Accepted Papers
- (RF)^2 -- Random Forest Random Field
N. Payet, S. Todorovic - A Bayesian Approach to Concept Drift
S. Bach, M. Maloof - A Bayesian Framework for Figure-Ground Interpretation
V. Froyen, J. Feldman, M. Singh - A biologically plausible network for the computation of orientation dominance
K. Muralidharan, N. Vasconcelos - Accounting for network effects in neuronal responses using L1 regularized point process models
R. Kelly, M. Smith, K. Rob, T. Lee - A Computational Decision Theory for Interactive Assistants
A. Fern, P. Tadepalli - Active Estimation of F-Measures
C. Sawade, N. Landwehr, T. Scheffer - Active Instance Sampling via Matrix Partition
Y. Guo - Active Learning Applied to Patient-Adaptive Heartbeat Classification
J. Wiens, J. Guttag - Active Learning by Querying Informative and Representative Examples
S. Huang, R. Jin, Z. Zhou - Adaptive Multi-Task Lasso: with Application to eQTL Detection
S. Lee, J. Zhu, E. Xing - A Dirty Model for Multi-task Learning
A. Jalali, P. Ravikumar, S. Sanghavi, C. Ruan - A Discriminative Latent Model of Image Region and Object Tag Correspondence
Y. Wang, G. Mori - A Family of Penalty Functions for Structured Sparsity
C. Micchelli, J. Morales, M. Pontil - Agnostic Active Learning Without Constraints
A. Beygelzimer, D. Hsu, J. Langford, T. Zhang - A Log-Domain Implementation of the Diffusion Network in Very Large Scale Integration
Y. Wu, S. Lin, H. Chen - An Alternative to Low-level-Sychrony-Based Methods for Speech Detection
P. Ruvolo, j. movellan - An analysis on negative curvature induced by singularity in multi-layer neural-network learning
E. Mizutani, S. Dreyfus - An Approximate Inference Approach to Temporal Optimization in Optimal Control
K. Rawlik, M. Toussaint, S. Vijayakumar - A New Probabilistic Model for Rank Aggregation
T. Qin, X. Geng, T. Liu - An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
M. Hein, T. Bühler - A novel family of non-parametric cumulative based divergences for point processes
S. Seth, I. Park, A. Brockmeier, M. Semework, J. Choi, J. Francis, J. Principe - A Novel Kernel for Learning a Neuron Model from Spike Train Data
N. Fisher, A. Banerjee - A POMDP Extension with Belief-dependent Rewards
M. Araya, O. Buffet, V. Thomas, F. Charpillet - Approximate Inference by Compilation to Arithmetic Circuits
D. Lowd, P. Domingos - Approximate inference in continuous time Gaussian-Jump processes
M. Opper, A. Ruttor, G. Sanguinetti - A Primal-Dual Algorithm for Group Sparse Regularization with Overlapping Groups
S. Mosci, S. Villa, A. Verri, L. Rosasco - A Primal-Dual Message-Passing Algorithm for Approximated Large Scale Structured Prediction
T. Hazan, R. Urtasun - A rational decision making framework for inhibitory control
P. Shenoy, R. Rao, A. Yu - A Reduction from Apprenticeship Learning to Classification
U. Syed, R. Schapire - A Theory of Multiclass Boosting
I. Mukherjee, R. Schapire - Attractor Dynamics with Synaptic Depression
C. Fung, K. Wong, H. Wang, S. Wu - A unified model of short-range and long-range motion perception
S. Wu, X. He, H. Lu, A. Yuille - Auto-Regressive HMM Inference with Incomplete Data for Short-Horizon Wind Forecasting
C. Barber, J. Bockhorst, P. Roebber - A VLSI Implementation of the Adaptive Exponential Integrate-and-Fire Neuron Model
S. Millner, A. Grübl, K. Meier, J. Schemmel, M. Schwartz - Avoiding False Positive in Multi-Instance Learning
