Accepted Papers
- (Not) Sparse Coding
D. Bagnell, D. Bradley - A "Shape Aware" Model for semi-supervised Learning of Objects and its Context
A. Gupta, J. Shi, L. Davis - A Bayesian Approach for Extracting State Transition Dynamics from Multiple Spike Trains
K. Katahira, J. Nishikawa, K. Okanoya, M. Okada - Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes
B. Calderhead, M. Girolami, N. Lawrence - A computational model of hippocampal function in trace conditioning
E. Ludvig, R. Sutton, E. Verbeek, J. Kehoe - A Convergent O(n) Temporal-difference Algorithm for Off-policy Learning with Linear Function Approxi
R. Sutton, C. Szepesvari, H. Maei - A Convex Upper Bound on the Log-Partition Function
L. El Ghaoui, A. Gueye - Adapting to a Market Shock: Optimal Sequential Market-Making
S. Das, M. Magdon-Ismail - Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models
T. Zhang - Adaptive Martingale Boosting
P. Long, R. Servedio - Adaptive Template Matching with Shift-Invariant Semi-NMF
J. Le Roux, A. de Cheveigné, L. Parra - A general framework for investigating how far the decoding process in the brain can be simplified
M. Oizumi, T. Ishii, K. Ishibashi, T. Hosoya, M. Okada - A Hierarchical Image Model for Polynomial-Time 2D Parsing
L. Zhu, Y. Chen, Y. Lin, A. Yuille - Algorithms for Infinitely Many-Armed Bandits
Y. Wang, J. Audibert, R. Munos - A Massively Parallel Digital Learning Processor
H. Graf, H. Cadambi, I. Durdanovic, V. Jakkula, M. Sankaradass, E. Cosatto, S. Chakradhar - A mixture model for the evolution of gene expression in non-homogeneous datasets
G. Quon, Y. Teh, E. Chan, M. Brudno, T. Hughes, Q. Morris - An Algorithm for Microchip Spike Sorting
Z. Yang, W. Liu - Analyzing human feature learning as nonparametric Bayesian inference
J. Austerweil, T. Griffiths - Analyzing the Monotonic Feature Abstraction for Text Classification
D. Downey, O. Etzioni - An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering
D. Gorur, Y. Teh - An empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis
G. Schweikert, C. Widmer, B. Schölkopf, G. Raetsch - An Extended Level Method for Efficient Multiple Kernel Learning
Z. Xu, R. Jin, I. King, M. Lyu - An Homotopy Algorithm for the Lasso with Online Observations
P. Garrigues, L. El Ghaoui - An ideal observer model of infant object perception
C. Kemp, F. Xu - An improved estimator of Variance Explained in the presence of noise
R. Haefner, B. Cumming - An interior-point stochastic approximation method and an L1-regularized delta rule
P. Carbonetto, M. Schmidt, N. de Freitas - An Online Algorithm for Maximizing Submodular Functions
M. Streeter, D. Golovin - A rational model of preference learning and choice prediction by children
C. Lucas, T. Griffiths, F. Xu, C. Fawcett - Artificial Olfactory Brain for Mixture Identification
M. Muezzinoglu, A. Vergara, R. Huerta, T. Nowotny, N. Rulkov, H. Abarbanel, A. Selverston, M. Rabinovich - A Scalable Hierarchical Distributed Language Model
A. Mnih, G. Hinton - A spatially varying two-sample recombinant coalescent, with applications to HIV escape response
A. Braunstein, Z. Wei, S. Jensen, J. McAuliffe - Asynchronous Distributed Learning of Topic Models
A. Asuncion, P. Smyth, M. Welling - A Transductive Bound for the Voted Classifier with an Application to Semi-supervised Learning
M. Amini, N. Usunier, F. Laviolette - Automatic online tuning for fast Gaussian summation
V. Morariu, B. Srinivasan, V. Raykar, R. Duraiswami, L. Davis - Bayesian Experimental Design of Magnetic Resonance Imaging Sequences
M. Seeger, H. Nickisch, R. Pohmann, B. Schölkopf - Bayesian Exponential Family PCA
S. Mohamed, K. Heller, Z. Ghahramani - Bayesian Kernel Shaping for Learning Control
J. Ting, M. Kalakrishnan, S. Vijayakumar, S. Schaal - Bayesian Model of Behaviour in Economic Games
D. Ray, B. King-Casas, P. Montague, P. Dayan - Bayesian Network Score Approximation using a Metagraph Kernel
