# JMLR Workshop and Conference Proceedings

## Volume 32: Proceedings of The 31st International Conference on Machine Learning

**Editors:
Eric P. Xing,
Tony Jebara
**

### Cycle 1 Papers

Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization

An Adaptive Accelerated Proximal Gradient Method and its Homotopy Continuation for Sparse Optimization

[abs] [pdf] [supplementary]

A Statistical Convergence Perspective of Algorithms for Rank Aggregation from Pairwise Data

[abs] [pdf] [supplementary]

Scaling Up Approximate Value Iteration with Options: Better Policies with Fewer Iterations

[abs] [pdf] [supplementary]

Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball

[abs] [pdf] [supplementary]

Robust RegBayes: Selectively Incorporating First-Order Logic Domain Knowledge into Bayesian Models

Learning Theory and Algorithms for revenue optimization in second price auctions with reserve

[abs] [pdf] [supplementary]

Prediction with Limited Advice and Multiarmed Bandits with Paid Observations

[abs] [pdf] [supplementary]

Efficient Approximation of Cross-Validation for Kernel Methods using Bouligand Influence Function

Optimal Budget Allocation: Theoretical Guarantee and Efficient Algorithm

[abs] [pdf] [supplementary]

Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach

[abs] [pdf] [supplementary]

Diagnosis determination: decision trees optimizing simultaneously worst and expected testing cost

(Near) Dimension Independent Risk Bounds for Differentially Private Learning

[abs] [pdf] [supplementary]

Forward-Backward Greedy Algorithms for General Convex Smooth Functions over A Cardinality Constraint

Online Learning in Markov Decision Processes with Changing Cost Sequences

[abs] [pdf] [supplementary]

Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection

[abs] [pdf] [supplementary]

Asymptotically consistent estimation of the number of change points in highly dependent time series

Coordinate-descent for learning orthogonal matrices through Givens rotations

[abs] [pdf] [supplementary]

Towards an optimal stochastic alternating direction method of multipliers

[abs] [pdf] [supplementary]

Making the Most of Bag of Words: Sentence Regularization with Alternating Direction Method of Multipliers

Learning Sum-Product Networks with Direct and Indirect Variable Interactions

[abs] [pdf] [supplementary]

Stochastic Dual Coordinate Ascent with Alternating Direction Method of Multipliers

[abs] [pdf] [supplementary]

Deep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction

### Cycle 2 Papers

Automated inference of point of view from user interactions in collective intelligence venues

On p-norm Path Following in Multiple Kernel Learning for Non-linear Feature Selection

[abs] [pdf] [supplementary]

Improving offline evaluation of contextual bandit algorithms via bootstrapping techniques

[abs] [pdf] [supplementary]

Optimal PAC Multiple Arm Identification with Applications to Crowdsourcing

[abs] [pdf] [supplementary]

A Highly Scalable Parallel Algorithm for Isotropic Total Variation Models

[abs] [pdf] [supplementary]

Statistical-Computational Phase Transitions in Planted Models: The High-Dimensional Setting

[abs] [pdf] [supplementary]

Safe Screening with Variational Inequalities and Its Application to Lasso

[abs] [pdf] [supplementary]

Learning the Consistent Behavior of Common Users for Target Node Prediction across Social Networks

[abs] [pdf] [supplementary]

Multi-label Classification via Feature-aware Implicit Label Space Encoding

[abs] [pdf] [supplementary]

Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications

[abs] [pdf] [supplementary]

Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices

[abs] [pdf] [supplementary]

Elementary Estimators for Sparse Covariance Matrices and other Structured Moments

[abs] [pdf] [supplementary]

Graph-based Semi-supervised Learning: Realizing Pointwise Smoothness Probabilistically

[abs] [pdf] [supplementary]

Gaussian Process Classification and Active Learning with Multiple Annotators

[abs] [pdf] [supplementary]

An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation Accuracy

Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification

[abs] [pdf] [supplementary]

A Single-Pass Algorithm for Efficiently Recovering Sparse Cluster Centers of High-dimensional Data

[abs] [pdf] [supplementary]

Topic Modeling using Topics from Many Domains, Lifelong Learning and Big Data

[abs] [pdf] [supplementary]

Nonmyopic \(\epsilon\)-Bayes-Optimal Active Learning of Gaussian Processes

[abs] [pdf] [supplementary]

Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm

[abs] [pdf] [supplementary]

Combinatorial Partial Monitoring Game with Linear Feedback and Its Applications

[abs] [pdf] [supplementary]

Approximation Analysis of Stochastic Gradient Langevin Dynamics by using Fokker-Planck Equation and Ito Process

Communication-Efficient Distributed Optimization using an Approximate Newton-type Method

[abs] [pdf] [supplementary]

Anti-differentiating approximation algorithms:A case study with min-cuts, spectral, and flow

Preference-Based Rank Elicitation using Statistical Models: The Case of Mallows

[abs] [pdf] [supplementary]

Hierarchical Conditional Random Fields for Outlier Detection: An Application to Detecting Epileptogenic Cortical Malformations

Ensemble-Based Tracking: Aggregating Crowdsourced Structured Time Series Data

[abs] [pdf] [supplementary]

Finito: A faster, permutable incremental gradient method for big data problems

[abs] [pdf] [supplementary]

Standardized Mutual Information for Clustering Comparisons: One Step Further in Adjustment for Chance

[abs] [pdf] [supplementary]

Stochastic Backpropagation and Approximate Inference in Deep Generative Models

[abs] [pdf] [supplementary]

High Order Regularization for Semi-Supervised Learning of Structured Output Problems

[abs] [pdf] [supplementary]

Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison

[abs] [pdf] [supplementary]

The f-Adjusted Graph Laplacian: a Diagonal Modification with a Geometric Interpretation

[abs] [pdf] [supplementary]

GeNGA: A Generalization of Natural Gradient Ascent with Positive and Negative Convergence Results

Multi-period Trading Prediction Markets with Connections to Machine Learning

[abs] [pdf] [supplementary]

Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets

Estimating Latent-Variable Graphical Models using Moments and Likelihoods

[abs] [pdf] [supplementary]

GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare

[abs] [pdf] [supplementary]

Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing

[abs] [pdf] [supplementary]