NIPS 2009 - Twenty-Third Annual Conference on Neural Information Processing Systems NIPS 2009
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Category NIPS 2009
Deadline: March 10, 2009 | Date: December 07, 2009
Venue/Country: Vancouver, Canada
Updated: 2010-06-04 19:32:22 (GMT+9)
Call For Papers - CFP
$L_1$-Penalized Robust Estimation for a Class of Inverse Problems Arising in Multiview GeometryA. Dalalyan, R. Keriven
3D Object Recognition with Deep Belief Nets
V. Nair, G. Hinton
A Bayesian Analysis of Dynamics in Free Recall
R. Socher, S. Gershman, A. Perotte, P. Sederberg, D. Blei, K. Norman
A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation
L. Du, L. Ren, D. Dunson, L. Carin
A Biologically Plausible Model for Rapid Natural Scene Identification
S. Ghebreab, H. Steven, V. Lamme, A. Smeulders
Abstraction and Relational learning
C. Kemp, A. Jern
Accelerated Gradient Methods for Stochastic Optimization and Online Learning
C. Hu, J. Kwok, W. Pan
Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models
B. Moghaddam, B. Marlin, M. Khan, K. Murphy
Adapting to the Shifting Intent of Search Queries
U. Syed, S. Aleksandrs, N. Mishra
Adaptive Design Optimization in Experiments with People
D. Cavagnaro, M. Pitt, J. Myung
Adaptive Regularization for Transductive Support Vector Machine
Z. Xu, R. Jin, J. Zhu, I. King, M. Lyu, Z. Yang
Adaptive Regularization of Weight Vectors
K. Crammer, A. Kulesza, M. Dredze
A Data-Driven Approach to Modeling Choice
V. Farias, S. Jagabathula, D. Shah
A Fast, Consistent Kernel Two-Sample Test
A. Gretton, K. Fukumizu, Z. Harchaoui, B. Sriperumbudur
A Game-Theoretic Approach to Hypergraph Clustering
S. Rota Bulò, M. Pelillo
A Gaussian Tree Approximation for Integer Least-Squares
J. Goldberger, A. Leshem
A Generalized Natural Actor-Critic Algorithm
T. Morimura, E. Uchibe, J. Yoshimoto, K. Doya
A General Projection Property for Distribution Families
Y. Yu, Y. Li, D. Schuurmans, C. Szepesvari
A joint maximum-entropy model for binary neural population patterns and continuous signals
S. Gerwinn, P. Berens, M. Bethge
An Additive Latent Feature Model for Transparent Object Recognition
M. Fritz, M. Black, G. Bradski, T. Darrell
Analysis of SVM with Indefinite Kernels
Y. Ying, C. Campbell, M. Girolami
An Efficient Interior-Point Method for Minimum-Regret Learning in Online Convex Optimization
E. Hazan, N. Megiddo
A Neural Implementation of the Kalman Filter
R. Wilson, L. Finkel
An Infinite Factor Model Hierarchy Via a Noisy-Or Mechanism
A. Courville, D. Eck, Y. Bengio
An Integer Projected Fixed Point Method for Graph Matching and MAP Inference
M. Leordeanu, M. Hebert, R. Sukthankar
An LP View of the M-best MAP problem
M. Fromer, A. Globerson
Anomaly Detection with Score functions based on Nearest Neighbor Graphs
M. Zhao, V. Saligrama
An Online Algorithm for Large Scale Image Similarity Learning
G. Chechik, U. Shalit, V. Sharma, S. Bengio
A Parameter-free Hedging Algorithm
K. Chaudhuri, Y. Freund, D. Hsu
Approximating MAP by Compensating for Structural Relaxations
A. Choi, A. Darwiche
A Rate Distortion Approach for Semi-Supervised Conditional Random Fields
Y. Wang, G. Haffari, S. Wang, G. Mori
A Smoothed Approximate Linear Program
V. Desai, V. Farias, C. Moallemi
A Sparse Non-Parametric Approach for Single Channel Separation of Known Sounds
P. Smaragdis, M. Shashanka, B. Raj
A Stochastic approximation method for inference in probabilistic graphical models
