Accepted Papers
- 3D Gaze Concurrences from Head-mounted Cameras
H. Park, e. Jain, Y. Sheikh - 3D Object Detection and Viewpoint Estimation with a Deformable 3D Cuboid Model
S. Fidler, S. Dickinson, R. Urtasun - A Bayesian Approach for Policy Learning from Trajectory Preference Queries
A. Wilson, A. Fern, P. Tadepalli - A Better Way to Pre-Train Deep Boltzmann Machines
R. Salakhutdinov, G. Hinton - Accelerated Training for Matrix-norm Regularization: A Boosting Approach
X. Zhang, Y. Yu, D. Schuurmans - Accuracy at the Top
S. Boyd, C. Cortes, M. Mohri, A. Radovanovic - A Convex Formulation for Learning Scale-Free Networks via Submodular Relaxation
A. Defazio, T. Caetano - Action-Model Based Multi-agent Plan Recognition
H. Zhuo, Q. Yang, S. Kambhampati - Active Comparison of Prediction Models
C. Sawade, N. Landwehr, T. Scheffer - Active Learning of Model Evidence Using Bayesian Quadrature
M. Osborne, D. Duvenaud, R. Garnett, C. Rasmussen, S. Roberts, Z. Ghahramani - Active Learning of Multi-Index Function Models
H. Tyagi, V. Cevher - Adaptive Learning of Smoothing Functions: Application to Electricity Load Forecasting
A. Ba, M. Sinn, Y. Goude, P. Pompey - Adaptive Stratified Sampling for Monte-Carlo integration of Differentiable functions
A. Carpentier, R. Munos - A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation
C. Hsieh, I. Dhillon, P. Ravikumar, A. Banerjee - Affine Independent Variational Inference
E. Challis, D. Barber - A Generative Model for Parts-based Object Segmentation
S. Eslami, C. Williams - A Geometric take on Metric Learning
S. Hauberg, O. Freifeld, M. Black - A latent factor model for highly multi-relational data
R. Jenatton, N. Le Roux, A. Bordes, G. Obozinski - A lattice filter model of the visual pathway
K. Gregor, D. Chklovskii - Algorithms for Learning Markov Field Policies
A. Boularias, O. Kroemer, J. Peters - A Linear Time Active Learning Algorithm for Link Classification
N. Cesa-Bianchi, C. Gentile, F. Vitale, G. Zappella - A Marginalized Particle Gaussian Process Regression
Y. Wang, B. Chaib-draa - A mechanistic model of early sensory processing based on subtracting sparse representations
S. Druckmann, T. Hu, D. Chklovskii - Analog readout for optical reservoir computers
A. Smerieri, F. Duport, Y. Paquot, M. Haelterman, S. Massar - Analyzing 3D Objects in Cluttered Images
M. Hejrati, D. Ramanan - Ancestor Sampling for Particle Gibbs
F. Lindsten, M. Jordan, T. Schön - A Neural Autoregressive Topic Model
H. Larochelle, S. Lauly - A new metric on the manifold of kernel matrices with application to matrix geometric means
S. Sra - Angular Quantization based Binary Codes for Fast Similarity Search
Y. Gong, S. Kumar, V. Verma, S. Lazebnik - A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function
P. Ortega, T. Genewein, J. Grau-Moya, D. Balduzzi, D. Braun - A nonparametric variable clustering model
D. Knowles, K. Palla, Z. Ghahramani - A P300 BCI for the Masses: Prior Information Enables Instant Unsupervised Spelling
P. Kindermans, H. Verschore, D. Verstraeten, B. Schrauwen - A Polylog Pivot Steps Simplex Algorithm for Classification
E. Hazan, Z. Karnin - A Polynomial-time Form of Robust Regression
Y. Yu, O. Aslan, D. Schuurmans - Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning
U. Kamilov, S. Rangan, A. Fletcher, M. Unser - Approximating Concavely Parameterized Optimization Problems
J. Giesen, J. Mueller, S. Laue, S. Swiercy - Approximating Equilibria in Sequential Auctions with Incomplete Information and Multi-Unit Demand
A. Greenwald, J. Li, E. Sodomka - A quasi-Newton proximal splitting method
S. Becker, J. Fadili - A Scalable CUR Matrix Decomposition Algorithm: Lower Time Complexity and Tighter Bound
S. Wang, Z. Zhang - A Simple and Practical Algorithm for Differentially Private Data Release
