neural Recording

R. Brasselet, R. Johansson, A. Arleo
M19
Optimal context separation of spiking haptic signals by secondorder somatosensory neurons

J. Macke, S. Gerwinn, L. White, M. Kaschube, M. Bethge
M20
Bayesian estimation of orientation preference maps

S. Klampfl, W. Maass
M21
Replacing supervised classification learning by Slow Feature Analysis in spiking neural networks

B. Conroy, B. Singer, J. Haxby, P. Ramadge
M22
fMRIBased InterSubject Cortical Alignment Using Functional Connectivity

A. Onken, S. Grünewälder, K. Obermayer
M23
Correlation Coefficients are Insufficient for Analyzing Spike Count Dependencies

Y. Fujiwara, Y. Miyawaki, Y. Kamitani
M24
Estimating image bases for visual image reconstruction from human brain activity

T. Hu, A. Leonardo, D. Chklovskii
M25
Reconstruction of Sparse Circuits Using Multineuronal Excitation (RESCUME)

M. Blaschko, J. Shelton, A. Bartels
M26
Augmenting Featuredriven fMRI Analyses: Semisupervised learning and resting state activity

C. Boutsidis, M. Mahoney, P. Drineas
M27
Unsupervised Feature Selection for the $k$means Clustering Problem

J. Wright, A. Balasubramanian, S. Rao, Y. Peng, Y. Ma
M28
Robust Principal Component Analysis: Exact Recovery of Corrupted LowRank Matrices via Convex Optimization

A. Kapoor, E. Horvitz
M29
Breaking Boundaries Between Induction Time and Diagnosis Time Active Information Acquisition

K. Bush, J. Pineau
M30
Manifold Embeddings for ModelBased Reinforcement Learning under Partial Observability

T. Iwata, T. Yamada, N. Ueda
M31
Modeling Social Annotation Data with Content Relevance using a Topic Model

P. Ram, D. Lee, H. Ouyang, A. Gray
M32
RankApproximate Nearest Neighbor Search: Retaining Meaning and Speed in High Dimensions

N. Quadrianto, J. Petterson, A. Smola
M33
Distribution Matching for Transduction

Z. Yang, I. King, Z. Xu, E. Oja
M34
HeavyTailed Symmetric Stochastic Neighbor Embedding

Y. Wang, G. Haffari, S. Wang, G. Mori
M35
A Rate Distortion Approach for SemiSupervised Conditional Random Fields

Z. Zhang, g. dai
M36
Optimal Scoring for Unsupervised Learning

G. Chechik, U. Shalit, V. Sharma, S. Bengio
M37
An Online Algorithm for Large Scale Image Similarity Learning

H. Wallach, D. Mimno, A. McCallum
M38
Rethinking LDA: Why Priors Matter

K. Sinha, M. Belkin
M39
Semisupervised Learning using Sparse Eigenfunction Bases

N. Ailon, R. Jaiswal, C. Monteleoni
M40
Streaming kmeans approximation

B. Bai, J. Weston, D. Grangier, R. Collobert, K. Sadamasa, Y. Qi, C. Cortes, M. Mohri
M41
Polynomial Semantic Indexing

R. Meka, P. Jain, I. Dhillon
M42
Matrix Completion from PowerLaw Distributed Samples

T. Ouyang, R. Davis
M43
Learning from Neighboring Strokes: Combining Appearance and Context for MultiDomain Sketch Recognition

J. Whitehill, P. Ruvolo, T. Wu, J. Bergsma, j. movellan
M44
Whose Vote Should Count More: Optimal Integration of Labels from Labelers of Unknown Expertise