P. Carbonetto, M. King, F. Hamze
Asymptotically Optimal Regularization in Smooth Parametric Models
P. Liang, F. Bach, G. Bouchard, M. Jordan
Asymptotic Analysis of MAP Estimation via the Replica Method and Compressed Sensing
S. Rangan, A. Fletcher, V. Goyal
AUC optimization and the two-sample problem
S. Clémençon, N. Vayatis, M. Depecker
Augmenting Feature-driven fMRI Analyses: Semi-supervised learning and resting state activity
M. Blaschko, J. Shelton, A. Bartels
A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers
S. Negahban, P. Ravikumar, M. Wainwright, B. Yu
Bayesian Belief Polarization
A. Jern, K. Chang, C. Kemp
Bayesian estimation of orientation preference maps
J. Macke, S. Gerwinn, L. White, M. Kaschube, M. Bethge
Bayesian Nonparametric Models on Decomposable Graphs
F. Caron, A. Doucet
Bayesian Source Localization with the Multivariate Laplace Prior
M. Van Gerven, B. Cseke, R. Oostenveld, T. Heskes
Bayesian Sparse Factor Models and DAGs Inference and Comparison
R. Henao, O. Winther
Beyond Categories: The Visual Memex Model for Reasoning About Object Relationships
T. Malisiewicz, A. Efros
Beyond Convexity: Online Submodular Minimization
E. Hazan, S. Kale
Bilinear classifiers for visual recognition
H. Pirsiavash, D. Ramanan, C. Fowlkes
Boosting with Spatial Regularization
Z. Xiang, Y. Xi, U. Hasson, P. Ramadge
Bootstrapping from Game Tree Search
J. Veness, D. Silver, W. Uther, A. Blair
Breaking Boundaries Between Induction Time and Diagnosis Time Active Information Acquisition
A. Kapoor, E. Horvitz
Canonical Time Warping for Alignment of Human Behavior
F. Zhou, F. De la Torre
Clustering sequence sets for motif discovery
J. Kim, S. Choi
Code-specific policy gradient rules for spiking neurons
H. Sprekeler, G. Hennequin, W. Gerstner
Complexity of Decentralized Control: Special Cases
M. Allen, S. Zilberstein
Compositionality of optimal control laws
E. Todorov
Compressed Least-Squares Regression
O. Maillard, R. Munos
Conditional Neural Fields
J. Peng, L. Bo, J. Xu
Conditional Random Fields with High-Order Features for Sequence Labeling
N. Ye, W. Lee, H. Chieu, D. Wu
Constructing Topological Maps using Markov Random Fields and Loop-Closure Detection
R. Anati, K. Daniilidis
Construction of Nonparametric Bayesian Models from Parametric Bayes Equations
P. Orbanz
Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation
H. Maei, C. Szepesvari, S. Batnaghar, D. Precup, D. Silver, R. Sutton
Convex Relaxation of Mixture Regression with Efficient Algorithms
N. Quadrianto, T. Caetano, J. Lim, D. Schuurmans
Correlation Coefficients are Insufficient for Analyzing Spike Count Dependencies
A. Onken, S. Grünewälder, K. Obermayer
Data-driven calibration of linear estimators with minimal penalties
S. Arlot, F. Bach
Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process
C. Wang, D. Blei
Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning
A. Hsu, T. Griffiths
Directed Regression
Y. Kao, B. Van Roy, X. Yan
Dirichlet-Bernoulli Alignment: A Generative Model for Multi-Class Multi-Label Multi-Instance Corpora
S. Yang, H. Zha, B. Hu
Discrete MDL Predicts in Total Variation
M. Hutter
Discriminative Network Models of Schizophrenia
G. Cecchi, I. Rish, B. Thyreau, B. Thirion, M. Plaze, M. Paillere-Martinot, J. Martinot, J. Poline
Distribution-Calibrated Hierarchical Classi?cation
O. Dekel
Distribution Matching for Transduction