M. Hardt, K. Ligett, F. McSherry - A Spectral Algorithm for Latent Dirichlet Allocation
A. Anandkumar, D. Foster, D. Hsu, S. Kakade, Y. Liu - Assessing Blinding in Clinical Trials
O. Arandjelovic - A Stochastic Gradient Method with an Exponential Convergence
Rate for Finite Training Sets
N. Le Roux, M. Schmidt, F. Bach - A systematic approach to extracting semantic information from functional MRI data
F. Pereira, M. Botvinick - A System for Predicting Action Content On-Line and in Real Time before Action Onset in Humans – an Intracranial Study
U. Maoz, S. Ye, I. Ross, A. Mamelak, C. Koch - Augment-and-Conquer Negative Binomial Processes
M. Zhou, L. Carin - Augmented-SVM: Automatic space partitioning for combining multiple non-linear dynamics
A. Shukla, A. Billard - A Unifying Perspective of Parametric Policy Search Methods for Markov Decision Processes
T. Furmston, D. Barber - Automatic Feature Induction for Stagewise Collaborative Filtering
J. Lee, M. Sun, S. Kim, G. Lebanon - Bandit Algorithms boost Brain Computer Interfaces for motor-task selection of a brain-controlled button
J. Fruitet, A. Carpentier, R. Munos, M. Clerc - Bayesian active learning with localized priors for fast receptive field characterization
M. Park, J. Pillow - Bayesian estimation of discrete entropy with mixtures of stick-breaking priors
E. Archer, J. Pillow, I. Park - Bayesian Hierarchical Reinforcement Learning
F. Cao, S. Ray - Bayesian models for Large-scale Hierarchical Classification
S. Gopal, Y. Yang, B. Bai, A. Niculescu-Mizil - Bayesian n-Choose-k Models for Classification and Ranking
K. Swersky, D. Tarlow, R. Zemel, R. Adams, B. Frey - Bayesian Nonparametric Maximum Margin Matrix Factorization for Collaborative Prediction
M. Xu, J. Zhu, B. Zhang - Bayesian Nonparametric Modeling of Suicide Attempts
F. Ruiz, I. Valera, C. Blanco, F. Perez-Cruz - Bayesian nonparametric models for bipartite graphs
F. Caron - Bayesian nonparametric models for ranked data
F. Caron, Y. Teh - Bayesian Pedigree Analysis using Measure Factorization
B. Kirkpatrick, A. Bouchard-Côté - Bayesian Probabilistic Co-Subspace Addition
L. Shi - Bayesian Warped Gaussian Processes
M. Lázaro-Gredilla - Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence
V. Gabillon, M. Ghavamzadeh, A. Lazaric - Burn-in, bias, and the rationality of anchoring
F. Lieder, T. Griffiths, N. Goodman - Calibrated Elastic Regularization in Matrix Completion
C. Zhang, T. Sun - Cardinality Restricted Boltzmann Machines
K. Swersky, D. Tarlow, I. Sutskever, R. Zemel, R. Salakhutdinov, R. Adams - Causal discovery with scale-mixture model for spatiotemporal variance dependencies
Z. Chen, K. Zhang, L. CHAN - Classification Calibration Dimension for General Multiclass Losses
H. Guruprasad, S. Agarwal - Clustering Aggregation as Maximum-Weight Independent Set
N. Li, L. Latecki - Clustering by Nonnegative Matrix Factorization Using Graph Random Walk
Z. Yang, T. Hao, O. Dikmen, X. Chen, E. Oja - Clustering Sparse Graphs
Y. Chen, S. Sanghavi, H. Xu - Co-Regularized Hashing for Multimodal Data
Y. Zhen, D. Yeung - Cocktail Party Processing via Structured Prediction
Y. Wang, D. Wang - Coding efficiency and detectability of rate fluctuations with non-Poisson neuronal firing
S. Koyama - Collaborative Gaussian Processes for Preference Learning
N. Houlsby, J. Hernández-Lobato, F. Huszar, Z. Ghahramani - Collaborative Ranking With 17 Parameters
M. Volkovs, R. Zemel - Communication-Efficient Algorithms for Statistical Optimization
Y. Zhang, J. Duchi, M. Wainwright - Communication/Computation Tradeoffs in Consensus-Based Distributed Optimization
K. Tsianos, S. Lawlor, M. Rabbat - Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models
J. Beck, K. Heller, A. Pouget - Compressive neural representation of sparse, high-dimensional probabilities