C. Kemp, A. Jern, F. Xu
M45
Individuation, Identification and Object Discovery

M. Steyvers, M. Lee, B. Miller, P. Hemmer
M46
The Wisdom of Crowds in the Recollection of Order Information

W. Vanpaemel
M47
Measuring model complexity with the prior predictive

A. Vedaldi, A. Zisserman
M48
Structured output regression for detection with partial truncation

L. Xiao
M49
Dual Averaging Method for Regularized Stochastic Learning and Online Optimization

K. Chai
M50
Generalization Errors and Learning Curves for Regression with Multitask Gaussian Processes

P. Zhao, S. Hoi, R. Jin
M51
DUOL: A Double Updating Approach for Online Learning

M. Lanctot, K. Waugh, M. Zinkevich, M. Bowling
M52
Monte Carlo Sampling for Regret Minimization in Extensive Games

E. Hazan, S. Kale
M53
Beyond Convexity: Online Submodular Minimization

P. Liang, F. Bach, G. Bouchard, M. Jordan
M54
Asymptotically Optimal Regularization in Smooth Parametric Models

O. Maillard, R. Munos
M55
Compressed LeastSquares Regression

M. Hein
M56
Robust Nonparametric Regression with MetricSpace Valued Output

J. Bouvrie, L. Rosasco, T. Poggio
M57
On Invariance in Hierarchical Models

I. Steinwart, A. Christmann
M58
Fast Learning from Noni.i.d. Observations

C. Hsu, Y. Chang, H. Huang, Y. Lee
M59
Periodic Step Size Adaptation for Single Pass Online Learning

L. Zhu, Y. Chen, B. Freeman, A. Torralba
M60
Nonparametric Bayesian Texture Learning and Synthesis

D. Zoran, Y. Weiss
M61
The "treedependent components" of natural scenes are edge filters

S. Ghebreab, H. Steven, V. Lamme, A. Smeulders
M62
A Biologically Plausible Model for Rapid Natural Scene Identification

J. Schlecht, K. Barnard
M63
Learning models of object structure

S. Yang, H. Zha, B. Hu
M64
DirichletBernoulli Alignment: A Generative Model for MultiClass MultiLabel MultiInstance Corpora

D. Margaritis
M65
Toward Provably Correct Feature Selection in Arbitrary Domains

S. Clémençon, N. Vayatis, M. Depecker
M66
AUC optimization and the twosample problem

H. Valizadegan, R. Jin, R. Zhang, J. Mao
M67
Learning to Rank by Optimizing NDCG Measure

R. Arora
M68
On Learning Rotations

M. Palatucci, D. Pomerleau, G. Hinton, T. Mitchell
M69
Zeroshot Learning with Semantic Output Codes

W. Chen, T. Liu, Y. Lan, Z. Ma, H. Li
M70
Ranking Measures and Loss Functions in Learning to Rank

M. Brückner, T. Scheffer
M71
Nash Equilibria of Static Prediction Games

M. Kolar, L. Song, E. Xing
M72
Sparsistent Learning of Varyingcoefficient Models with Structural Changes

M. Karasuyama, I. Takeuchi
M73
Multiple Incremental Decremental Learning of Support Vector Machines

S. Jagarlapudi, d. govindaraj, R. S, C. Bhattacharyya, A. BenTal, K. Ramakrishnan
M74
On the Algorithmics and Applications of a Mixednorm based Kernel Learning Formulation

J. Gao, F. Liang, W. Fan, Y. Sun, J. Han
M75
Graphbased Consensus Maximization among Multiple Supervised and Unsupervised Models

C. Shen, J. Kim, L. Wang, A. van den Hengel
M76
Positive Semidefinite Metric Learning with Boosting

A. Perina, M. Cristani, U. Castellani, V. Murino, N. Jojic
M77
Free energy score space

J. Peng, L. Bo, J. Xu
M78
Conditional Neural Fields

O. Dekel
M79
DistributionCalibrated Hierarchical Classiﬁcation

V. Cevher
M80
Learning with Compressible Priors

A. Gretton, K. Fukumizu, Z. Harchaoui, B. Sriperumbudur
M81
A Fast, Consistent Kernel TwoSample Test

G. Shani, C. Meek
M82
Improving Existing Fault Recovery Policies

H. Sprekeler, G. Hennequin, W. Gerstner
M83
Codespecific policy gradient rules for spiking neurons

T. Morimura, E. Uchibe, J. Yoshimoto, K. Doya
M84
A Generalized Natural ActorCritic Algorithm

H. Maei, C. Szepesvari, S. Batnaghar, D. Precup, D. Silver, R. Sutton
M85
Convergent TemporalDifference Learning with Arbitrary Smooth Function Approximation

L. MacDermed, C. Isbell
M86
Solving Stochastic Games

M. Cuturi, J. Vert, A. d'Aspremont
M87
White Functionals for Anomaly Detection in Dynamical Systems

Tuesday, December 8 
7:30 – 9:00am 
Breakfast 
8:00am – 6:00pm 
Registration Desk, Internet Cafe 
8:30 – 10:10am 
Oral Session 1: Information Theory and EstimationSession Chair:Rob Nowak 


10:10 – 10:40am 
Break 
10:40am – 12:00pm 
Oral Session 2: Images and CodesSession Chair:Bill Triggs 


M. Fritz, M. Black, G. Bradski, T. Darrell
An Additive Latent Feature Model for Transparent Object Recognition

R. Fergus, Y. Weiss, A. Torralba
SemiSupervised Learning in Gigantic Image Collections

M. Zhou, H. Chen, J. Paisley, L. Ren, G. Sapiro, L. Carin
NonParametric Bayesian Dictionary Learning for Sparse Image Representations