N. Quadrianto, J. Petterson, A. Smola
Dual Averaging Method for Regularized Stochastic Learning and Online Optimization
L. Xiao
DUOL: A Double Updating Approach for Online Learning
P. Zhao, S. Hoi, R. Jin
Efficient and Accurate Lp-Norm Multiple Kernel Learning
M. Kloft, U. Brefeld, S. Sonnenburg, P. Laskov, K. Müller, A. Zien
Efficient Bregman Range Search
L. Cayton
Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models
G. Mann, R. McDonald, M. Mohri, N. Silberman, D. Walker
Efficient Learning using Forward-Backward Splitting
J. Duchi, Y. Singer
Efficient Match Kernel between Sets of Features for Visual Recognition
L. Bo, C. Sminchisescu
Efficient Moments-based Permutation Tests
C. Zhou, H. Wang, Y. Wang
Efficient Recovery of Jointly Sparse Vectors
L. Sun, J. Liu, J. Chen, J. Ye
Ensemble Nystrom Method
S. Kumar, M. Mohri, A. Talwalkar
Entropic Graph Regularization in Non-Parametric Semi-Supervised Classification
A. Subramanya, J. Bilmes
Estimating image bases for visual image reconstruction from human brain activity
Y. Fujiwara, Y. Miyawaki, Y. Kamitani
Evaluating multi-class learning strategies in a generative hierarchical framework for object detection
S. Fidler, M. Boben, A. Leonardis
Explaining human multiple object tracking as resource-constrained approximate inference in a dynamic probabilistic model
E. Vul, M. Frank, G. Alvarez, J. Tenenbaum
Exploring Functional Connectivities of the Human Brain using Multivariate Information Analysis
B. Chai, D. Walther, D. Beck, F. Li
Exponential Family Graph Matching and Ranking
J. Petterson, T. Caetano, J. McAuley, J. Yu
Extending Phase Mechanism to Differential Motion Opponency for Motion Pop-out
y. meng, B. Shi
FACTORIE: Probabilistic Programming via Imperatively Defined Factor Graphs
A. McCallum, K. Schultz, S. Singh
Factor Modeling for Advertisement Targeting
Y. Chen, M. Kapralov, D. Pavlov, J. Canny
Fast, smooth and adaptive regression in metric spaces
s. kpotufe
Fast Graph Laplacian Regularized Kernel Learning via Semidefinite?Quadratic?Linear Programming
X. WU, A. So, Z. Li, S. Li
Fast Image Deconvolution using Hyper-Laplacian Priors
D. Krishnan, R. Fergus
Fast Learning from Non-i.i.d. Observations
I. Steinwart, A. Christmann
Fast subtree kernels on graphs
N. Shervashidze, K. Borgwardt
Filtering Abstract Senses From Image Search Results
K. Saenko, T. Darrell
fMRI-Based Inter-Subject Cortical Alignment Using Functional Connectivity
B. Conroy, B. Singer, J. Haxby, P. Ramadge
Free energy score space
A. Perina, M. Cristani, U. Castellani, V. Murino, N. Jojic
From PAC-Bayes Bounds to KL Regularization
P. Germain, A. Lacasse, F. Laviolette, M. Marchand, S. Shanian
Functional network reorganization in motor cortex can be explained by reward-modulated Hebbian learning
R. Legenstein, S. Chase, A. Schwartz, W. Maass
Gaussian process regression with Student-t likelihood
J. Vanhatalo, P. Jylänki, A. Vehtari
Generalization Errors and Learning Curves for Regression with Multi-task Gaussian Processes
K. Chai
Graph-based Consensus Maximization among Multiple Supervised and Unsupervised Models
J. Gao, F. Liang, W. Fan, Y. Sun, J. Han
Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation
Y. Watanabe, K. Fukumizu
Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction
A. Lozano, G. Swirszcz, N. Abe
Group Sparse Coding
S. Bengio, F. Pereira, Y. Singer, D. Strelow
Heavy-Tailed Symmetric Stochastic Neighbor Embedding