Y. Han, Q. Tao, J. Wang - b-Bit Minwise Hashing for Estimating Three-Way Similarities
P. Li, A. König, W. Gui - Basis Construction from Power Series Expansions of Value Functions
S. Mahadevan, B. LIU - Batch Bayesian Optimization via Simulation Matching
J. Azimi, A. Fern, X. Fern - Bayesian Action-Graph Games
A. Jiang, K. Leyton-Brown - Beyond Actions: Discriminative Models for Contextual Group Activities
T. Lan, Y. Wang, W. Yang, G. Mori - Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference
A. Lozano, V. Sindhwani - Boosting Classifier Cascades
M. Saberian, N. Vasconcelos - Bootstrapping Apprenticeship Learning
A. Boularias, B. Chaib-draa - Brain covariance selection: better individual functional connectivity models using population prior
G. Varoquaux, A. Gramfort, J. Poline, B. Thirion - Categories and Functional Units: An Infinite Hierarchical Model for Brain Activations
D. Lashkari, R. Sridharan, P. Golland - Causal discovery in multiple models from different experiments
T. Claassen, T. Heskes - Co-regularization Based Semi-supervised Domain Adaptation
H. Daume III, A. Kumar, A. Saha - Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm
R. Salakhutdinov, N. Srebro - Computing Marginal Distributions over Continuous Markov Networks for Statistical Relational Learning
M. Broecheler, L. Getoor - Constructing Skill Trees for Reinforcement Learning Agents from Demonstration Trajectories
G. Konidaris, S. Kuindersma, A. Barto, R. Grupen - Construction of Dependent Dirichlet Processes based on Poisson Processes
D. Lin, E. Grimson, J. Fisher - Convex Multiple-Instance Learning by Estimating Likelihood Ratio
F. Li, C. Sminchisescu - Copula Bayesian Networks
G. Elidan - Copula Processes
A. Wilson, Z. Ghahramani - Cross Species Expression Analysis using a Dirichlet Process Mixture Model with Latent Matchings
H. Le, Z. Bar-Joseph - CUR from a Sparse Optimization Viewpoint
J. Bien, Y. Xu, M. Mahoney - Deciphering subsampled data: adaptive compressive sampling as a principle of brain communication
G. Isely, C. Hillar, F. Sommer - Decoding Ipsilateral Finger Movements from ECoG Signals in Humans
Y. Liu, M. Sharma, C. Gaona, J. Breshears, j. Roland, z. Freudenburg, K. Weinberger, E. Leuthardt - Decomposing Isotonic Regression for Efficiently Solving Large Problems
R. Luss, S. Rosset, M. Shahar - Deep Coding Network
Y. Lin, T. Zhang, S. Zhu, K. Yu - Deterministic Single-Pass Algorithm for LDA
I. Sato, K. Kurihara, H. Nakagawa - Direct Loss Minimization for Structured Prediction
D. McAllester, T. Hazan, J. Keshet - Discriminative Clustering by Regularized Information Maximization
R. Gomes, A. Krause, P. Perona - Distributed Dual Averaging In Networks
J. Duchi, A. Agarwal, M. Wainwright - Distributionally Robust Markov Decision Processes
H. Xu, S. Mannor - Divisive Normalization: Justification and Effectiveness as Efficient Coding Transform
S. Lyu - Double Q-learning
H. van Hasselt - Dynamic Infinite Relational Model for Time-varying Relational Data Analysis
K. Ishiguro, T. Iwata, N. Ueda, J. Tenenbaum - Effects of Synaptic Weight Diffusion on Learning in Decision Making Networks
K. Katahira, K. Okanoya, M. Okada - Efficient algorithms for learning kernels from multiple similarity matrices with general convex loss functions
A. Kundu, V. Tankasali, C. Bhattacharyya, A. Ben-Tal - Efficient and Robust Feature Selection via Joint ℓ2,1-Norms Minimization