X. Pitkow - Compressive Sensing MRI with Wavelet Tree Sparsity
C. Chen, J. Huang - Confusion-Based Online Learning and a Passive-Aggressive Scheme
L. Ralaivola - Context-Sensitive Decision Forests for Object Detection
P. Kontschieder, S. Bulò, A. Criminisi, P. Kohli, M. Pelillo, H. Bischof - Continuous Relaxations for Discrete Hamiltonian Monte Carlo
Z. Ghahramani, Y. Zhang, C. Sutton, A. Storkey - Controlled Recognition Bounds for Visual Learning and Exploration
V. Karasev, A. Chiuso, S. Soatto - Convergence and Energy Landscape for Cheeger Cut Clustering
X. Bresson, T. Laurent, D. Uminsky, J. von Brecht - Convergence Rate Analysis of MAP Coordinate Minimization Algorithms
O. Meshi, T. Jaakkola, A. Globerson - Convex Multi-view Subspace Learning
M. White, Y. Yu, X. Zhang, D. Schuurmans - Cost-Sensitive Exploration in Bayesian Reinforcement Learning
D. Kim, K. Kim, P. Poupart - Coupling Nonparametric Mixtures via Latent Dirichlet Processes
D. Lin, J. Fisher - CPRL -- An Extension of Compressive Sensing to the Phase Retrieval Problem
H. Ohlsson, A. Yang, R. Dong, S. Sastry - Deep Learning of invariant features via tracked video sequences
W. Zou, A. Ng, S. Zhu, K. Yu - Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images
D. Ciresan, A. Giusti, l. Gambardella, J. Schmidhuber - Deep Representations and Codes for Image Auto-Annotation
R. Kiros, C. Szepesvari - Deep Spatio-Temporal Architectures and Learning for Protein Structure Prediction
P. Lena, P. Baldi, K. Nagata - Delay Compensation with Dynamical Synapses
C. Fung, K. Wong, S. Wu - Density-Difference Estimation
M. Sugiyama, T. Kanamori, T. Suzuki, M. Plessis, S. Liu, I. Takeuchi - Density Propagation and Improved Bounds on the Partition Function
S. Ermon, C. Gomes, A. Sabharwal, B. Selman - Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification
Y. Noh, F. Park, D. Lee - Dimensionality Dependent PAC-Bayes Margin Bound
C. Jin, L. Wang - Dip-means: an incremental clustering method for estimating the number of clusters
A. Kalogeratos, A. Likas - Discriminative Learning of Sum-Product Networks
R. Gens, P. Domingos - Discriminatively Trained Sparse Code Gradients for Contour Detection
X. Ren, L. Bo - Distributed Non-Stochastic Experts
V. Kanade, Z. Liu, B. Radunovic - Distributed Probabilistic Learning for Camera Networks with Missing Data
S. Yoon, V. Pavlovic - Dual-Space Analysis of the Sparse Linear Model
D. Wipf - Dynamical And-Or Graph Learning for Object Shape Modeling and Detection
x. wang, L. Lin - Dynamic Pruning of Factor Graphs for Maximum Marginal Prediction
C. Lampert - Effective Split-Merge Monte Carlo Methods for Nonparametric Models of Sequential Data
M. Hughes, E. Fox, E. Sudderth - Efficient and direct estimation of a neural subunit model for sensory coding
B. Vintch, A. Zaharia, J. Movshon, E. Simoncelli - Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search
A. Guez, D. Silver, P. Dayan - Efficient coding connects prior and likelihood function in perceptual Bayesian inference
X. Wei, A. Stocker - Efficient high dimensional maximum entropy modeling via symmetric partition functions
P. Vernaza, D. Bagnell - Efficient Monte Carlo Counterfactual Regret Minimization in Games with Many Player Actions
R. Gibson, M. Lanctot, N. Burch, D. Szafron - Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems
M. Ibrahimi, A. Javanmard, B. Van Roy - Efficient Sampling for Bipartite Matching Problems
M. Volkovs, R. Zemel - Efficient Spike-Coding with Multiplicative Adaptation in a Spike Response Model
S. Bohte - Emergence of Object-Selective Features in Unsupervised Feature Learning
A. Coates, A. Karpathy, A. Ng - Ensemble weighted kernel estimators for multivariate entropy estimation
K. Sricharan, A. Hero - Entangled Monte Carlo
S. Jun, L. Wang, A. Bouchard-Côté - Entropy Estimations Using Correlated Symmetric Stable Random Projections