B. Yackley, E. Corona, T. Lane - Bayesian Synchronous Grammar Induction
P. Blunsom, T. Cohn, M. Osborne - Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree
D. Weinshall, H. Hermansky, A. Zweig, L. Jie, H. Jimison, F. Ohl, M. Pavel - Biasing Approximate Dynamic Programming with a Lower Discount Factor
M. Petrik, B. Scherrer - Bio-inspired Real Time Sensory Map Realignment in a Robotic Barn Owl
J. Huo, Z. Yang, A. Murray - Bounding Performance Loss in Approximate MDP Homomorphisms
D. Precup, J. Taylor, P. Panangaden - Bounds on marginal probability distributions
J. Mooij, H. Kappen - Breaking Audio CAPTCHAs with Machine Learning Techniques
J. Tam, J. Simsa, S. Hyde, L. von Ahn - Cascaded Classification Models: Combining Models for Holistic Scene Understanding
G. Heitz, S. Gould, A. Saxena, D. Koller - Cell Assemblies in Large Sparse Inhibitory Networks of Biologically Realistic Spiking Neurons
A. Ponzi, J. Wickens - Characteristic Kernels on Groups and Semigroups
K. Fukumizu, B. Sriperumbudur, A. Gretton, B. Schölkopf - Characterizing neural dependencies with Poisson copula models
P. Berkes, F. Wood, J. Pillow - Clustered Multi-Task Learning: A Convex Formulation
L. Jacob, F. Bach, J. Vert - Clustering via LP-based Stabilities
N. Komodakis, N. Paragios, G. Tziritas - Clusters and Coarse Partitions in LP Relaxations
D. Sontag, A. Globerson, T. Jaakkola - Comparing model predictions of response bias and variance in cue combination
R. Natarajan, I. Murray, L. Shams, R. Zemel - Competing RBM density models for classification of fMRI images
T. Schmah, G. Hinton, R. Zemel - Continuously-adaptive discretization for message-passing algorithms
M. Isard, J. MacCormick, K. Achan - Convergence and Rate of Convergence of A Manifold-Based Dimension Reduction
A. Smith, X. Huo, H. Zha - Correlated Bigram LSA for Unsupervised Language Model Adaptation
Y. Tam, T. Schultz - Counting Solution Clusters Using Belief Propagation
L. Kroc, A. Sabharwal, B. Selman - Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform
G. Cao, C. Bouman - Cyclizing Clusters via Zeta Function of a Graph
D. Zhao, X. Tang - Deep Learning with Kernel Regularization for Visual Recognition
K. Yu, W. Xu, Y. Gong - Deflation Methods for Sparse PCA
L. Mackey - Dependence of Orientation Tuning on Recurrent Excitation and Inhibition in a Network Model of V1
K. Wimmer, M. Stimberg, R. Martin, L. Schwabe, J. Mariño, J. Schummers, D. Lyon, M. Sur, K. Obermayer - Dependent Dirichlet Process Spike Sorting
J. Gasthaus, F. Wood, D. Gorur, Y. Teh - Depression: an RL formulation and a behavioural test
Q. Huys, j. vogelstein, P. Dayan - Designing neurophysiology experiments to optimally constrain receptive field models along parametric
J. Lewi, R. Butera, L. Paninski - Diffeomorphic Dimensionality Reduction
C. Walder, B. Schölkopf - Dimensionality Reduction for Data in Multiple Feature Representations
Y. Lin, T. Liu, C. Fuh - DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification
S. Lacoste-Julien, F. Sha, M. Jordan - Domain Adaptation with Multiple Sources
Y. Mansour, M. Mohri, A. Rostamizadeh - Dynamic Visual Attention: Searching for coding length increments
X. Hou, L. Zhang - Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance
J. Hill, J. Farquhar, S. Martens, F. Bießmann, B. Schölkopf - Efficient Direct Density Ratio Estimation for Non-stationarity Adaptation and Outlier Detection
T. Kanamori, S. Hido, M. Sugiyama - Efficient Exact Inference in Planar Ising Models
N. Schraudolph, D. Kamenetsky - Efficient Inference in Phylogenetic InDel Trees
A. Bouchard-Côté, M. Jordan, D. Klein - Efficient Sampling for Gaussian Process Inference using Control Variables
M. Titsias, N. Lawrence, M. Rattray - Empirical performance maximization for linear rank statistics
S. Clémençon, N. Vayatis - Estimating Robust Query Models with Convex Optimization
K. Collins-Thompson - Estimating the Location and Orientation of Complex, Correlated Neural Activity using MEG