F. Nie, H. Huang, X. Cai, C. Ding - Efficient Minimization of Decomposable Submodular Functions
P. Stobbe, A. Krause - Efficient Optimization for Discriminative Latent Class Models
A. Joulin, F. Bach, J. Ponce - Efficient Relational Learning with Hidden Variable Detection
N. Lao, J. Zhu, L. Xinwang, Y. Liu, W. Cohen - Empirical Bernstein Inequalities for U-Statistics
T. Peel, S. Anthoine, L. Ralaivola - Empirical Risk Minimization with Approximations of Probabilistic Grammars
S. Cohen, N. Smith - Energy Disaggregation via Discriminative Sparse Coding
J. Kolter, S. Batra, A. Ng - Epitome driven 3-D Diffusion Tensor image segmentation: on extracting specific structures
K. Motwani, N. Adluru, C. Hinrichs, a. Alexander, V. Singh - Error Propagation for Approximate Policy and Value Iteration
A. Farahmand, R. Munos, C. Szepesvari - Estimating Spatial Layout of Rooms using Volumetric Reasoning about Objects and Surfaces
D. Lee, A. Gupta, M. Hebert, T. Kanade - Estimation of Renyi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs
D. Pal, B. Poczos, C. Szepesvari - Evaluating neuronal codes for inference using Fisher information
R. Haefner, M. Bethge - Evaluation of Rarity of Fingerprints in Forensics
C. Su, S. Srihari - Evidence-Specific Structures for Rich Tractable CRFs
A. Chechetka, C. Guestrin - Exact inference and learning for cumulative distribution functions on loopy graphs
J. Huang, N. Jojic, C. Meek - Exact learning curves for Gaussian process regression on large random graphs
M. Urry, P. Sollich - Exploiting weakly-labeled Web images to improve object classification: a domain adaptation approach
A. Bergamo, L. Torresani - Extended Bayesian Information Criteria for Gaussian Graphical Models
R. Foygel, M. Drton - Extensions of Generalized Binary Search to Group Identification and Exponential Costs
G. Bellala, S. Bhavnani, C. Scott - Factorized Latent Spaces with Structured Sparsity
Y. Jia, M. Salzmann, T. Darrell - Fast detection of multiple change-points shared by many signals using group LARS
J. Vert, K. Bleakley - Fast global convergence rates of gradient methods for high-dimensional statistical recovery
A. Agarwal, S. Negahban, M. Wainwright - Fast Large-scale Mixture Modeling with Component-specific Data Partitions
B. Thiesson, C. Wang - Feature Construction for Inverse Reinforcement Learning
S. Levine, Z. Popovic, V. Koltun - Feature Set Embedding for Incomplete Data
D. Grangier, I. Melvin - Feature Transitions with Saccadic Search: Size, Color, and Orientation Are Not Alike
S. Yu - Fractionally Predictive Spiking Neurons
S. Bohte, J. Rombouts - Functional form of motion priors in human motion perception
H. Lu, T. Lin, A. Lee, L. Vese, A. Yuille - Functional Geometry Alignment and Localization of Brain Areas
G. Langs, Y. Tie, L. Rigolo, A. Golby, P. Golland - Gated Softmax Classification
R. Memisevic, C. Zach, G. Hinton, M. Pollefeys - Gaussian Process Preference Elicitation
E. Bonilla, S. Guo, S. Sanner - Gaussian sampling by local perturbations
G. Papandreou, A. Yuille - Generalized roof duality and bisubmodular functions
V. Kolmogorov - Generating more realistic images using gated MRF's
M. Ranzato, V. Mnih, G. Hinton - Generative Local Metric Learning for Nearest Neighbor Classification
Y. Noh, B. Zhang, D. Lee - Getting lost in space: Large sample analysis of the resistance distance
U. von Luxburg, A. Radl, M. Hein - Global Analytic Solution for Variational Bayesian Matrix Factorization