P. Li, C. Zhang - Exact and Stable Recovery of Sequences of Signals with Sparse Increments via Differential ℓ1-Minimization
D. Ba, B. Babadi, P. Purdon, E. Brown - Expectation Propagation in Gaussian Process Dynamical Systems
M. Deisenroth, S. Mohamed - Exploration in Model-based Reinforcement Learning by Empirically Estimating Learning Progress
M. Lopes, T. Lang, M. Toussaint, P. Oudeyer - Exponential Concentration for Mutual Information Estimation with Application to Forests
H. Liu, J. Lafferty, L. Wasserman - Factorial LDA: Sparse Multi-Dimensional Text Models
M. Paul, M. Dredze - Factoring nonnegative matrices with linear programs
B. Recht, C. Re, J. Tropp, V. Bittorf - Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression
M. Khan, S. Mohamed, K. Murphy - FastEx: Fast Clustering with Exponential Families
A. Ahmed, S. Ravi, S. Narayanamurthy, A. Smola - Fast Resampling Weighted v-Statistics
C. Zhou, j. Park, Y. Fu - Fast Variational Inference in the Conjugate Exponential Family
J. Hensman, M. Rattray, N. Lawrence - Feature-aware Label Space Dimension Reduction for Multi-label Classification
Y. Chen, H. Lin - Feature Clustering for Accelerating Parallel Coordinate Descent
C. Scherrer, A. Tewari, M. Halappanavar, D. Haglin - Fiedler Random Fields: A Large-Scale Spectral Approach to Statistical Network Modeling
A. Freno, M. Keller, M. Tommasi - Finding Exemplars from Pairwise Dissimilarities via Simultaneous Sparse Recovery
E. Elhamifar, G. Sapiro, R. Vidal - Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods
J. Duchi, M. Jordan, M. Wainwright, A. Wibisono - Forging The Graphs: A Low Rank and Positive Semidefinite Graph Learning Approach
D. Luo, C. Ding, H. Huang - Forward-Backward Activation Algorithm for Hierarchical Hidden Markov Models
K. Wakabayashi, T. Miura - From Deformations to Parts: Motion-based Segmentation of 3D Objects
S. Ghosh, E. Sudderth, M. Loper, M. Black - Fully Bayesian inference for neural models with negative-binomial spiking
J. Pillow, J. Scott - Fused sparsity and robust estimation for linear models with unknown variance
A. Dalalyan, Y. Chen - Fusion with Diffusion for Robust Visual Tracking
Y. Zhou, X. Bai, W. Liu, L. Latecki - GenDeR: A Generic Diversified Ranking Algorithm
J. He, H. Tong, Q. Mei, B. Szymanski - Generalization Bounds for Domain Adaptation
C. Zhang, J. Ye, L. Zhang - Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins
A. Schwing, T. Hazan, M. Pollefeys, R. Urtasun - Gradient-based kernel method for feature extraction and variable selection
K. Fukumizu, C. Leng - Gradient Weights help Nonparametric Regressors
S. Kpotufe, A. Boularias - Graphical Gaussian Vector for Image Categorization
T. Harada - Graphical Models via Generalized Linear Models
E. Yang, P. Ravikumar, G. Allen, z. Liu - Hamming Distance Metric Learning
M. Norouzi, R. Salakhutdinov, D. Fleet - Hierarchical Optimistic Region Selection driven by Curiosity
O. Maillard - Hierarchical spike coding of sound
y. karklin, C. Ekanadham, E. Simoncelli - High-dimensional Nonparanormal Graph Estimation via Smooth-projected Neighborhood Pursuit
T. Zhao, K. Roeder, H. Liu - High-Order Multi-Task Feature Learning to Identify Longitudinal Phenotypic Markers for Alzheimer Disease Progression Prediction
H. Wang, F. Nie, H. Huang, J. Yan, S. Kim, S. Risacher, A. Saykin, L. Shen - High Dimensional Semiparametric Scale-invariant Principal Component Analysis
F. Han, H. Liu - High Dimensional Transelliptical Graphical Models
H. Liu, F. Han - Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints
S. Habenschuss, J. Bill, B. Nessler - How Prior Probability Influences Decision Making: A Unifying Probabilistic Model
Y. Huang, A. Friesen, T. Hanks, M. Shadlen, R. Rao - How They Vote: Issue-Adjusted Models of Legislative Behavior