M. Raginsky, S. Lazebnik
LocalitySensitive Binary Codes from ShiftInvariant Kernels

12:00 – 2:00pm 
Lunch Break 
12:30 – 1:45pm 
Yoshua Bengio Debate on Future Publication Models for the NIPS Community 
2:00 – 3:20pm 
Oral Session 3: Deep Learning and Network ModelsSession Chair:Aaron C Courville 


3:20 – 3:40pm 
Spotlights 


P. Sollich, M. Urry, C. Coti
Kernels and learning curves for Gaussian process regression on random graphs

M. Petrik, S. Zilberstein
Robust Value Function Approximation Using Bilinear Programming

Y. Ying, C. Campbell, M. Girolami
Analysis of SVM with Indefinite Kernels

Z. Xiang, Y. Xi, U. Hasson, P. Ramadge
Boosting with Spatial Regularization

C. Kemp, A. Jern
Abstraction and Relational learning

W. Li, D. Yeung, Z. Zhang
Probabilistic Relational PCA

C. Wang, D. Blei
Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process

S. Gerwinn, P. Berens, M. Bethge
A joint maximumentropy model for binary neural population patterns and continuous signals

L. Cayton
Efficient Bregman Range Search

Y. Watanabe, K. Fukumizu
Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation

M. Streeter, D. Golovin, A. Krause
Online Learning of Assignments

P. Ram, D. Lee, W. March, A. Gray
Lineartime Algorithms for Pairwise Statistical Problems

3:40 – 4:10pm 
Break 
4:10 – 5:10pm 
Oral Session 4: Cognitive Science and EEG AnalysisSession Chair:Charles Kemp 


5:10 – 5:30pm 
Spotlights 


Y. Teh, D. Gorur
Indian Buffet Processes with Powerlaw Behavior

Y. Kawahara, K. Nagano, K. Tsuda, J. Bilmes
Submodularity Cuts and Applications

R. CoenCagli, P. Dayan, O. Schwartz
Statistical Models of Linear and Nonlinear Contextual Interactions in Early Visual Processing

B. Nessler, M. Pfeiffer, W. Maass
STDP enables spiking neurons to detect hidden causes of their inputs

V. Nair, G. Hinton
3D Object Recognition with Deep Belief Nets

T. Perkins
Maximum likelihood trajectories for continuoustime Markov chains

L. Song, M. Kolar, E. Xing
TimeVarying Dynamic Bayesian Networks

P. Orbanz
Construction of Nonparametric Bayesian Models from Parametric Bayes Equations

M. Wick, K. Rohanimanesh, S. Singh, A. McCallum
Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference

J. Huang, C. Guestrin
Riffled Independence for Ranked Data

V. Desai, V. Farias, C. Moallemi
A Smoothed Approximate Linear Program

A. BouchardCôté, S. Petrov, D. Klein
Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic Programs

S. Fazli, C. Grozea, M. Danóczy, B. Blankertz, F. Popescu, K. Müller
Subject independent EEGbased BCI decoding

5:30 – 7:30pm 
Dinner Break 
7:30 – 11:59pm 
Poster Session 


P. Sollich, M. Urry, C. Coti
T1
Kernels and learning curves for Gaussian process regression on random graphs

M. Raginsky, S. Lazebnik
T2
Localitysensitive binary codes from shiftinvariant kernels

W. Li, D. Yeung, Z. Zhang
T3
Probabilistic Relational PCA

C. Wang, D. Blei
T4
Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process

L. Cayton
T5
Efficient Bregman Range Search

L. Wu, R. Jin, S. Hoi, J. Zhu, N. Yu
T6
Learning Bregman Distance Functions and Its Application for SemiSupervised Clustering

M. Schmidt
T7
Linearly constrained Bayesian matrix factorization for blind source separation

R. Keshavan, A. Montanari, S. Oh
T8
Matrix Completion from Noisy Entries

K. Yu, T. Zhang, Y. Gong
T9
Nonlinear Learning using Local Coordinate Coding

K. Kim, F. Steinke, M. Hein
T10
Semisupervised Regression using Hessian energy with an application to semisupervised dimensionality reduction

S. Bengio, F. Pereira, Y. Singer, D. Strelow
T11
Group Sparse Coding

A. Guillory, J. Bilmes
T12
Label Selection on Graphs

K. Jung, P. Kohli, D. Shah
T13
Local Rules for Global MAP: When Do They Work ?

M. Zhou, H. Chen, J. Paisley, L. Ren, G. Sapiro, L. Carin
T14
NonParametric Bayesian Dictionary Learning for Sparse Image Representations