Z. Yang, I. King, Z. Xu, E. Oja
Help or Hinder: Bayesian Models of Social Goal Inference
T. Ullman, C. Baker, O. Macindoe, O. Evans, N. Goodman, J. Tenenbaum
Heterogeneous multitask learning with joint sparsity constraints
X. Yang, S. Kim, E. Xing
Hierarchical Learning of Dimensional Biases in Human Categorization
K. Heller, A. Sanborn, N. Chater
Hierarchical Mixture of Classification Experts Uncovers Interactions between Brain Regions
B. Yao, D. Walther, D. Beck, F. Li
Hierarchical Modeling of Local Image Features through $L_p$-Nested Symmetric Distributions
F. Sinz, E. Simoncelli, M. Bethge
Human Rademacher Complexity
X. Zhu, T. Rogers, B. Gibson
Improving Existing Fault Recovery Policies
G. Shani, C. Meek
Indian Buffet Processes with Power-law Behavior
Y. Teh, D. Gorur
Individuation, Identification and Object Discovery
C. Kemp, A. Jern, F. Xu
Information-theoretic lower bounds on the oracle complexity of convex optimization
A. Agarwal, P. Bartlett, P. Ravikumar, M. Wainwright
Inter-domain Gaussian Processes for Sparse Inference using Inducing Features
M. Lázaro-Gredilla, A. Figueiras-Vidal
Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions
B. Sriperumbudur, K. Fukumizu, A. Gretton, G. Lanckriet, B. Schölkopf
Kernel Methods for Deep Learning
Y. Cho, L. Saul
Kernels and learning curves for Gaussian process regression on random graphs
P. Sollich, M. Urry, C. Coti
Know Thy Neighbour: A Normative Theory of Synaptic Depression
J. Pfister, P. Dayan, M. Lengyel
Label Selection on Graphs
A. Guillory, J. Bilmes
Large Scale Nonparametric Bayesian Inference: Data Parallelisation in the Indian Buffet Process
S. Mohamed, D. Knowles, Z. Ghahramani, F. Doshi-Velez
Lattice Regression
E. Garcia, M. Gupta
Learning a Small Mixture of Trees
M. Kumar, D. Koller
Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data
S. Huang, J. Li, L. Sun, J. Liu, T. Wu, K. Chen, A. Fleisher, E. Reiman, J. Ye
Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering
L. Wu, R. Jin, S. Hoi, J. Zhu, N. Yu
Learning from Multiple Partially Observed Views - an Application to Multilingual Text Categorization
M. Amini, N. Usunier, C. Goutte
Learning from Neighboring Strokes: Combining Appearance and Context for Multi-Domain Sketch Recognition
T. Ouyang, R. Davis
Learning in Markov Random Fields using Tempered Transitions
R. Salakhutdinov
Learning Label Embeddings for Nearest-Neighbor Multi-class Classification with an Application to Speech Recognition
N. Singh-Miller, M. Collins
Learning models of object structure
J. Schlecht, K. Barnard
Learning Non-Linear Combinations of Kernels
C. Cortes, M. Mohri, A. Rostamizadeh
Learning to Explore and Exploit in POMDPs
C. Cai, X. Liao, L. Carin
Learning to Hash with Binary Reconstructive Embeddings
B. Kulis, T. Darrell
Learning to Rank by Optimizing NDCG Measure
H. Valizadegan, R. Jin, R. Zhang, J. Mao
Learning transport operators for image manifolds
J. Culpepper, B. Olshausen
Learning with Compressible Priors
V. Cevher
Linear-time Algorithms for Pairwise Statistical Problems
P. Ram, D. Lee, W. March, A. Gray
Linearly constrained Bayesian matrix factorization for blind source separation
M. Schmidt
Locality-sensitive binary codes from shift-invariant kernels
M. Raginsky, S. Lazebnik
Localizing Bugs in Program Executions with Graphical Models
L. Dietz, V. Dallmeier, A. Zeller, T. Scheffer
Local Rules for Global MAP: When Do They Work ?
