## Volume 33: Artificial Intelligence and Statistics, 22-25 April 2014, Reykjavik, Iceland

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**Editors:
Samuel Kaski,
Jukka Corander
**

### Preface

### Notable Papers

Analysis of Empirical MAP and Empirical Partially Bayes: Can They be Alternatives to Variational Bayes?

PMLR 33:20-28

;### Regular Papers

Improved Bounds for Online Learning Over the Permutahedron and Other Ranking Polytopes

PMLR 33:29-37

;Information-Theoretic Characterization of Sparse Recovery

PMLR 33:38-46

;[abs] [pdf] [supplementary]

Hybrid Discriminative-Generative Approach with Gaussian Processes

PMLR 33:47-56

;[abs] [pdf] [supplementary]

Average Case Analysis of High-Dimensional Block-Sparse Recovery and Regression for Arbitrary Designs

PMLR 33:57-67

;A New Perspective on Learning Linear Separators with Large L_qL_p Margins

PMLR 33:68-76

;[abs] [pdf] [supplementary]

A Non-parametric Conditional Factor Regression Model for Multi-Dimensional Input and Response

PMLR 33:77-85

;Learning Optimal Bounded Treewidth Bayesian Networks via Maximum Satisfiability

PMLR 33:86-95

;Online Passive-Aggressive Algorithms for Non-Negative Matrix Factorization and Completion

PMLR 33:96-104

;[abs] [pdf] [supplementary]

Efficient Low-Rank Stochastic Gradient Descent Methods for Solving Semidefinite Programs

PMLR 33:122-130

;Characterizing EVOI-Sufficient k-Response Query Sets in Decision Problems

PMLR 33:131-139

;Doubly Aggressive Selective Sampling Algorithms for Classification

PMLR 33:140-148

;[abs] [pdf] [supplementary]

Sparse Bayesian Variable Selection for the Identification of Antigenic Variability in the Foot-and-Mouth Disease Virus

PMLR 33:149-158

;Efficient Distributed Topic Modeling with Provable Guarantees

PMLR 33:167-175

;[abs] [pdf] [supplementary]

Pan-sharpening with a Bayesian nonparametric dictionary learning model

PMLR 33:176-184

;Efficient Inference for Complex Queries on Complex Distributions

PMLR 33:211-219

;[abs] [pdf] [supplementary]

Bayesian Nonparametric Poisson Factorization for Recommendation Systems

PMLR 33:275-283

;[abs] [pdf] [supplementary]

Learning and Evaluation in Presence of Non-i.i.d. Label Noise

PMLR 33:293-302

;[abs] [pdf] [supplementary]

Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics

PMLR 33:347-355

;[abs] [pdf] [supplementary]

On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning

PMLR 33:365-374

;[abs] [pdf] [supplementary]

Optimality of Thompson Sampling for Gaussian Bandits Depends on Priors

PMLR 33:375-383

;[abs] [pdf] [supplementary]

Tight Bounds for the Expected Risk of Linear Classifiers and PAC-Bayes Finite-Sample Guarantees

PMLR 33:384-392

;[abs] [pdf] [supplementary]

A Finite-Sample Generalization Bound for Semiparametric Regression: Partially Linear Models

PMLR 33:402-410

;[abs] [pdf] [supplementary]

Global Optimization Methods for Extended Fisher Discriminant Analysis

PMLR 33:411-419

;[abs] [pdf] [supplementary]

High-Dimensional Density Ratio Estimation with Extensions to Approximate Likelihood Computation

PMLR 33:420-429

;[abs] [pdf] [supplementary]

Near Optimal Bayesian Active Learning for Decision Making

PMLR 33:430-438

;[abs] [pdf] [supplementary]

A Level-set Hit-and-run Sampler for Quasi-Concave Distributions

PMLR 33:439-447

;[abs] [pdf] [supplementary]

Recovering Distributions from Gaussian RKHS Embeddings

PMLR 33:457-465

;[abs] [pdf] [supplementary]

A Gaussian Latent Variable Model for Large Margin Classification of Labeled and Unlabeled Data

PMLR 33:484-492

;[abs] [pdf] [supplementary]

Scalable Variational Bayesian Matrix Factorization with Side Information

PMLR 33:493-502

;Algebraic Reconstruction Bounds and Explicit Inversion for Phase Retrieval at the Identifiability Threshold