S. Nakajima, M. Sugiyama, R. Tomioka - Global seismic monitoring as probabilistic inference
N. Arora, S. Russell, P. Kidwell, E. Sudderth - Graph-Valued Regression
H. Liu, X. Chen, J. Lafferty, L. Wasserman - Group Sparse Coding with a Laplacian Scale Mixture Prior
P. Garrigues, B. Olshausen - Guaranteed Rank Minimization via Singular Value Projection
P. Jain, R. Meka, I. Dhillon - Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: a Deep Boltzmann Machine Model
D. Reichert, P. Series, A. Storkey - Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning
P. Jain, S. Vijayanarasimhan, K. Grauman - Heavy-Tailed Process Priors for Selective Shrinkage
F. Wauthier, M. Jordan - Humans Learn Using Manifolds, Reluctantly
B. Gibson, X. Zhu, T. Rogers, C. Kalish, J. Harrison - Identifying Dendritic Processing
A. Lazar, Y. Slutskiy - Identifying graph-structured activation patterns in networks
J. Sharpnack, A. Singh - Identifying Patients at Risk of Major Adverse Cardiovascular Events Using Symbolic Mismatch
Z. Syed, J. Guttag - Implicit Differentiation by Perturbation
J. Domke - Implicit encoding of prior probabilities in optimal neural populations
D. Ganguli, E. Simoncelli - Implicitly Constrained Gaussian Process Regression for Monocular Non-Rigid Pose Estimation
M. Salzmann, R. Urtasun - Improvements to the Sequence Memoizer
J. Gasthaus, Y. Teh - Improving Human Judgments by Decontaminating Sequential Dependencies
M. Mozer, H. Pashler, M. Wilder, R. Lindsey, M. Jones, M. Jones - Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices
Y. Sun, F. Gomez, J. Schmidhuber - Individualized ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles
K. Li, L. Guo, C. Faraco, D. Zhu, F. Deng, T. Zhang, X. Jiang, D. Zhang, H. Chen, X. Hu, S. Miller, t. Liu - Inductive Regularized Learning of Kernel Functions
P. Jain, B. Kulis, I. Dhillon - Inference and communication in the game of Password
Y. Xu, C. Kemp - Inference with Multivariate Heavy-Tails in Linear Models
D. Bickson, C. Guestrin - Inferring Stimulus Selectivity from the Spatial Structure of Neural Network Dynamics
K. Rajan, L. Abbott, H. Sompolinsky - Infinite Relational Modeling of Functional Connectivity in Resting State fMRI
M. Mørup, K. Madsen, A. Dogonowski, h. Siebner, L. Hansen - Inter-time segment information sharing for non-homogeneous dynamic Bayesian networks
D. Husmeier, F. Dondelinger, S. Lebre - Interval Estimation for Reinforcement-Learning Algorithms in Continuous-State Domains
M. White, A. White - Joint Analysis of Time-Evolving Binary Matrices and Associated Documents
E. Wang, D. Liu, J. Silva, D. Dunson, L. Carin - Joint Cascade Optimization Using A Product Of Boosted Classifiers
L. Lefakis, F. Fleuret - Kernel Descriptors for Visual Recognition
L. Bo, X. Ren, D. Fox - Label Embedding Trees for Large Multi-Class Tasks
S. Bengio, J. Weston, D. Grangier - Large-Scale Matrix Factorization with Missing Data under Additional Constraints
K. Mitra, S. Sheorey, R. Chellappa - Large Margin Learning of Upstream Scene Understanding Models
J. Zhu, L. Li, F. Li, E. Xing - Large Margin Multi-Task Metric Learning
S. Parameswaran, K. Weinberger - Latent Variable Models for Predicting File Dependencies in Large-Scale Software Development
D. Hu, L. van der Maaten, Y. Cho, L. Saul, S. Lerner - Layer-wise analysis of deep networks with Gaussian kernels