K. Jung, P. Kohli, D. Shah
Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness
G. Raskutti, M. Wainwright, B. Yu
Manifold Embeddings for Model-Based Reinforcement Learning under Partial Observability
K. Bush, J. Pineau
Manifold Regularization for SIR with Rate Root-n Convergence
W. Bian, D. Tao
Matrix Completion from Noisy Entries
R. Keshavan, A. Montanari, S. Oh
Matrix Completion from Power-Law Distributed Samples
R. Meka, P. Jain, I. Dhillon
Maximin affinity learning of image segmentation
S. Turaga, K. Briggman, M. Helmstaedter, W. Denk, H. Seung
Maximum likelihood trajectories for continuous-time Markov chains
T. Perkins
Measuring Invariances in Deep Networks
I. Goodfellow, q. le, A. Saxe, A. Ng
Measuring model complexity with the prior predictive
W. Vanpaemel
Modeling Social Annotation Data with Content Relevance using a Topic Model
T. Iwata, T. Yamada, N. Ueda
Modeling the spacing effect in sequential category learning
H. Lu, M. Weiden, A. Yuille
Modelling Relational Data using Bayesian Clustered Tensor Factorization
I. Sutskever, R. Salakhutdinov, J. Tenenbaum
Monte Carlo Sampling for Regret Minimization in Extensive Games
M. Lanctot, K. Waugh, M. Zinkevich, M. Bowling
Multi-Label Prediction via Compressed Sensing
D. Hsu, S. Kakade, J. Langford, T. Zhang
Multi-Label Prediction via Sparse Infinite CCA
P. Rai, H. Daume III
Multi-Step Dyna Planning for Policy Evaluation and Control
H. Yao, R. Sutton, S. Bhatnagar, D. Diao, C. Szepesvari
Multiple Incremental Decremental Learning of Support Vector Machines
M. Karasuyama, I. Takeuchi
Nash Equilibria of Static Prediction Games
M. Brückner, T. Scheffer
Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling
L. Shi, T. Griffiths
Neurometric function analysis of population codes
P. Berens, S. Gerwinn, A. Ecker, M. Bethge
No evidence for active sparsification in the visual cortex
P. Berkes, B. White, J. Fiser
Noise Characterization, Modeling, and Reduction for In Vivo Neural Recording
Z. Yang, Q. Zhao, E. Keefer, W. Liu
Noisy Generalized Binary Search
R. Nowak
Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations
M. Zhou, H. Chen, J. Paisley, L. Ren, G. Sapiro, L. Carin
Non-stationary continuous dynamic Bayesian networks
M. Grzegorczyk, D. Husmeier
Nonlinear directed acyclic structure learning with weakly additive noise models
R. Tillman, A. Gretton, P. Spirtes
Nonlinear Learning using Local Coordinate Coding
K. Yu, T. Zhang, Y. Gong
Nonparametric Bayesian Models for Unsupervised Event Coreference Resolution
C. Bejan, M. Titsworth, A. Hickl, S. Harabagiu
Nonparametric Bayesian Texture Learning and Synthesis
L. Zhu, Y. Chen, B. Freeman, A. Torralba
Nonparametric Greedy Algorithms for the Sparse Learning Problem
H. Liu, X. Chen
Nonparametric Latent Feature Models for Link Prediction
K. Miller, T. Griffiths, M. Jordan
Occlusive Components Analysis
J. Lucke, R. Turner, M. Sahani, M. Henniges
On Invariance in Hierarchical Models
J. Bouvrie, L. Rosasco, T. Poggio
On Learning Rotations
R. Arora
Online Learning of Assignments
M. Streeter, D. Golovin, A. Krause
On Stochastic and Worst-case Models for Investing
E. Hazan, S. Kale
On the Algorithmics and Applications of a Mixed-norm based Kernel Learning Formulation
S. Jagarlapudi, d. govindaraj, R. S, C. Bhattacharyya, A. Ben-Tal, K. Ramakrishnan
On the Convergence of the Concave-Convex Procedure
B. Sriperumbudur, G. Lanckriet
Optimal context separation of spiking haptic signals by second-order somatosensory neurons
R. Brasselet, R. Johansson, A. Arleo
Optimal Scoring for Unsupervised Learning
Z. Zhang, g. dai
Optimizing Multi-Class Spatio-Spectral Filters via Bayes Error Estimation for EEG Classification