S. Gerrish, D. Blei - Human memory search as a random walk in a semantic network
J. Abbott, J. Austerweil, T. Griffiths - Identifiability and Unmixing of Latent Parse Trees
P. Liang, S. Kakade, D. Hsu - Identification of Recurrent Patterns in the Activation of Brain Networks
f. janoos, W. Li, N. Subrahmanya, I. Morocz, W. Wells - Image Denoising and Inpainting with Deep Neural Networks
J. Xie, L. Xu, E. Chen - ImageNet Classification with Deep Convolutional Neural Networks
A. Krizhevsky, I. Sutskever, G. Hinton - Imitation Learning by Coaching
H. He, H. Daume III, J. Eisner - Interpreting prediction markets: a stochastic approach
N. Della Penna, M. Reid, R. Frongillo - Inverse Reinforcement Learning through Structured Classification
E. Klein, M. Geist, B. PIOT, O. Pietquin - Isotropic Hashing
W. Kong, W. Li - Iterative ranking from pair-wise comparisons
S. Negahban, S. Oh, D. Shah - Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation
B. Rolfs, B. Rajaratnam, D. Guillot, A. Maleki, I. Wong - Joint Modeling of a Matrix with Associated Text via Latent Binary Features
X. Zhang, L. Carin - Kernel Hyperalignment
A. Lorbert, P. Ramadge - Kernel Latent SVM for Visual Recognition
W. Yang, Y. Wang, A. Vahdat, G. Mori - Label Ranking with Partial Abstention based on Thresholded Probabilistic Models
W. Cheng, E. Huellermeier, W. Waegeman, V. Welker - Large Scale Distributed Deep Networks
J. Dean, G. Corrado, R. Monga, K. Chen, M. Devin, Q. Le, M. Mao, M. Ranzato, A. Senior, P. Tucker, K. Yang, A. Ng - Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning
M. Der, L. Saul - Latent Graphical Model Selection: Efficient Methods for Locally Tree-like Graphs
A. Anandkumar, R. Valluvan - Learned Prioritization for Trading Off Accuracy and Speed
J. Jiang, A. Teichert, H. Daume III, J. Eisner - Learning about Canonical Views from Internet Image Collections
E. Mezuman, Y. Weiss - Learning as MAP Inference in Discrete Graphical Models
T. Caetano, X. Liu, J. Petterson - Learning curves for multi-task Gaussian process regression
P. Sollich, S. Ashton - Learning from Distributions via Support Measure Machines
K. Muandet, K. Fukumizu, F. Dinuzzo, B. Schölkopf - Learning from the Wisdom of Crowds by Minimax Entropy
D. Zhou, J. Platt, S. Basu, Y. Mao - Learning Halfspaces with the Zero-One Loss: Time-Accuracy Tradeoffs
A. Birnbaum, S. Shalev-Shwartz - Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data
A. Glazer, M. Lindenbaoum, S. Markovitch - Learning Image Descriptors with the Boosting-Trick
T. Trzcinski, M. Christoudias, V. Lepetit, P. Fua - Learning Invariant Representations of Molecules for Atomization Energy Prediction
G. Montavon, K. Hansen, S. Fazli, M. Rupp, F. Biegler, A. Ziehe, A. Tkatchenko, A. von Lilienfeld, K. Müller - Learning Label Trees for Probabilistic Modelling of Implicit Feedback
A. Mnih, Y. Teh - Learning Manifolds with K-Means and K-Flats
G. Canas, T. Poggio, L. Rosasco - Learning Mixtures of Tree Graphical Models
A. Anandkumar, D. Hsu, F. Huang, S. Kakade - Learning Multiple Tasks using Shared Hypotheses
K. Crammer, Y. Mansour - Learning Networks of Heterogeneous Influence
N. DU, L. Song, A. Smola, M. Yuan - Learning optimal spike-based representations
R. Bourdoukan, D. Barrett, C. Machens, S. Deneve - Learning Partially Observable Models Using Temporally Abstract Decision Trees
E. Talvitie - Learning Probability Measures with respect to Optimal Transport Metrics
G. Canas, L. Rosasco - Learning the Architecture of Sum-Product Networks Using Clustering on Variables
A. Dennis, D. Ventura - Learning the Dependency Structure of Latent Factors
Y. He, Y. Qi, k. kavukcuoglu, H. Park - Learning to Align from Scratch
G. Huang, M. Mattar, H. Lee, E. Learned-Miller - Learning to Discover Social Circles in Ego Networks