G. Montavon, M. Braun, K. Muller - Layered image motion with explicit occlusions, temporal consistency, and depth ordering
D. Sun, E. Sudderth, M. Black - Learning Bounds for Importance Weighting
C. Cortes, Y. Mansour, M. Mohri - Learning concept graphs from text with stick-breaking priors
A. Chambers, P. Smyth, M. Steyvers - Learning Convolutional Feature Hierarchies for Visual Recognition
k. kavukcuoglu, P. Sermanet, Y. Boureau, K. Gregor, M. Mathieu, Y. LeCun - Learning Efficient Markov Networks
V. Gogate, W. Webb, P. Domingos - Learning from Candidate Labeling Sets
L. Jie, F. Orabona - Learning from Logged Implicit Exploration Data
A. Strehl, J. Langford, L. Li, S. Kakade - Learning invariant features using the Transformed Indian Buffet Process
J. Austerweil, T. Griffiths - Learning Kernels with Radiuses of Minimum Enclosing Balls
K. Gai, G. Chen, C. Zhang - Learning Multiple Tasks using Manifold Regularization
A. Agarwal, H. Daume III, S. Gerber - Learning Multiple Tasks with a Sparse Matrix-Normal Penalty
Y. Zhang, J. Schneider - Learning Networks of Stochastic Differential Equations
J. Ayres Pereira, M. Ibrahimi, A. Montanari - Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors
A. Chiuso, G. Pillonetto - Learning the context of a category
D. Navarro - Learning to combine foveal glimpses with a third-order Boltzmann machine
H. Larochelle, G. Hinton - Learning To Count Objects in Images
V. Lempitsky, A. Zisserman - Learning to localise sounds with spiking neural networks
D. Goodman, R. Brette - Learning via Gaussian Herding
K. Crammer, D. Lee - Lifted Inference Seen from the Other Side : The Tractable Features
A. Jha, V. Gogate, A. Meliou, D. Suciu - Linear Complementarity for Regularized Policy Evaluation and Improvement
J. Johns, C. Painter-Wakefield, R. Parr - Linear readout from a neural population with partial correlation data
A. Wohrer, R. Romo, C. Machens - Link Discovery using Graph Feature Tracking
E. Richard, N. Baskiotis, T. Evgeniou, N. Vayatis - Lower Bounds on Rate of Convergence of Cutting Plane Methods
X. Zhang, A. Saha, S. Vishwanathan - LSTD with Random Projections
M. Ghavamzadeh, A. Lazaric, O. Maillard, R. Munos - MAP Estimation for Graphical Models by Likelihood Maximization
A. Kumar, S. Zilberstein - MAP estimation in Binary MRFs via Bipartite Multi-cuts
S. Jakkam Reddi, S. Sarawagi, S. Vishwanathan - Minimum Average Cost Clustering
K. Nagano, Y. Kawahara, S. Iwata - Mixture of time-warped trajectory models for movement decoding
E. Corbett, E. Perreault, K. Koerding - Monte-Carlo Planning in Large POMDPs
D. Silver, J. Veness - Moreau-Yosida Regularization for Grouped Tree Structure Learning
J. Liu, J. Ye - More data means less inference: A pseudo-max approach to structured learning
D. Sontag, O. Meshi, T. Jaakkola, A. Globerson - Movement extraction by detecting dynamics switches and repetitions
S. Chiappa, J. Peters - Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition
S. Bucak, R. Jin, A. Jain - Multi-Stage Dantzig Selector
J. Liu, P. Wonka, J. Ye - Multi-View Active Learning in the Non-Realizable Case
W. Wang, Z. Zhou - Multiparty Differential Privacy via Aggregation of Locally Trained Classifiers
M. Pathak, S. Rane, B. Raj - Multiple Kernel Learning and the SMO Algorithm
S. Vishwanathan, Z. sun, N. Ampornpunt, M. Varma - Multitask Learning without Label Correspondences
N. Quadrianto, A. Smola, T. Caetano, S. Vishwanathan, J. Petterson - Multivariate Dyadic Regression Trees for Sparse Learning Problems