W. Zheng, Z. Lin
Orthogonal Matching Pursuit From Noisy Random Measurements: A New Analysis
A. Fletcher, S. Rangan
Parallel Inference for Latent Dirichlet Allocation on Graphics Processing Units
F. Yan, N. XU, Y. Qi
Particle-based Variational Inference for Continuous Systems
A. Ihler, A. Frank, P. Smyth
Perceptual Multistability as Markov Chain Monte Carlo Inference
S. Gershman, E. Vul, J. Tenenbaum
Periodic Step Size Adaptation for Single Pass On-line Learning
C. Hsu, Y. Chang, H. Huang, Y. Lee
Polynomial Semantic Indexing
B. Bai, J. Weston, D. Grangier, R. Collobert, K. Sadamasa, Y. Qi, C. Cortes, M. Mohri
Positive Semidefinite Metric Learning with Boosting
C. Shen, J. Kim, L. Wang, A. van den Hengel
Posterior vs Parameter Sparsity in Latent Variable Models
J. Graca, K. Ganchev, B. Taskar, F. Pereira
Potential-Based Agnostic Boosting
A. Kalai, V. Kanade
Predicting the Optimal Spacing of Study: A Multiscale Context Model of Memory
M. Mozer, H. Pashler, N. Cepeda, R. Lindsey, E. Vul
Probabilistic Relational PCA
W. Li, D. Yeung, Z. Zhang
Quantification and the language of thought
C. Kemp
Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic Programs
A. Bouchard-Côté, S. Petrov, D. Klein
Rank-Approximate Nearest Neighbor Search: Retaining Meaning and Speed in High Dimensions
P. Ram, D. Lee, H. Ouyang, A. Gray
Ranking Measures and Loss Functions in Learning to Rank
C. Wei, T. Liu, Y. Lan, Z. Ma, H. Li
Reading Tea Leaves: How Humans Interpret Topic Models
J. Chang, J. Boyd-Graber, S. Gerrish, C. Wang, D. Blei
Reconstruction of Sparse Circuits Using Multi-neuronal Excitation (RESCUME)
T. Hu, A. Leonardo, D. Chklovskii
Region-based Segmentation and Object Detection
S. Gould, T. Gao, D. Koller
Regularized Distance Metric Learning:Theory and Algorithm
R. Jin, S. Wang, Y. Zhou
Replacing supervised classification learning by Slow Feature Analysis in spiking neural networks
S. Klampfl, W. Maass
Replicated Softmax: an Undirected Topic Model
R. Salakhutdinov, G. Hinton
Rethinking LDA: Why Priors Matter
H. Wallach, D. Mimno, A. McCallum
Riffled Independence for Ranked Data
J. Huang, C. Guestrin
Robust Nonparametric Regression with Metric-Space Valued Output
M. Hein
Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices via Convex Optimization
J. Wright, A. Balasubramanian, S. Rao, Y. Peng, Y. Ma
Robust Value Function Approximation Using Bilinear Programming
M. Petrik, S. Zilberstein
Segmenting Scenes by Matching Image Composites
B. Russell, A. Efros, J. Sivic, B. Freeman, A. Zisserman
Semi-Supervised Learning in Gigantic Image Collections
R. Fergus, Y. Weiss, A. Torralba
Semi-supervised Learning using Sparse Eigenfunction Bases
K. Sinha, M. Belkin
Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction
K. Kim, F. Steinke, M. Hein
Sensitivity analysis in HMMs with application to likelihood maximization
P. Coquelin, R. Deguest, R. Munos
Sequential effects reflect parallel learning of multiple environmental regularities
M. Wilder, M. Jones, M. Mozer
Sharing Features among Dynamical Systems with Beta Processes
E. Fox, E. Sudderth, M. Jordan, A. Willsky
Skill Discovery in Continuous Reinforcement Learning Domains using Skill Chaining
G. Konidaris, A. Barto
Slow, Decorrelated Features for Pretraining Complex Cell-like Networks
J. Bergstra, Y. Bengio
Slow Learners are Fast
M. Zinkevich, A. Smola, J. Langford
Solving Stochastic Games
L. Mac Dermed, C. Isbell
Sparse and Locally Constant Gaussian Graphical Models
J. Honorio, L. Ortiz, D. Samaras, N. Paragios, R. Goldstein
Sparse Estimation Using General Likelihoods and Non-Factorial Priors
D. Wipf, S. Nagarajan