J. McAuley, J. Leskovec - Learning visual motion in recurrent neural networks
M. Pachitariu, M. Sahani - Learning with Partially Absorbing Random Walks
X. Wu, Z. Li, S. Chang, J. Wright, A. So - Learning with Recursive Perceptual Representations
O. Vinyals, Y. Jia, L. Deng, T. Darrell - Learning with Target Prior
Z. Wang, S. Lyu, G. Schalk, Q. Ji - Link Prediction in Graphs with Autoregressive Features
E. Richard, S. Gaiffas, N. Vayatis - Localizing 3D cuboids in single-view images
J. Xiao, B. Russell, A. Torralba - Local Supervised Learning through Space Partitioning
J. Wang, V. Saligrama - Locating Changes in Highly Dependent Data with Unknown Number of Change Points
A. Khaleghi, D. Ryabko - LUCID: Locally Uniform Comparison Image Descriptor
A. Ziegler, E. Christiansen, D. Kriegman, S. Belongie - Majorization for CRFs and Latent Likelihoods
T. Jebara, A. Choromanska - Mandatory Leaf Node Prediction in Hierarchical Multilabel Classification
W. Bi, J. Kwok - MAP Inference in Chains using Column Generation
D. Belanger, A. Passos, S. Riedel, A. McCallum - Matrix reconstruction with the local max norm
R. Foygel, N. Srebro, R. Salakhutdinov - Max-Margin Structured Output Regression for Spatio-Temporal Action Localization
D. Tran, J. Yuan - MCMC for continuous-time discrete-state systems
V. Rao, Y. Teh - Meta-Gaussian Information Bottleneck
M. Rey, V. Roth - Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL
N. Mehta, D. Lee, A. Gray - Minimization of Continuous Bethe Approximations: A Positive Variation
J. Pacheco, E. Sudderth - Minimizing Sparse High-Order Energies by Submodular Vertex-Cover
A. Delong, O. Veksler, A. Osokin, Y. Boykov - Minimizing Uncertainty in Pipelines
N. Dalvi, A. Parameswaran, V. Rastogi - Mirror Descent Meets Fixed Share (and feels no regret)
N. Cesa-Bianchi, P. Gaillard, G. Lugosi, G. Stoltz - Mixability in Statistical Learning
T. van Erven, P. Grunwald, M. Reid, R. Williamson - Mixing Properties of Conditional Markov Chains with Unbounded Feature Functions
M. Sinn, B. Chen - Modeling the Forgetting Process using Image Regions
A. Khosla, J. Xiao, A. Torralba, A. Oliva - Modelling Reciprocating Relationships with Hawkes processes
C. Blundell, K. Heller, J. Beck - Monte Carlo Methods for Maximum Margin Supervised Topic Models
Q. Jiang, J. Zhu, M. Sun, E. Xing - Multi-criteria Anomaly Detection using Pareto Depth Analysis
K. Hsiao, K. Xu, J. Calder, A. Hero - Multi-scale Hyper-time Hardware Emulation of Human Motor Nervous System Based on Spiking Neurons using FPGA
C. Niu, S. Nandyala, W. Sohn, T. Sanger - Multi-Stage Multi-Task Feature Learning
P. Gong, J. Ye, C. Zhang - Multi-Task Averaging
S. Feldman, M. Gupta, B. Frigyik - Multi-task Vector Field Learning
B. Lin, S. Yang, C. Zhang, J. Ye, X. He - Multiclass Learning Approaches: A Theoretical Comparison with Implications
A. Daniely, S. Sabato, S. Shalev-Shwartz - Multiclass Learning with Simplex Coding
Y. Mroueh, T. Poggio, L. Rosasco, J. Slotine - Multilabel Classification using Bayesian Compressed Sensing
A. Kapoor, R. Viswanathan, P. Jain - Multimodal Learning with Deep Boltzmann Machines
N. Srivastava, R. Salakhutdinov - Multiple Choice Learning: Learning to Produce Multiple Structured Outputs
A. Guzmán-Rivera, D. Batra, P. Kohli - Multiple Operator-valued Kernel Learning
H. Kadri, A. Rakotomamonjy, F. Bach, p. preux - Multiplicative Forests for Continuous-Time Processes
J. Weiss, S. Natarajan, D. Page - Multiresolution analysis on the symmetric group
R. Kondor, W. Dempsey - Multiresolution Gaussian Processes
E. Fox, D. Dunson - Natural Images, Gaussian Mixtures and Dead Leaves
D. Zoran, Y. Weiss - Near-optimal Differentially Private Principal Components
K. Chaudhuri, A. Sarwate, K. Sinha - Near-Optimal MAP Inference for Determinantal Point Processes
A. Kulesza, J. Gillenwater, B. Taskar - Near Optimal Chernoff Bounds for Markov Decision Processes