J. Petterson, T. Caetano, J. McAuley, J. Yu
T15
Exponential Family Graph Matching and Ranking

P. Coquelin, R. Deguest, R. Munos
T16
Sensitivity analysis in HMMs with application to likelihood maximization

J. Goldberger, A. Leshem
T17
A Gaussian Tree Approximation for Integer LeastSquares

N. Ye, W. Lee, H. Chieu, D. Wu
T18
Conditional Random Fields with HighOrder Features for Sequence Labeling

Y. Watanabe, K. Fukumizu
T19
Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation

Y. Teh, D. Gorur
T20
Indian Buffet Processes with Powerlaw Behavior

M. LazaroGredilla, A. FigueirasVidal
T21
Interdomain Gaussian Processes for Sparse Inference using Inducing Features

R. Henao, O. Winther
T22
Bayesian Sparse Factor Models and DAGs Inference and Comparison

R. Salakhutdinov
T23
Learning in Markov Random Fields using Tempered Transitions

T. Perkins
T24
Maximum likelihood trajectories for continuoustime Markov chains

J. Huang, C. Guestrin
T25
Riffled Independence for Ranked Data

R. Tillman, A. Gretton, P. Spirtes
T26
Nonlinear directed acyclic structure learning with weakly additive noise models

C. Kemp, A. Jern
T27
Abstraction and Relational learning

X. Zhu, T. Rogers, B. Gibson
T28
Human Rademacher Complexity

F. Yan, N. XU, Y. Qi
T29
Parallel Inference for Latent Dirichlet Allocation on Graphics Processing Units

A. Hsu, T. Griffiths
T30
Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning

D. Cavagnaro, M. Pitt, J. Myung
T31
Adaptive Design Optimization in Experiments with People

E. Vul, M. Frank, G. Alvarez, J. Tenenbaum
T32
Explaining human multiple object tracking as resourceconstrained approximate inference in a dynamic probabilistic model

Y. Chen, M. Kapralov, D. Pavlov, J. Canny
T33
Factor Modeling for Advertisement Targeting

J. Kim, S. Choi
T34
Clustering sequence sets for motif discovery

L. Song, M. Kolar, E. Xing
T35
TimeVarying Dynamic Bayesian Networks

A. BouchardCôté, S. Petrov, D. Klein
T36
Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic Programs

D. Hsu, S. Kakade, J. Langford, T. Zhang
T38
MultiLabel Prediction via Compressed Sensing

S. Arlot, F. Bach
T39
Datadriven calibration of linear estimators with minimal penalties

R. Jin, S. Wang, Y. Zhou
T40
Regularized Distance Metric Learning:Theory and Algorithm

M. Streeter, D. Golovin, A. Krause
T41
Online Learning of Assignments

Y. Yu, Y. Li, D. Schuurmans, C. Szepesvari
T42
A General Projection Property for Distribution Families

Y. Kawahara, K. Nagano, K. Tsuda, J. Bilmes
T43
Submodularity Cuts and Applications

P. Ram, D. Lee, W. March, A. Gray
T44
Lineartime Algorithms for Pairwise Statistical Problems

B. Sriperumbudur, G. Lanckriet
T45
On the Convergence of the ConcaveConvex Procedure

M. Zinkevich, A. Smola, J. Langford
T46
Slow Learners are Fast

C. Hu, J. Kwok, W. Pan
T47
Accelerated Gradient Methods for Stochastic Optimization and Online Learning

R. Nowak
T48
Noisy Generalized Binary Search

S. Zhou
T49
Thresholding Procedures for High Dimensional Variable Selection and Statistical Estimation

P. Orbanz
T50
Construction of Nonparametric Bayesian Models from Parametric Bayes Equations

U. Syed, A. Slivkins, N. Mishra
T51
Adapting to the Shifting Intent of Search Queries

S. Negahban, P. Ravikumar, M. Wainwright, B. Yu
T52
A unified framework for highdimensional analysis of $M$estimators with decomposable regularizers

T. Malisiewicz, A. Efros
T53
Beyond Categories: The Visual Memex Model for Reasoning About Object Relationships

A. Dalalyan, R. Keriven
T54
$L_1$Penalized Robust Estimation for a Class of Inverse Problems Arising in Multiview Geometry

M. Fritz, M. Black, G. Bradski, T. Darrell
T55
An Additive Latent Feature Model for Transparent Object Recognition

R. Fergus, Y. Weiss, A. Torralba
T56
SemiSupervised Learning in Gigantic Image Collections

W. Campbell, Z. Karam, D. Sturim
T57
Speaker Comparison with Inner Product Discriminant Functions

L. Sun, J. Liu, J. Chen, J. Ye
T58
Efficient Recovery of Jointly Sparse Vectors

y. meng, B. Shi
T59
Extending Phase Mechanism to Differential Motion Opponency for Motion Popout

