# JMLR Workshop and Conference Proceedings

## Volume 38: Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics

**Editors:
Guy Lebanon,
S.V.N. Vishwanathan
**

### Accepted Papers

Spectral Gap Error Bounds for Improving CUR Matrix Decomposition and the Nyström Method

[abs] [pdf] [supplementary]

Efficient Sparse Clustering of High-Dimensional Non-spherical Gaussian Mixtures

[abs] [pdf] [supplementary]

Unifying Local Consistency and MAX SAT Relaxations for Scalable Inference with Rounding Guarantees

[abs] [pdf] [supplementary]

Predictive Inverse Optimal Control for Linear-Quadratic-Gaussian Systems

[abs] [pdf] [supplementary]

Averaged Least-Mean-Squares: Bias-Variance Trade-offs and Optimal Sampling Distributions

[abs] [pdf] [supplementary]

Back to the Past: Source Identification in Diffusion Networks from Partially Observed Cascades

[abs] [pdf] [supplementary]

A Sufficient Statistics Construction of Exponential Family Le ́vy Measure Densities for Nonparametric Conjugate Models

[abs] [pdf] [supplementary]

Efficient Estimation of Mutual Information for Strongly Dependent Variables

[abs] [pdf] [supplementary]

The Bayesian Echo Chamber: Modeling Social Influence via Linguistic Accommodation

[abs] [pdf] [supplementary]

Reliable and Scalable Variational Inference for the Hierarchical Dirichlet Process

[abs] [pdf] [supplementary]

Cross-domain recommendation without shared users or items by sharing latent vector distributions

On Approximate Non-submodular Minimization via Tree-Structured Supermodularity

[abs] [pdf] [supplementary]

Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering

[abs] [pdf] [supplementary]

Bayesian Hierarchical Clustering with Exponential Family: Small-Variance Asymptotics and Reducibility

[abs] [pdf] [supplementary]

Scalable Optimization of Randomized Operational Decisions in Adversarial Classification Settings

[abs] [pdf] [supplementary]

Conditional Restricted Boltzmann Machines for Multi-label Learning with Incomplete Labels

On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives

[abs] [pdf] [supplementary]

Non-Uniform Stochastic Average Gradient Method for Training Conditional Random Fields

[abs] [pdf] [supplementary]

A Rate of Convergence for Mixture Proportion Estimation, with Application to Learning from Noisy Labels

Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence

[abs] [pdf] [supplementary]

Exploiting Symmetries to Construct Efficient MCMC Algorithms With an Application to SLAM

[abs] [pdf] [supplementary]

State Space Methods for Efficient Inference in Student-t Process Regression

[abs] [pdf] [supplementary]

Calibration of conditional composite likelihood for Bayesian inference on Gibbs random fields

Predicting Preference Reversals via Gaussian Process Uncertainty Aversion

[abs] [pdf] [supplementary]

Streaming Variational Inference for Bayesian Nonparametric Mixture Models

[abs] [pdf] [supplementary]

Learning of Non-Parametric Control Policies with High-Dimensional State Features

[abs] [pdf] [supplementary]

Maximally Informative Hierarchical Representations of High-Dimensional Data

[abs] [pdf] [supplementary]

Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction

[abs] [pdf] [supplementary]

The Log-Shift Penalty for Adaptive Estimation of Multiple Gaussian Graphical Models

[abs] [pdf] [supplementary]