D. Wipf, J. Owen, H. Attias, K. Sekihara, S. Nagarajan - Estimating vector fields using sparse basis field expansions
S. Haufe, V. Nikulin, A. Ziehe, K. Muller, G. Nolte - Estimation of Information Theoretic Measures for Continuous Random Variables
F. Perez-Cruz - Evaluating probabilities under high-dimensional latent variable models
I. Murray, R. Salakhutdinov - Exact Convex Confidence-Weighted Learning
K. Crammer, M. Dredze, F. Pereira - Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning
F. Bach - Extended Grassmann Kernels for Subspace-Based Learning
J. Hamm, D. Lee - Fast Computation of Posterior Mode in Multi-Level Hierarchical Models
D. Agarwal, L. Zhang - Fast High-dimensional Kernel Summations Using the Monte Carlo Multipole Method
D. Lee, A. Gray - Fast Prediction on a Tree
M. Herbster, M. Pontil, S. Rojas Galeano - Fast Rates for Regularized Objectives
K. Sridharan, S. Shalev-Shwartz, N. Srebro - Finding Latent Causes in Causal Networks: an Efficient Approach Based on Markov Blankets
J. Pellet, A. Elisseeff - Fitted Q-iteration by Advantage Weighted Regression
G. Neumann, J. Peters - From Online to Batch Learning with Cutoff-Averaging
O. Dekel - Gates
T. Minka, J. Winn - Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity
B. Yu, J. Cunningham, G. Santhanam, S. Ryu, K. Shenoy, M. Sahani - Generative and Discriminative Learning with Unknown Labeling Bias
M. Dudik, S. Phillips - Global Ranking Using Continuous Conditional Random Fields
T. Qin, T. Liu, X. Zhang, D. Wang, H. Li - Goal-directed decision making in prefrontal cortex: a computational framework
M. Botvinick, J. An - Grouping Contours Via a Related Image
P. Srinivasan, L. Wang, J. Shi - Hebbian Learning of Bayes Optimal Decisions
B. Nessler, M. Pfeiffer, W. Maass - Hierarchical Conditional Random Fields for Recursive Sequential Data
T. Tran, D. Phung, H. Bui, S. Venkatesh - Hierarchical Fisher Kernels for Longitudinal Data
Z. Lu, T. Leen, J. Kaye - High-dimensional union support recovery in multivariate regression
G. Obozinski, M. Wainwright, M. Jordan - How memory biases affect information transmission: A rational analysis of serial reproduction
J. Xu, T. Griffiths - Human Active Learning
X. Zhu, R. Castro, T. Rogers, R. Nowak, R. Qian, C. Kalish - ICA based on a Smooth Estimation of the Differential Entropy
L. Faivishevsky, J. Goldberger - Implicit Mixtures of Restricted Boltzmann Machines
V. Nair, G. Hinton - Improved Moves for Truncated Convex Models
P. Mudigonda, P. Torr - Improving on Expectation Propagation
M. Opper, U. Paquet, O. Winther - Inferring rankings under constrained sensing
S. Jagabathula, D. Shah - Influence of graph construction on graph-based clustering measures
M. Maier, U. von Luxburg, M. Hein - Integrating Locally Learned Causal Structures with Overlapping Variables
R. Tillman, D. Danks, C. Glymour - Interpreting the neural code with Formal Concept Analysis
D. Endres, P. Foldiak - Kernel-ARMA for Hand Tracking and Brain-Machine interfacing During 3D Motor Control
L. Shpigelman, H. Lalazar, E. Vaadia - Kernel Change-point Analysis
Z. Harchaoui, F. Bach, E. Moulines - Kernelized Sorting
N. Quadrianto, L. Song, A. Smola - Kernel Measures of Independence for non-iid Data
X. Zhang, L. Song, A. Gretton, A. Smola - Large Margin Taxonomy Embedding for Document Categorization
K. Weinberger, O. Chapelle - Learning a discriminative hidden part model for human action recognition
Y. Wang, G. Mori - Learning Bounded Treewidth Bayesian Networks
G. Elidan, S. Gould - Learning Hybrid Models for Image Annotation with Partially Labeled Data
X. He, R. Zemel - Learning Taxonomies by Dependence Maximization
M. Blaschko, A. Gretton - Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text
Y. Zhang, J. Schneider, A. Dubrawski - Learning to Use Working Memory in Partially Observable Environments through Dopaminergic Reinforcement
M. Todd, Y. Niv, J. Cohen - Learning Transformational Invariants from Time-Varying Natural Images