H. Liu, X. Chen - Natural Policy Gradient Methods with Parameter-based Exploration for Control Tasks
A. Miyamae, Y. Nagata, I. Ono, S. Kobayashi - Near-Optimal Bayesian Active Learning with Noisy Observations
D. Golovin, A. Krause, D. Ray - Network Flow Algorithms for Structured Sparsity
J. Mairal, R. Jenatton, G. Obozinski, F. Bach - New Adaptive Algorithms for Online Classification
F. Orabona, K. Crammer - Non-Stochastic Bandit Slate Problems
S. Kale, L. Reyzin, R. Schapire - Nonparametric Bayesian Policy Priors for Reinforcement Learning
F. Doshi-Velez, D. Wingate, N. Roy, J. Tenenbaum - Nonparametric Density Estimation for Stochastic Optimization with an Observable State Variable
L. Hannah, W. Powell, D. Blei - Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification
L. Li, H. Su, E. Xing, F. Li - Occlusion Detection and Motion Estimation with Convex Optimization
A. Ayvaci, M. Raptis, S. Soatto - On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient
J. Tang, P. Abbeel - On Herding and the Perceptron Cycling Theorem
A. Gelfand, Y. Chen, L. van der Maaten, M. Welling - Online Classification with Specificity Constraints
A. Bernstein, S. Mannor, N. Shimkin - Online Learning: Random Averages, Combinatorial Parameters, and Learnability
A. Rakhlin, K. Sridharan, A. Tewari - Online Learning for Latent Dirichlet Allocation
M. Hoffman, D. Blei, F. Bach - Online Learning in The Manifold of Low-Rank Matrices
U. Shalit, D. Weinshall, G. Chechik - Online Markov Decision Processes under Bandit Feedback
G. Neu, A. György, C. Szepesvari, A. Antos - On the Convexity of Latent Social Network Inference
S. Myers, J. Leskovec - On the Theory of Learnining with Privileged Information
D. Pechyony, V. Vapnik - Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets
P. Viappiani, C. Boutilier - Optimal learning rates for Kernel Conjugate Gradient regression
G. Blanchard, N. Krämer - Optimal Web-Scale Tiering as a Flow Problem
G. Leung, N. Quadrianto, A. Smola, K. Tsioutsiouliklis - Over-complete representations on recurrent neural networks can support persistent percepts
S. Druckmann, D. Chklovskii - PAC-Bayesian Model Selection for Reinforcement Learning
M. Milani Fard, J. Pineau - Parallelized Stochastic Gradient Descent
M. Zinkevich, M. Weimer, A. Smola, L. Li - Parametric Bandits: The Generalized Linear Case
S. Filippi, O. Cappe, A. Garivier, C. Szepesvari - Penalized Principal Component Regression on Graphs for Analysis of Subnetworks
A. Shojaie, G. Michailidis - Permutation Complexity Bound on Out-Sample Error
M. Magdon-Ismail - Phoneme Recognition with Large Hierarchical Reservoirs
F. Triefenbach, A. Jalalvand, B. Schrauwen, J. Martens - Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine
G. Dahl, M. Ranzato, A. Mohamed, G. Hinton - Policy gradients in linearly-solvable MDPs
E. Todorov - Pose-Sensitive Embedding by Nonlinear NCA Regression
G. Taylor, R. Fergus, G. Williams, I. Spiro, C. Bregler - Practical Large-Scale Optimization for Max-norm Regularization
J. Lee, B. Recht, R. Salakhutdinov, N. Srebro, J. Tropp - Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression
L. Huang, J. Jia, B. Yu, B. Chun, P. Maniatis, M. Naik - Predictive State Temporal Difference Learning
B. Boots, G. Gordon - Predictive Subspace Learning for Multi-view Data: a Large Margin Approach