M. Leordeanu, M. Hebert, R. Sukthankar
T60
An Integer Projected Fixed Point Method for Graph Matching and MAP Inference

K. Saenko, T. Darrell
T61
Filtering Abstract Senses From Image Search Results

W. Zheng, Z. Lin
T62
Optimizing MultiClass SpatioSpectral Filters via Bayes Error Estimation for EEG Classification

P. Berkes, B. White, J. Fiser
T63
No evidence for active sparsification in the visual cortex

S. Gerwinn, P. Berens, M. Bethge
T64
A joint maximumentropy model for binary neural population patterns and continuous signals

H. Lee, P. Pham, Y. Largman, A. Ng
T65
Unsupervised feature learning for audio classification using convolutional deep belief networks

B. Yao, D. Walther, D. Beck, F. Li
T66
Hierarchical Mixture of Classification Experts Uncovers Interactions between Brain Regions

R. CoenCagli, P. Dayan, O. Schwartz
T67
Statistical Models of Linear and Nonlinear Contextual Interactions in Early Visual Processing

G. Cecchi, I. Rish, B. Thyreau, B. Thirion, M. Plaze, M. PaillereMartinot, J. Martinot, J. Poline
T68
Discriminative Network Models of Schizophrenia

B. Nessler, M. Pfeiffer, W. Maass
T69
STDP enables spiking neurons to detect hidden causes of their inputs

R. Wilson, L. Finkel
T70
A Neural Implementation of the Kalman Filter

M. Seeger
T71
Speeding up Magnetic Resonance Image Acquisition by Bayesian MultiSlice Adaptive Compressed Sensing

S. Fazli, C. Grozea, M. Danóczy, B. Blankertz, F. Popescu, K. Müller
T72
Subject independent EEGbased BCI decoding

Y. Ying, C. Campbell, M. Girolami
T73
Analysis of SVM with Indefinite Kernels

Z. Xiang, Y. Xi, U. Hasson, P. Ramadge
T74
Boosting with Spatial Regularization

Y. Kao, B. Van Roy, X. Yan
T75
Directed Regression

I. Goodfellow, Q. Le, A. Saxe, A. Ng
T76
Measuring Invariances in Deep Networks

H. Liu, X. Chen
T77
Nonparametric Greedy Algorithms for the Sparse Learning Problem

C. Cortes, M. Mohri, A. Rostamizadeh
T78
Learning NonLinear Combinations of Kernels

V. Nair, G. Hinton
T79
3D Object Recognition with Deep Belief Nets

A. Lozano, G. Swirszcz, N. Abe
T80
Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction

M. Kloft, U. Brefeld, S. Sonnenburg, P. Laskov, K. Müller, A. Zien
T81
Efficient and Accurate LpNorm Multiple Kernel Learning

M. Wick, K. Rohanimanesh, S. Singh, A. McCallum
T82
Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference

S. Kpotufe
T83
Fast, smooth and adaptive regression in metric spaces

M. Petrik, S. Zilberstein
T84
Robust Value Function Approximation Using Bilinear Programming

F. DoshiVelez
T85
The Infinite Partially Observable Markov Decision Process

V. Desai, V. Farias, C. Moallemi
T86
A Smoothed Approximate Linear Program

C. Cai, X. Liao, L. Carin
T87
Learning to Explore and Exploit in POMDPs

E. Todorov
T88
Compositionality of optimal control laws

R. Anati, K. Daniilidis
T89
Constructing Topological Maps using Markov Random Fields and LoopClosure Detection

7:30 – 11:59pm 
Demonstrations 


Wednesday, December 9 
7:30 – 9:00am 
Breakfast 
8:00am – 6:00pm 
Registration Desk, Internet Cafe 
8:30 – 10:10am 
Oral Session 5: NeuroscienceSession Chair:Tai Sing Lee 


10:10 – 10:40am 
Break 
10:40am – 12:00pm 
Oral Session 6: Theory, Optimization and Games Session Chair:Ben Taskar 


12:00 – 2:00pm 
Lunch Break 
2:00 – 3:20pm 
Oral session 7: Vision and InferenceSession Chair:Antonio Torralba 


3:20 – 3:40pm 
Spotlights 


C. Kemp
Quantification and the language of thought

D. Krishnan, R. Fergus
Fast Image Deconvolution using HyperLaplacian Priors

G. Mann, R. McDonald, M. Mohri, N. Silberman, D. Walker
Efficient LargeScale Distributed Training of Conditional Maximum Entropy Models