C. Cadieu, B. Olshausen - Learning with Consistency between Inductive Functions and Kernels
H. Yang, I. King, M. Lyu - Linear Classification and Selective Sampling Under Low Noise Conditions
G. Cavallanti, N. Cesa-Bianchi, C. Gentile - Load and Attentional Bayes
P. Dayan - Local Gaussian Process Regression for Real Time Online Model Learning
D. Nguyen-Tuong, M. Seeger, J. Peters - Localized Sliced Inverse Regression
Q. Wu, S. Mukherjee, F. Liang - LOOPS: Localizing Object Outlines using Probabilistic Shape
G. Heitz, G. Elidan, B. Packer, D. Koller - MAS: a multiplicative approximation scheme for probabilistic inference
Y. Wexler, C. Meek - MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual Features
T. Kim, R. Cipolla - MDPs with Non-Deterministic Policies
M. Milani Fard, J. Pineau - Measures of Clustering Quality: A Working Set of Axioms for Clustering
S. Ben-David, M. Ackerman - Mind the Duality Gap: Logarithmic regret algorithms for online optimization
S. Shalev-Shwartz, S. Kakade - Mixed Membership Stochastic Blockmodels
E. Airoldi, D. Blei, S. Fienberg, E. Xing - Modeling human function learning with Gaussian processes
T. Griffiths, C. Lucas, J. Williams, M. Kalish - Modeling Short-term Noise Dependence of Spike Counts in Macaque Prefrontal Cortex
A. Onken, S. Grünewälder, M. Munk, K. Obermayer - Modeling the effects of memory on human online sentence processing with particle filters
R. Levy, F. Reali, T. Griffiths - Model selection and velocity estimation using novel priors for motion patterns
A. Yuille, S. Wu, H. Lu - Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of \ell_1-regularizedMLE
P. Ravikumar, G. Raskutti, M. Wainwright, B. Yu - Mortal Multi-Armed Bandits
F. Radlinski, D. Chakrabarti, R. Kumar, E. Upfal - Multi-Agent Filtering with Infinitely Nested Beliefs
L. Zettlemoyer, B. Milch, L. Kaelbling - Multi-label Multiple Kernel Learning
S. Ji, L. Sun, R. Jin, J. Ye - Multi-Level Active Prediction of Useful Image Annotations for Recognition
S. Vijayanarasimhan, K. Grauman - Multi-resolution Exploration in Continuous Spaces
A. Nouri, M. Littman - Multi-stage Convex Relaxation for Learning with Sparse Regularization
T. Zhang - Multi-task Gaussian Process Learning of Robot Inverse Dynamics
K. Chai, C. Williams, S. Klanke, S. Vijayakumar - Multiscale Random Fields with Application to Contour Grouping
L. Latecki, C. Lu, M. Sobel, X. Bai - Natural Image Denoising with Convolutional Networks
V. Jain, H. Seung - Near-minimax recursive density estimation on the binary hypercube
M. Raginsky, S. Lazebnik, R. Willett, J. Silva - Near-optimal Regret Bounds for Reinforcement Learning
P. Auer, T. Jaksch, R. Ortner - Non-parametric Regression Between Manifolds
F. Steinke, M. Hein - Non-stationary dynamic Bayesian networks
J. Robinson, A. Hartemink - Nonlinear causal discovery with additive noise models
P. Hoyer, D. Janzing, J. Mooij, J. Peters, B. Schölkopf - Nonparametric Bayesian Learning of Switching Linear Dynamical Systems
E. Fox, E. Sudderth, M. Jordan, A. Willsky - Nonparametric Bayesian Sparse Hierarchical Factor Modeling and Regression
P. Rai, H. Daume III - Nonparametric regression and classification with joint sparsity constraints
H. Liu, J. Lafferty, L. Wasserman - Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images
P. Ravikumar, V. Vu, B. Yu, T. Naselaris, K. Kay, J. Gallant - Nonrigid Structure from Motion in Trajectory Space
I. Akhter, Y. Sheikh, S. Khan, T. Kanade - Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks
A. Graves, J. Schmidhuber - On-Line Prediction on Large Diameter Graphs
M. Herbster, M. Pontil, G. Lever - On Bootstrapping the ROC Curve
P. Bertail, S. Clémençon, N. Vayatis - On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing
B. Schrauwen, L. Buesing, R. Legenstein - One sketch for all: Theory and Application of Conditional Random Sampling
P. Li, K. Church, T. Hastie - Online Metric Learning and Fast Similarity Search