N. Chen, J. Zhu, E. Xing - Probabilistic Belief Revision with Structural Constraints
P. Jones, V. Saligrama, S. Mitter - Probabilistic Deterministic Infinite Automata
D. Pfau, N. Bartlett, F. Wood - Probabilistic Inference and Differential Privacy
O. Williams, F. McSherry - Probabilistic latent variable models for distinguishing between cause and effect
J. Mooij, O. Stegle, D. Janzing, K. Zhang, B. Schölkopf - Probabilistic Multi-Task Feature Selection
Y. Zhang, D. Yeung, Q. Xu - Random Conic Pursuit for Semidefinite Programming
A. Kleiner, a. rahimi, M. Jordan - Random Projections for $k$-means Clustering
C. Boutsidis, A. Zouzias, P. Drineas - Random Projection Trees Revisited
A. Dhesi, P. Kar - Random Walk Approach to Regret Minimization
H. Narayanan, A. Rakhlin - Rates of convergence for the cluster tree
K. Chaudhuri, S. Dasgupta - Regularized estimation of image statistics by Score Matching
D. Kingma, Y. LeCun - Relaxed Clipping: A Global Training Method for Robust Regression and Classification
Y. Yu, M. Yang, L. Xu, M. White, D. Schuurmans - Repeated Games against Budgeted Adversaries
J. Abernethy, M. Warmuth - Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models
F. Gerhard, W. Gerstner - Reverse Multi-Label Learning
J. Petterson, T. Caetano - Reward Design via Online Gradient Ascent
J. Sorg, S. Singh, R. Lewis - Robust Clustering as Ensembles of Affinity Relations
H. Liu, L. Latecki, s. yan - Robust PCA via Outlier Pursuit
H. Xu, C. Caramanis, S. Sanghavi - Sample Complexity of Testing the Manifold Hypothesis
H. Narayanan, S. Mitter - Scrambled Objects for Least-Squares Regression
O. Maillard, R. Munos - Segmentation as Maximum-Weight Independent Set
w. brendel, S. Todorovic - Self-Paced Learning for Latent Variable Models
M. Kumar, B. Packer, D. Koller - Semi-Supervised Learning with Adversarially Missing Label Information
U. Syed, B. Taskar - Shadow Dirichlet for Restricted Probability Modeling
B. Frigyik, M. Gupta, Y. Chen - Short-term memory in neuronal networks through dynamical compressed sensing
S. Ganguli, H. Sompolinsky - Sidestepping Intractable Inference with Structured Ensemble Cascades
D. Weiss, B. Sapp, B. Taskar - Simultaneous Object Detection and Ranking with Weak Supervision
M. Blaschko, A. Vedaldi, A. Zisserman - Size Matters: Metric Visual Search Constraints from Monocular Metadata
M. Fritz, K. Saenko, T. Darrell - Slice sampling covariance hyperparameters of latent Gaussian models
I. Murray, R. Adams - Smoothness, Low Noise and Fast Rates
N. Srebro, K. Sridharan, A. Tewari - Sodium entry efficiency during action potentials: A novel single-parameter family of Hodgkin-Huxley models
A. Singh, R. Jolivet, P. Magistretti, B. Weber - Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake
S. Harmeling, M. Hirsch, B. Schölkopf - Sparse Coding for Learning Interpretable Spatio-Temporal Primitives
T. Kim, G. Shakhnarovich, R. Urtasun - Sparse Instrumental Variables (SPIV) for Genome-Wide Studies
F. Agakov, P. McKeigue, J. Krohn, A. Storkey - Sparse Inverse Covariance Selection via Alternating Linearization Methods
K. Scheinberg, S. Ma, D. Goldfarb - Spatial and anatomical regularization of SVM for brain image analysis
R. Cuingnet, M. Chupin, H. Benali, O. Colliot - Spectral Regularization for Support Estimation
E. De Vito, L. Rosasco, A. Toigo - Sphere Embedding: An Application to Part-of-Speech Induction
Y. Maron, M. Lamar, E. Bienenstock - SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex system