V. Farias, S. Jagabathula, D. Shah
A DataDriven Approach to Modeling Choice

B. Nadler, N. Srebro, X. Zhou
Statistical Analysis of SemiSupervised Learning: The Limit of Infinite Unlabelled Data

S. Gould, T. Gao, D. Koller
Regionbased Segmentation and Object Detection

M. Zhao, V. Saligrama
Anomaly Detection with Score functions based on Nearest Neighbor Graphs

K. Crammer, A. Kulesza, M. Dredze
Adaptive Regularization of Weight Vectors

Z. Xu, R. Jin, J. Zhu, I. King, M. Lyu, Z. Yang
Adaptive Regularization for Transductive Support Vector Machine

J. Luttinen, A. Ilin
Variational Gaussianprocess factor analysis for modeling spatiotemporal data

M. Mozer, H. Pashler, N. Cepeda, R. Lindsey, E. Vul
Predicting the Optimal Spacing of Study: A Multiscale Context Model of Memory

X. Wu, A. So, Z. Li, S. Li
Fast Graph Laplacian Regularized Kernel Learning via Semidefinite–Quadratic–Linear Programming

S. Huang, J. Li, L. Sun, J. Liu, T. Wu, K. Chen, A. Fleisher, E. Reiman, J. Ye
Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data

3:40 – 4:10pm 
Break 
4:10 – 5:10pm 
Oral session 8: Probabilistic Models and KernelsSession Chair:Jon McAuliffe 


5:10 – 5:30pm 
Spotlights 


S. Venkataraman, A. Blum, D. Song, S. Sen, O. Spatscheck
Tracking Dynamic Sources of Malicious Activity at Internet Scale

G. Konidaris, A. Barto
Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining

L. Bo, C. Sminchisescu
Efficient Match Kernel between Sets of Features for Visual Recognition

A. Fletcher, S. Rangan
Orthogonal Matching Pursuit From Noisy Random Measurements: A New Analysis

B. Kulis, T. Darrell
Learning to Hash with Binary Reconstructive Embeddings

S. Gershman, E. Vul, J. Tenenbaum
Perceptual Multistability as Markov Chain Monte Carlo Inference

A. Agarwal, P. Bartlett, P. Ravikumar, M. Wainwright
Informationtheoretic lower bounds on the oracle complexity of convex optimization

K. Heller, A. Sanborn, N. Chater
Hierarchical Learning of Dimensional Biases in Human Categorization

G. Raskutti, M. Wainwright, B. Yu
Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness

L. ShiUpdateMe, T. Griffiths
Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling

J. Graca, K. Ganchev, B. Taskar, F. Pereira
Posterior vs Parameter Sparsity in Latent Variable Models

I. Stevenson, K. Koerding
Structural inference affects depth perception in the context of potential occlusion

H. Pirsiavash, D. Ramanan, C. Fowlkes
Bilinear classifiers for visual recognition

5:30 – 7:30pm 
Dinner Break 
7:30 – 11:59pm 
Poster Session 


R. Legenstein, S. Chase, A. Schwartz, W. Maass
W1
Functional network reorganization in motor cortex can be explained by rewardmodulated Hebbian learning

G. Mann, R. McDonald, M. Mohri, N. Silberman, D. Walker
W2
Efficient LargeScale Distributed Training of Conditional Maximum Entropy Models

S. Kumar, M. Mohri, A. Talwalkar
W3
Ensemble Nystrom Method

N. SinghMiller, M. Collins
W4
Learning Label Embeddings for NearestNeighbor Multiclass Classification with an Application to Speech Recognition

P. Germain, A. Lacasse, F. Laviolette, M. Marchand, S. Shanian
W5
From PACBayes Bounds to KL Regularization

N. Shervashidze, K. Borgwardt
W6
Fast subtree kernels on graphs

K. Crammer, A. Kulesza, M. Dredze
W7
Adaptive Regularization of Weight Vectors

Y. Cho, L. Saul
W8
Kernel Methods for Deep Learning

E. Garcia, M. Gupta
W9
Lattice Regression

J. Bergstra, Y. Bengio
W10
Slow, Decorrelated Features for Pretraining Complex Celllike Networks

A. Fletcher, S. Rangan
W11
Orthogonal Matching Pursuit From Noisy Random Measurements: A New Analysis

D. Wipf, S. Nagarajan
W12
Sparse Estimation Using General Likelihoods and NonFactorial Priors

J. Duchi, Y. Singer
W13
Efficient Learning using ForwardBackward Splitting

V. Farias, S. Jagabathula, D. Shah
W14
A DataDriven Approach to Modeling Choice

G. Kim, A. Torralba
W15
Unsupervised Detection of Regions of Interest Using Iterative Link Analysis

S. Turaga, K. Briggman, M. Helmstaedter, W. Denk, H. Seung
W16
Maximin affinity learning of image segmentation

S. Fidler, M. Boben, A. Leonardis
W17
Evaluating multiclass learning strategies in a generative hierarchical framework for object detection

