Papers
Averaged Collapsed Variational Bayes Inference
Katsuhiko Ishiguro, Issei Sato, Naonori Ueda
Bayesian Inference for Spatio-temporal Spike-and-Slab Priors
Michael Riis Andersen, Aki Vehtari, Ole Winther et al.
Bayesian Learning of Dynamic Multilayer Networks
Daniele Durante, Nabanita Mukherjee, Rebecca C. Steorts
Bayesian Network Learning via Topological Order
Young Woong Park, Diego Klabjan
Bayesian Tensor Regression
Rajarshi Guhaniyogi, Shaan Qamar, David B. Dunson
Bridging Supervised Learning and Test-Based Co-optimization
Elena Popovici
Certifiably Optimal Low Rank Factor Analysis
Dimitris Bertsimas, Martin S. Copenhaver, Rahul Mazumder
Classification of Time Sequences using Graphs of Temporal Constraints
Mathieu Guillame-Bert, Artur Dubrawski
Clustering from General Pairwise Observations with Applications to Time-varying Graphs
Shiau Hong Lim, Yudong Chen, Huan Xu
Clustering with Hidden Markov Model on Variable Blocks
Lin Lin, Jia Li
COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Evolution
Mehrdad Farajtabar, Yichen Wang, Manuel Gomez-Rodriguez et al.
Communication-efficient Sparse Regression
Jason D. Lee, Qiang Liu, Yuekai Sun et al.
Community Extraction in Multilayer Networks with Heterogeneous Community Structure
James D. Wilson, John Palowitch, Shankar Bhamidi et al.
Computational Limits of A Distributed Algorithm for Smoothing Spline
Zuofeng Shang, Guang Cheng
Confidence Sets with Expected Sizes for Multiclass Classification
Christophe Denis, Mohamed Hebiri
Consistency, Breakdown Robustness, and Algorithms for Robust Improper Maximum Likelihood Clustering
Pietro Coretto, Christian Hennig
Convolutional Neural Networks Analyzed via Convolutional Sparse Coding
Vardan Papyan, Yaniv Romano, Michael Elad
Dense Distributions from Sparse Samples: Improved Gibbs Sampling Parameter Estimators for LDA
Yannis Papanikolaou, James R. Foulds, Timothy N. Rubin et al.
Density Estimation in Infinite Dimensional Exponential Families
Bharath Sriperumbudur, Kenji Fukumizu, Arthur Gretton et al.
Differential Privacy for Bayesian Inference through Posterior Sampling
Christos Dimitrakakis, Blaine Nelson, Zuhe Zhang et al.
Dimension Estimation Using Random Connection Models
Paulo Serra, Michel Mandjes
Distributed Bayesian Learning with Stochastic Natural Gradient Expectation Propagation and the Posterior Server
Leonard Hasenclever, Stefan Webb, Thibaut Lienart et al.
Distributed Learning with Regularized Least Squares
Shao-Bo Lin, Xin Guo, Ding-Xuan Zhou
Distributed Semi-supervised Learning with Kernel Ridge Regression
Xiangyu Chang, Shao-Bo Lin, Ding-Xuan Zhou