Accepted Papers
- $L_1$-Penalized Robust Estimation for a Class of Inverse Problems Arising in Multiview Geometry
A. 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, A. Slivkins, 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, L. Sun, 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 Classification
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. ShiUpdateMe, 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
W. Chen, 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. Müller - 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. Bento - White Functionals for Anomaly Detection in Dynamical Systems
M. Cuturi, J. Vert, A. d'Aspremont - Whose Vote Should Count More: Optimal Integration of Labels from Labelers of Unknown Expertise
J. Whitehill, P. Ruvolo, T. Wu, J. Bergsma, j. movellan - Who’s Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation
J. Luo, B. Caputo, V. Ferrari - Zero-shot Learning with Semantic Output Codes
M. Palatucci, D. Pomerleau, G. Hinton, T. Mitchell