F. Sinz, E. Simoncelli, M. Bethge
W18
Hierarchical Modeling of Local Image Features through $L_p$Nested Symmetric Distributions

D. Krishnan, R. Fergus
W19
Fast Image Deconvolution using HyperLaplacian Priors

T. Chin, H. Wang, D. Suter
W20
The Ordered Residual Kernel for Robust Motion Subspace Clustering

S. Gould, T. Gao, D. Koller
W21
Regionbased Segmentation and Object Detection

L. Bo, C. Sminchisescu
W22
Efficient Match Kernel between Sets of Features for Visual Recognition

B. Russell, A. Efros, J. Sivic, B. Freeman, A. Zisserman
W23
Segmenting Scenes by Matching Image Composites

I. Stevenson, K. Koerding
W24
Structural inference affects depth perception in the context of potential occlusion

J. Luo, B. Caputo, V. Ferrari
W25
Who’s Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation

H. Pirsiavash, D. Ramanan, C. Fowlkes
W26
Bilinear classifiers for visual recognition

P. Berens, S. Gerwinn, A. Ecker, M. Bethge
W27
Neurometric function analysis of population codes

J. Pillow
W28
Timerescaling methods for the estimation and assessment of nonPoisson neural encoding models

J. Pfister, P. Dayan, M. Lengyel
W29
Know Thy Neighbour: A Normative Theory of Synaptic Depression

S. Huang, J. Li, L. Sun, J. Liu, T. Wu, K. Chen, A. Fleisher, E. Reiman, J. Ye
W30
Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data

L. ShiUpdateMe, T. Griffiths
W31
Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling

B. Chai, D. Walther, D. Beck, F. Li
W32
Exploring Functional Connectivities of the Human Brain using Multivariate Information Analysis

C. Kemp
W33
Quantification and the language of thought

A. Jern, K. Chang, C. Kemp
W34
Bayesian Belief Polarization

M. Mozer, H. Pashler, N. Cepeda, R. Lindsey, E. Vul
W35
Predicting the Optimal Spacing of Study: A Multiscale Context Model of Memory

S. Gershman, E. Vul, J. Tenenbaum
W36
Perceptual Multistability as Markov Chain Monte Carlo Inference

H. Yao, R. Sutton, S. Bhatnagar, D. Diao, C. Szepesvari
W37
MultiStep Dyna Planning for Policy Evaluation and Control

J. Veness, D. Silver, W. Uther, A. Blair
W38
Bootstrapping from Game Tree Search

G. Konidaris, A. Barto
W39
Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining

K. Waugh, N. Bard, M. Bowling
W40
Strategy Grafting in Extensive Games

M. Allen, S. Zilberstein
W41
Complexity of Decentralized Control: Special Cases

M. Hutter
W42
Discrete MDL Predicts in Total Variation

A. Kalai, V. Kanade
W43
PotentialBased Agnostic Boosting

E. Hazan, S. Kale
W44
On Stochastic and Worstcase Models for Investing

f. xia, T. Liu, H. Li
W45
Statistical Consistency of Topk Ranking

M. Amini, N. Usunier, C. Goutte
W46
Learning from Multiple Partially Observed Views  an Application to Multilingual Text Categorization

S. Venkataraman, A. Blum, D. Song, S. Sen, O. Spatscheck
W47
Tracking Dynamic Sources of Malicious Activity at Internet Scale

B. Sriperumbudur, K. Fukumizu, A. Gretton, G. Lanckriet, B. Schölkopf
W48
Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions

A. Agarwal, P. Bartlett, P. Ravikumar, M. Wainwright
W49
Informationtheoretic lower bounds on the oracle complexity of convex optimization

G. Raskutti, M. Wainwright, B. Yu
W50
Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness

K. Chaudhuri, Y. Freund, D. Hsu
W51
A Parameterfree Hedging Algorithm

J. Chang, J. BoydGraber, S. Gerrish, C. Wang, D. Blei
W52
Reading Tea Leaves: How Humans Interpret Topic Models

L. Wang
W53
Sufficient Conditions for Agnostic Active Learnable

Y. Ying, K. Huang, C. Campbell
W54
Sparse Metric Learning via Smooth Optimization

B. Nadler, N. Srebro, X. Zhou
W55
Statistical Analysis of SemiSupervised Learning: The Limit of Infinite Unlabelled Data

W. Bian, D. Tao
W56
Manifold Regularization for SIR with Rate Rootn Convergence

M. Zhao, V. Saligrama
W57
Anomaly Detection with Score functions based on Nearest Neighbor Graphs

Z. Xu, R. Jin, J. Zhu, I. King, M. Lyu, Z. Yang
W58
Adaptive Regularization for Transductive Support Vector Machine

F. Zhou, F. De la Torre
W59
Canonical Time Warping for Alignment of Human Behavior

X. Wu, A. So, Z. Li, S. Li
W60
Fast Graph Laplacian Regularized Kernel Learning via Semidefinite–Quadratic–Linear Programming