T. Moldovan, P. Abbeel - Neurally Plausible Reinforcement Learning of Working Memory Tasks
J. Rombouts, S. Bohte, P. Roelfsema - Neuronal spike generation mechanism as an oversampling, noise-shaping A-to-D converter
D. Chklovskii - Newton-Like Methods for Sparse Inverse Covariance Estimation
P. Olsen, F. Oztoprak, J. Nocedal, S. Rennie - No-Regret Algorithms for Unconstrained Online Convex Optimization
M. Streeter, B. McMahan - Non-linear Metric Learning
D. Kedem, S. Tyree, K. Weinberger, F. Sha, G. Lanckriet - Non-parametric Approximate Dynamic Programming via the Kernel Method
N. Bhat, C. Moallemi, V. Farias - Nonconvex Penalization, Levy Processes and Concave Conjugates
Z. Zhang, B. Tu - Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions
J. Choi, K. Kim - Nonparametric Reduced Rank Regression
R. Foygel, M. Horrell, M. Drton, J. Lafferty - Nonparanormal Belief Propagation (NPBP)
G. Elidan, C. Cario - No voodoo here! Learning discrete graphical models via inverse covariance estimation
P. Loh, M. Wainwright - Nystr{ö}m Method vs Random Fourier Features: A Theoretical and Empirical Comparison
T. Yang, Y. Li, M. Mahdavi, R. Jin, Z. Zhou - On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization
A. Barreto, D. Precup, J. Pineau - One Permutation Hashing
P. Li, A. Owen, C. Zhang - On Lifting the Gibbs Sampling Algorithm
D. Venugopal, V. Gogate - Online allocation and homogeneous partitioning for piecewise constant mean-approximation
A. Carpentier, O. Maillard - Online L1-Dictionary Learning with Application to Novel Document Detection
S. Kasiviswanathan, H. Wang, A. Banerjee, P. Melville - Online Regret Bounds for Undiscounted Continuous Reinforcement Learning
R. Ortner, D. Ryabko - Online Sum-Product Computation
M. Herbster, F. Vitale, S. Pasteris - On Multilabel Classification and Ranking with Partial Feedback
C. Gentile, F. Orabona - On the (Non-)existence of Convex, Calibrated Surrogate Losses for Ranking
C. Calauzènes, N. Usunier, P. Gallinari - On the connections between saliency and tracking
V. Mahadevan, N. Vasconcelos - On the Sample Complexity of Robust PCA
M. Coudron, G. Lerman - On the Use of Non-Stationary Policies for Stationary Infinite-Horizon Markov Decision Processes
B. Scherrer, B. Lesner - On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks
Q. Ho, J. Yin, E. Xing - Optimal kernel choice for large-scale two-sample tests
A. Gretton, B. Sriperumbudur, D. Sejdinovic, H. Strathmann, S. Balakrishnan, M. Pontil, K. Fukumizu - Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum $L_p$ Loss
Z. Wang, A. Stocker, D. Lee - Optimal Regularized Dual Averaging Methods for Stochastic Optimization
X. Chen, Q. Lin, J. Pena - Parametric Local Metric Learning for Nearest Neighbor Classification
J. Wang, A. Kalousis, A. Woznica - Patient Risk Stratification for Hospital-Associated C. Diff as a Time-Series Classification Task
J. Wiens, J. Guttag, E. Horvitz - Perceptron Learning of SAT
A. Flint, M. Blaschko - Perfect Dimensionality Recovery by Variational Bayesian PCA
S. Nakajima, R. Tomioka, M. Sugiyama, S. Babacan - Persistent Homology for Learning Densities with Bounded Support
F. Pokorny, C. Ek, H. Kjellström, D. Kragic - Phoneme Classification using Constrained Variational Gaussian Process Dynamical System
H. Park, J. Kim, S. Park, S. Yun, C. Yoo - Pointwise Tracking the Optimal Regression Function
Y. Wiener, R. El-Yaniv - Practical Bayesian Optimization of Machine Learning Algorithms
J. Snoek, H. Larochelle, R. Adams - Priors for Diversity in Generative Latent Variable Models
J. Zou, R. Adams - Privacy Aware Learning
J. Duchi, M. Jordan, M. Wainwright - Probabilistic Event Cascades for Alzheimer's disease
J. Huang, D. Alexander - Probabilistic Low-Rank Subspace Clustering