P. Jain, B. Kulis, I. Dhillon, K. Grauman - Online Models for Content Optimization
D. Agarwal, B. Chen, P. Elango, N. Motgi, S. Park, R. Ramakrishnan, S. Roy, J. Zachariah - Online Optimization in X-Armed Bandits
S. Bubeck, R. Munos, G. Stoltz, C. Szepesvari - On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization
S. Kakade, K. Sridharan, A. Tewari - On the Design of Loss Functions for Classification: theory, robustness to outliers, and SavageBoost
H. Masnadi-Shirazi, N. Vasconcelos - On the Efficient Minimization of Classification Calibrated Surrogates
R. Nock, F. NIELSEN - On the equivalence between TD learning and differential Hebbian learning using a local third factor
C. Kolodziejski, B. Porr, M. Tamosiunaite, F. Woergoetter - On the Generalization Ability of Online Strongly Convex Programming Algorithms
S. Kakade, A. Tewari - On the Reliability of Clustering Stability in the Large Sample Regime
O. Shamir, N. Tishby - Optimal Response Initiation: Why Recent Experience Matters
M. Jones, M. Mozer, S. Kinoshita - Optimization on a Budget: A Reinforcement Learning Approach
P. Ruvolo, I. Fasel, j. movellan - Overlaying classifiers: a practical approach for optimal ranking
S. Clémençon, N. Vayatis - Partially Observed Maximum Entropy Discrimination Markov Networks
J. Zhu, E. Xing, B. Zhang - Particle Filter-based Policy Gradient in POMDPs
P. Coquelin, R. Deguest, R. Munos - Performance analysis for L_2 kernel classification
J. Kim, C. Scott - Phase transitions for high-dimensional joint support recovery
S. Negahban, M. Wainwright - Playing Pinball with non-invasive BCI
M. Tangermann (ne Schröder), M. Krauledat, K. Grzeska, M. Sagebaum, B. Blankertz, K. Muller - Policy Search for Motor Primitives in Robotics
J. Kober, J. Peters - Posterior Consistency of the Silverman g-prior in Bayesian Model Choice
Z. Zhang, M. Jordan, D. Yeung - Predicting the Geometry of Metal Binding Sites from Protein Sequence
P. Frasconi, A. Passerini - Predictive Indexing for Fast Search
S. Goel, J. Langford, A. Strehl - Privacy-preserving logistic regression
K. Chaudhuri, C. Monteleoni - Probabilistic detection of short events, with application to critical care monitoring
N. Aleks, S. Russell, M. Madden, D. Morabito, G. Manley, K. Staudenmayer, M. Cohen - PSDBoost: Matrix-Generation Linear Programming for Positive Semidefinite Matrices Learning
C. Shen, A. Welsh, L. Wang - QUIC-SVD: Fast SVD Using Cosine Trees
M. Holmes, A. Gray, C. Isbell - Rademacher Complexity Bounds for Non-I.I.D. Processes
M. Mohri, A. Rostamizadeh - Reconciling Real Scores with Binary Comparisons: A Unified Logistic Model for Ranking
N. Ailon - Reducing statistical dependencies in natural signals using radial Gaussianization
S. Lyu, E. Simoncelli - Regularized Co-Clustering with Dual Supervision
V. Sindhwani, J. Hu, A. Mojsilovic - Regularized Learning with Networks of Features
T. Sandler, J. Blitzer, P. Talukdar, L. Ungar - Regularized Policy Iteration
A. Farahmand, M. Ghavamzadeh, C. Szepesvari, S. Mannor - Relative Margin Machines
P. Shivaswamy, T. Jebara - Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation
I. Mukherjee, D. Blei - Resolution Limits of Sparse Coding in High Dimensions
A. Fletcher, S. Rangan, V. Goyal - Risk Bounds for Randomized Sample Compressed Classifiers
M. Shah - Robust Kernel Principal Component Analysis
M. Nguyen, F. De la Torre - Robust Near-Isometric Matching via Structured Learning of Graphical Models
J. McAuley, T. Caetano, A. Smola - Robust Regression and Lasso
H. Xu, C. Caramanis, S. Mannor - Scalable Algorithms for String Kernels with Inexact Matching
P. Kuksa, P. Huang, V. Pavlovic - SDL: Supervised Dictionary Learning
J. Mairal, F. Bach, J. Ponce, G. Sapiro, A. Zisserman - Self-organization using dynamical synapses
V. Gómez, A. Kaltenbrunner, V. López, H. Kappen - Semi-supervised Learning with Weakly-Related Unlabeled Data : Towards Better Text Categorization