Sparse Metric Learning via Smooth Optimization
Y. Ying, K. Huang, C. Campbell
Sparsistent Learning of Varying-coefficient Models with Structural Changes
M. Kolar, L. Song, E. Xing
Spatial Normalized Gamma Processes
V. Rao, Y. Teh
Speaker Comparison with Inner Product Discriminant Functions
W. Campbell, Z. Karam, D. Sturim
Speeding up Magnetic Resonance Image Acquisition by Bayesian Multi-Slice Adaptive Compressed Sensing
M. Seeger
Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data
B. Nadler, N. Srebro, X. Zhou
Statistical Consistency of Top-k Ranking
f. xia, T. Liu, H. Li
Statistical Models of Linear and Nonlinear Contextual Interactions in Early Visual Processing
R. Coen-Cagli, P. Dayan, O. Schwartz
STDP enables spiking neurons to detect hidden causes of their inputs
B. Nessler, M. Pfeiffer, W. Maass
Strategy Grafting in Extensive Games
K. Waugh, N. Bard, M. Bowling
Streaming k-means approximation
N. Ailon, R. Jaiswal, C. Monteleoni
Streaming Pointwise Mutual Information
B. Van Durme, A. Lall
Structural inference affects depth perception in the context of potential occlusion
I. Stevenson, K. Koerding
Structured output regression for detection with partial truncation
A. Vedaldi, A. Zisserman
Subject independent EEG-based BCI decoding
S. Fazli, C. Grozea, M. Danóczy, B. Blankertz, F. Popescu, K. Muller
Submanifold density estimation
A. Ozakin, A. Gray
Submodularity Cuts and Applications
Y. Kawahara, K. Nagano, K. Tsuda, J. Bilmes
Sufficient Conditions for Agnostic Active Learnable
L. Wang
The "tree-dependent components" of natural scenes are edge filters
D. Zoran, Y. Weiss
The Infinite Partially Observable Markov Decision Process
F. Doshi-Velez
The Ordered Residual Kernel for Robust Motion Subspace Clustering
T. Chin, H. Wang, D. Suter
The Wisdom of Crowds in the Recollection of Order Information
M. Steyvers, M. Lee, B. Miller, P. Hemmer
Thresholding Procedures for High Dimensional Variable Selection and Statistical Estimation
S. Zhou
Time-rescaling methods for the estimation and assessment of non-Poisson neural encoding models
J. Pillow
Time-Varying Dynamic Bayesian Networks
L. Song, M. Kolar, E. Xing
Toward Provably Correct Feature Selection in Arbitrary Domains
D. Margaritis
Tracking Dynamic Sources of Malicious Activity at Internet Scale
S. Venkataraman, A. Blum, D. Song, S. Sen, O. Spatscheck
Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference
M. Wick, K. Rohanimanesh, S. Singh, A. McCallum
Unsupervised Detection of Regions of Interest Using Iterative Link Analysis
G. Kim, A. Torralba
Unsupervised feature learning for audio classification using convolutional deep belief networks
H. Lee, P. Pham, Y. Largman, A. Ng
Unsupervised Feature Selection for the $k$-means Clustering Problem
C. Boutsidis, M. Mahoney, P. Drineas
Variational Gaussian-process factor analysis for modeling spatio-temporal data
J. Luttinen, A. Ilin
Variational Inference for the Nested Chinese Restaurant Process
C. Wang, D. Blei
Which graphical models are difficult to learn?
A. Montanari, J. Ayres Pereira
White Functionals for Anomaly Detection in Dynamical Systems
M. Cuturi, J. Vert, A. d'Aspremont
Who’s Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation
J. Luo, B. Caputo, V. Ferrari
Whose Vote Should Count More: Optimal Integration of Labels from Labelers of Unknown Expertise
J. Whitehill, P. Ruvolo, T. Wu, J. Bergsma, j. movellan
Zero-shot Learning with Semantic Output Codes
M. Palatucci, D. Pomerleau, G. Hinton, T. Mitchell
Keywords: Accepted papers list. Acceptance Rate. EI Compendex. Engineering Index. ISTP index. ISI index. Impact Factor.
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