R. Salakhutdinov, G. Hinton
W61
Replicated Softmax: an Undirected Topic Model

S. Rota Bulò, M. Pelillo
W62
A GameTheoretic Approach to Hypergraph Clustering

B. Kulis, T. Darrell
W63
Learning to Hash with Binary Reconstructive Embeddings

J. Graca, K. Ganchev, B. Taskar, F. Pereira
W64
Posterior vs Parameter Sparsity in Latent Variable Models

J. Lücke, R. Turner, M. Sahani, M. Henniges
W65
Occlusive Components Analysis

M. Van Gerven, B. Cseke, R. Oostenveld, T. Heskes
W66
Bayesian Source Localization with the Multivariate Laplace Prior

L. Du, L. Ren, D. Dunson, L. Carin
W67
A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation

F. Caron, A. Doucet
W68
Bayesian Nonparametric Models on Decomposable Graphs

C. Zhou, H. Wang, Y. Wang
W69
Efficient Momentsbased Permutation Tests

L. Dietz, V. Dallmeier, A. Zeller, T. Scheffer
W70
Localizing Bugs in Program Executions with Graphical Models

J. Culpepper, B. Olshausen
W71
Learning transport operators for image manifolds

J. Luttinen, A. Ilin
W72
Variational Gaussianprocess factor analysis for modeling spatiotemporal data

M. Fromer, A. Globerson
W73
An LP View of the Mbest MAP problem

C. Bejan, M. Titsworth, A. Hickl, S. Harabagiu
W74
Nonparametric Bayesian Models for Unsupervised Event Coreference Resolution

E. Fox, E. Sudderth, M. Jordan, A. Willsky
W75
Sharing Features among Dynamical Systems with Beta Processes

N. Quadrianto, T. Caetano, J. Lim, D. Schuurmans
W76
Convex Relaxation of Mixture Regression with Efficient Algorithms

A. McCallum, K. Schultz, S. Singh
W77
FACTORIE: Probabilistic Programming via Imperatively Defined Factor Graphs

A. Ihler, A. Frank, P. Smyth
W78
Particlebased Variational Inference for Continuous Systems

A. Choi, A. Darwiche
W79
Approximating MAP by Compensating for Structural Relaxations

B. Moghaddam, B. Marlin, M. Khan, K. Murphy
W80
Accelerating Bayesian Structural Inference for NonDecomposable Gaussian Graphical Models

A. Courville, D. Eck, Y. Bengio
W81
An Infinite Factor Model Hierarchy Via a NoisyOr Mechanism

P. Rai, H. Daume III
W82
MultiLabel Prediction via Sparse Infinite CCA

A. Ozakin, A. Gray
W83
Submanifold density estimation

X. Yang, S. Kim, E. Xing
W84
Heterogeneous multitask learning with joint sparsity constraints

H. Lu, M. Weiden, A. Yuille
W85
Modeling the spacing effect in sequential category learning

K. Heller, A. Sanborn, N. Chater
W86
Hierarchical Learning of Dimensional Biases in Human Categorization

T. Ullman, C. Baker, O. Macindoe, O. Evans, N. Goodman, J. Tenenbaum
W87
Help or Hinder: Bayesian Models of Social Goal Inference

7:30 – 11:59pm 
Demonstrations 


Thursday, December 10 
7:30 – 9:00am 
Breakfast 
8:00 – 11:00am 
Registration Desk 
8:00am – 12:00pm 
Internet Cafe 
8:30 – 9:50am 
Oral session 9: Bayesian AnalysisSession Chair:Erik B Sudderth 


9:50 – 10:30am 
Break 
10:30 – 11:50am 
Oral session 10: Neural Modeling and ImagingSession Chair:Arthur Gretton 


11:50am – 1:30pm 
Lunch Break 
1:30 – 4:30pm 
Mini Symposia 


F. PerezCruz, E. ParradoHernandez, D. Hardoon, J. MadridSanchez
Assistive Machine Learning for People with Disabilities

F. Popescu, I. Guyon, G. Nolte
Causality and Time Series Analysis

J. Kolter, T. Dietterich, A. Ng
Machine Learning for Sustainability

J. Vert, Y. Qi, G. Chechik, A. Zien, T. Hertz, W. Noble
Machine Learning in Computational Biology

M. Hutter, W. Uther, P. Poupart
Partially Observable Reinforcement Learning

2:50 – 3:10pm 
Break 