S. Chevallier, H. Paugam-Moisy, M. Sebag - Spike timing-dependent plasticity as dynamic filter
J. Schmiedt, C. Albers, K. Pawelzik - Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models
H. Liu, K. Roeder, L. Wasserman - Static Analysis of Binary Executables Using Structural SVMs
N. Karampatziakis - Structural epitome: a way to summarize one’s visual experience
N. Jojic, A. Perina, V. Murino - Structured Determinantal Point Processes
A. Kulesza, B. Taskar - Structured sparsity-inducing norms through submodular functions
F. Bach - Subgraph Detection Using Eigenvector L1 Norms
B. Miller, N. Bliss, P. Wolfe - Sufficient Conditions for Generating Group Level Sparsity in a Robust Minimax Framework
H. Zhou, Q. Cheng - Supervised Clustering
P. Awasthi, R. Bosagh Zadeh - Switched Latent Force Models for Movement Segmentation
M. Alvarez, J. Peters, B. Schölkopf, N. Lawrence - Switching state space model for simultaneously estimating state transitions and nonstationary firing rates
K. Takiyama, M. Okada - Synergies in learning words and their referents
M. Johnson, K. Demuth, M. Frank, B. Jones - t-logistic regression
N. Ding, S. Vishwanathan - The LASSO risk: asymptotic results and real world examples
M. Bayati, J. Ayres Pereira, A. Montanari - The Maximal Causes of Natural Scenes are Edge Filters
J. Puertas, J. Bornschein, J. Lucke - The Multidimensional Wisdom of Crowds
P. Welinder, S. Branson, S. Belongie, P. Perona - The Neural Costs of Optimal Control
S. Gershman, R. Wilson - Throttling Poisson Processes
U. Dick, P. Haider, T. Vanck, M. Brückner, T. Scheffer - Tight Sample Complexity of Large-Margin Learning
S. Sabato, N. Srebro, N. Tishby - Tiled convolutional neural networks
Q. Le, J. Ngiam, Z. Chen, D. Chia, P. Koh, A. Ng - Towards Holistic Scene Understanding: Feedback Enabled Cascaded Classification Models
C. Li, A. Kowdle, A. Saxena, T. Chen - Towards Property-Based Classification of Clustering Paradigms
M. Ackerman, S. Ben-David, D. Loker - Trading off Mistakes and Don't-Know Predictions
A. Sayedi, M. Zadimoghaddam, A. Blum - Transduction with Matrix Completion: Three Birds with One Stone
A. Goldberg, X. Zhu, B. Recht, J. Sui, R. Nowak - Tree-Structured Stick Breaking for Hierarchical Data
R. Adams, Z. Ghahramani, M. Jordan - Two-Layer Generalization Analysis for Ranking Using Rademacher Average
W. Chen, T. Liu, Z. Ma - Universal Consistency of Multi-Class Support Vector Classification
T. Glasmachers - Universal Kernels on Non-Standard Input Spaces
A. Christmann, I. Steinwart - Unsupervised Kernel Dimension Reduction
M. Wang, F. Sha, M. Jordan - Using body-anchored priors for identifying actions in single images
L. Karlinsky, M. Dinerstein, S. Ullman - Variable margin losses for classifier design
H. Masnadi-Shirazi, N. Vasconcelos - Variational bounds for mixed-data factor analysis
M. Khan, B. Marlin, G. Bouchard, K. Murphy - Variational Inference over Combinatorial Spaces
A. Bouchard-Côté, M. Jordan - Why are some word orders more common than others? A uniform information density account
L. Maurits, D. Navarro, A. Perfors - Word Features for Latent Dirichlet Allocation
J. Petterson, A. Smola, T. Caetano, W. Buntine, S. Narayanamurthy - Worst-case bounds on the quality of max-product fixed-points
M. Vinyals, J. Cerquides, A. Farinelli, J. Rodríguez-Aguilar - Worst-Case Linear Discriminant Analysis
Y. Zhang, D. Yeung