L. Yang, R. Jin, R. Sukthankar - Sequential effects: Superstition or rational behavior?
A. Yu, J. Cohen - Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes
E. Sudderth, M. Jordan - Short-Term Depression in VLSI Stochastic Synapse
P. Xu, T. Horiuchi, P. Abshire - Signal-to-Noise Ratio Analysis of Policy Gradient Algorithms
J. Roberts, R. Tedrake - Simple Local Models for Complex Dynamical Systems
E. Talvitie, S. Singh - Skill Characterization Based on Betweenness
O. Simsek, A. Barto - Sparse Convolved Gaussian Processes for Multi-ouptut Regression
M. Alvarez, N. Lawrence - Sparse Online Learning via Truncated Gradient
J. Langford, L. Li, T. Zhang - Sparse probabilistic projections
C. Archambeau, F. Bach - Sparse Signal Recovery Using Markov Random Fields
V. Cevher, M. Duarte, C. Hegde, R. Baraniuk - Sparsity of SVMs that use the epsilon-insensitive loss
I. Steinwart, A. Christmann - Spectral Clustering with Perturbed Data
L. Huang, D. Yan, M. Jordan, N. Taft - Spectral Hashing
Y. Weiss, A. Torralba, R. Fergus - Stochastic Relational Models for Large-scale Dyadic Data using MCMC
S. Zhu, K. Yu, Y. Gong - Stress, noradrenaline, and realistic prediction of mouse behaviour using reinforcement learning
G. Luksys, C. Sandi, W. Gerstner - Structured ranking learning using cumulative distribution networks
J. Huang, B. Frey - Structure Learning in Human Sequential Decision-Making
D. Acuna, P. Schrater - Supervised Bipartite Graph Inference
Y. Yamanishi - Supervised Exponential Family Principal Component Analysis via Convex Optimizatio
Y. Guo - Suppport Vector Machines with a Reject Option
Y. Grandvalet, J. Keshet, A. Rakotomamonjy, S. Canu - Syntactic Topic Models
J. Boyd-Graber, D. Blei - Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation
D. Di Castro, D. Volkinshtein, R. Meir - Temporal Dynamics of Cognitive Control
J. Reynolds, M. Mozer - The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction
F. Sinz, M. Bethge - The Gaussian Process Density Sampler
R. Adams, I. Murray, D. MacKay - The Infinite Factorial Hidden Markov Model
J. Van Gael, Y. Teh, Z. Ghahramani - The Mondrian Process
D. Roy, Y. Teh - Theory of matching pursuit
Z. Hussain, J. Shawe-Taylor - The Recurrent Temporal Restricted Boltzmann Machine
I. Sutskever, G. Hinton, G. Taylor - Tighter Bounds for Structured Estimation
O. Chapelle, C. Do, Q. Le, A. Smola, C. Teo - Tracking Changing Stimuli in Continuous Attractor Neural Networks
C. Fung, K. Wong, S. Wu - Transfer Learning by Distribution Matching for Targeted Advertising
S. Bickel, C. Sawade, T. Scheffer - Translated Learning
W. Dai, Y. Chen, G. Xue, Q. Yang, Y. Yu - Understanding Brain Connectivity Patterns during Motor Imagery for Brain-Computer Interfacing
M. Grosse-Wentrup - Unifying the Sensory and Motor Components of Sensorimotor Adaptation
A. Haith, C. Jackson, R. Miall, S. Vijayakumar - Unlabeled data: Now it helps, now it doesn't
A. Singh, R. Nowak, X. Zhu - Unsupervised Bayesian Parameter Estimation for Probabilistic Grammars
S. Cohen, K. Gimpel, N. Smith - Unsupervised Learning of Visual Sense Models for Polysemous Words
K. Saenko, T. Darrell - Using Bayesian Dynamical Systems for Motion Template Libraries
S. Chiappa, J. Kober, J. Peters - Using matrices to model symbolic relationship
I. Sutskever, G. Hinton - Variational Mixture of Gaussian Process Experts
C. Yuan, C. Neubauer - Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learning
a. rahimi, B. Recht