PMLR 33:503-511

;[abs] [pdf] [supplementary]

Visual Boundary Prediction: A Deep Neural Prediction Network and Quality Dissection

PMLR 33:512-521

;[abs] [pdf] [supplementary]

Fugue: Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data

PMLR 33:531-539

;[abs] [pdf] [supplementary]

Incremental Tree-Based Inference with Dependent Normalized Random Measures

PMLR 33:558-566

;[abs] [pdf] [supplementary]

A Geometric Algorithm for Scalable Multiple Kernel Learning

PMLR 33:633-642

;[abs] [pdf] [supplementary]

The Dependent Dirichlet Process Mixture of Objects for Detection-free Tracking and Object Modeling

PMLR 33:660-668

;Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence

PMLR 33:669-677

;[abs] [pdf] [supplementary]

Robust Forward Algorithms via PAC-Bayes and Laplace Distributions

PMLR 33:678-686

;[abs] [pdf] [supplementary]

Joint Structure Learning of Multiple Non-Exchangeable Networks

PMLR 33:687-695

;[abs] [pdf] [supplementary]

Scaling Nonparametric Bayesian Inference via Subsample-Annealing

PMLR 33:696-705

;[abs] [pdf] [supplementary]

LAMORE: A Stable, Scalable Approach to Latent Vector Autoregressive Modeling of Categorical Time Series

PMLR 33:733-742

;Spoofing Large Probability Mass Functions to Improve Sampling Times and Reduce Memory Costs

PMLR 33:743-750

;Learning Bounded Tree-width Bayesian Networks using Integer Linear Programming

PMLR 33:751-759

;An Efficient Algorithm for Large Scale Compressive Feature Learning

PMLR 33:760-768

;[abs] [pdf] [supplementary]

Expectation Propagation for Likelihoods Depending on an Inner Product of Two Multivariate Random Variables

PMLR 33:769-777

;[abs] [pdf] [supplementary]

An inclusion optimal algorithm for chain graph structure learning

PMLR 33:778-786

;[abs] [pdf] [supplementary]

A Stepwise uncertainty reduction approach to constrained global optimization

PMLR 33:787-795

;An Analysis of Active Learning with Uniform Feature Noise

PMLR 33:805-813

;[abs] [pdf] [supplementary]

Sequential crowdsourced labeling as an epsilon-greedy exploration in a Markov Decision Process

PMLR 33:832-840

;[abs] [pdf] [supplementary]

Learning Structured Models with the AUC Loss and Its Generalizations

PMLR 33:841-849

;[abs] [pdf] [supplementary]

Class Proportion Estimation with Application to Multiclass Anomaly Rejection

PMLR 33:850-858

;[abs] [pdf] [supplementary]

Estimating Dependency Structures for non-Gaussian Components with Linear and Energy Correlations

PMLR 33:868-876

;[abs] [pdf] [supplementary]

Student-t Processes as Alternatives to Gaussian Processes

PMLR 33:877-885

;[abs] [pdf] [supplementary]

Explicit Link Between Periodic Covariance Functions and State Space Models

PMLR 33:904-912

;Bat Call Identification with Gaussian Process Multinomial Probit Regression and a Dynamic Time Warping Kernel

PMLR 33:913-921

;SMERED: A Bayesian Approach to Graphical Record Linkage and De-duplication

PMLR 33:922-930

;[abs] [pdf] [supplementary]

Scaling Graph-based Semi Supervised Learning to Large Number of Labels Using Count-Min Sketch

PMLR 33:940-947

;Path Thresholding: Asymptotically Tuning-Free High-Dimensional Sparse Regression

PMLR 33:948-957

;Active Learning for Undirected Graphical Model Selection

PMLR 33:958-967

;[abs] [pdf] [supplementary]

Linear-time training of nonlinear low-dimensional embeddings

PMLR 33:968-977

;[abs] [pdf] [supplementary]

Efficient Algorithms and Error Analysis for the Modified Nystrom Method

PMLR 33:996-1004

;[abs] [pdf] [supplementary]

Context Aware Group Nearest Shrunken Centroids in Large-Scale Genomic Studies

PMLR 33:1051-1059

;[abs] [pdf] [supplementary]

Efficient Transfer Learning Method for Automatic Hyperparameter Tuning

PMLR 33:1077-1085

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