S. Babacan, S. Nakajima, M. Do - Probabilistic Topic Coding for Superset Label Learning
L. Liu, T. Dietterich - Projection Retrieval for Classification
M. Fiterau, A. Dubrawski - Proper losses for learning from partial labels
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S. Arora, R. Ge, A. Moitra, S. Sachdeva - Proximal Newton-type Methods for Minimizing Convex Objective Functions in Composite Form
J. Lee, Y. Sun, M. Saunders - Putting Bayes to sleep
W. Koolen, D. Adamskiy, M. Warmuth - Q-MKL: Matrix-induced Regularization in Multi-Kernel Learning with Applications to Neuroimaging
C. Hinrichs, V. Singh, J. Peng, S. Johnson - Query Complexity of Derivative-Free Optimization
K. Jamieson, R. Nowak, B. Recht - Random function priors for exchangeable graphs and arrays
J. Lloyd, D. Roy, P. Orbanz, Z. Ghahramani - Random Utility Theory for Social Choice: Theory and Algorithms
H. Azari, D. Parkes, L. Xia - Rational inference of relative preferences
N. Srivastava, P. Schrater - Recognizing Activities by Attribute Dynamics
W. Li, N. Vasconcelos - Recovery of Sparse Probability Measures via Convex Programming
M. Pilanci, L. El Ghaoui, V. Chandrasekaran - Recursive Deep Learning on 3D Point Clouds
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A. Rakhlin, O. Shamir, K. Sridharan - Repulsive Mixtures
F. PETRALIA, V. Rao, D. Dunson - Risk-Aversion in Multi-armed Bandits
A. Sani, A. Lazaric, R. Munos - Robustness and risk-sensitivity in Markov decision processes
T. Osogami - Scalable imputation of genetic data with a discrete fragmentation-coagulation process
L. Elliott, Y. Teh - Scalable Inference of Overlapping Communities
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S. Sra - Scaled Gradients on Grassmann Manifolds for Matrix Completion
T. Ngo, Y. Saad - Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization
S. Bach, M. Broecheler, L. Getoor, D. O'Leary - Searching for objects driven by context
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A. Das, A. Dasgupta, R. Kumar - Selective Labeling via Error Bound Minimization
Q. Gu, T. Zhang, C. Ding, J. Han - Semantic Kernel Forests from Multiple Taxonomies
S. Hwang, K. Grauman, F. Sha - Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning
J. Yi, R. Jin, A. Jain, S. Jain - Semi-Supervised Domain Adaptation with Non-Parametric Copulas
D. Lopez-Paz, J. Hernández-Lobato, B. Schölkopf - Semi-supervised Eigenvectors for Locally-biased Learning
T. Jansen Hansen, M. Mahoney - Shifting Weights: Adapting Object Detectors from Image to Video
K. Tang, V. Ramanathan, F. Li, D. Koller - Simultaneously Leveraging Output and Task Structures for Multiple-Output Regression
P. Rai, A. Kumar, H. Daume III - Sketch-Based Linear Value Function Approximation
M. Bellemare, J. Veness, M. Bowling - Slice Normalized Dynamic Markov Logic Networks
T. Papai, H. Kautz, D. Stefankovic - Slice sampling normalized kernel-weighted completely random measure mixture models
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K. Jiang, B. Kulis, M. Jordan - Sparse Approximate Manifolds for Differential Geometric MCMC
B. Calderhead, M. Sustik - Sparse Prediction with the $k$-Support Norm
A. Argyriou, R. Foygel, N. Srebro - Spectral Learning of General Weighted Automata via Constrained Matrix Completion
B. de Balle Pigem, M. Mohri - Spectral learning of linear dynamics from generalised-linear observations with application to neural population data
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Y. Lan, J. Guo, X. Cheng, T. Liu - Stochastic Gradient Descent with Only One Projection
M. Mahdavi, T. Yang, R. Jin, S. Zhu - Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions
A. Agarwal, S. Negahban, M. Wainwright - Strategic Impatience in Go/NoGo versus Forced-Choice Decision-Making
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