Papers
4,025 papers found
Sparse Principal Component Analysis for High Dimensional Multivariate Time Series
Zhaoran Wang, Fang Han, Han Liu
Statistical Tests for Contagion in Observational Social Network Studies
Greg Ver Steeg, Aram Galstyan
Stochastic blockmodeling of relational event dynamics
Christopher DuBois, Carter Butts, Padhraic Smyth
Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variables
Nevena Lazic, Christopher Bishop, John Winn
Structure Learning of Mixed Graphical Models
Jason Lee, Trevor Hastie
Supervised Sequential Classification Under Budget Constraints
Kirill Trapeznikov, Venkatesh Saligrama
Texture Modeling with Convolutional Spike-and-Slab RBMs and Deep Extensions
Heng Luo, Pierre Luc Carrier, Aaron Courville et al.
Thompson Sampling in Switching Environments with Bayesian Online Change Detection
Joseph Mellor, Jonathan Shapiro
Ultrahigh Dimensional Feature Screening via RKHS Embeddings
Krishnakumar Balasubramanian, Bharath Sriperumbudur, Guy Lebanon
Uncover Topic-Sensitive Information Diffusion Networks
Nan Du, Le Song, Hyenkyun Woo et al.
Unsupervised Link Selection in Networks
Quanquan Gu, Charu Aggarwal, Jiawei Han
Why Steiner-tree type algorithms work for community detection
Mung Chiang, Henry Lam, Zhenming Liu et al.
A Bayesian Analysis of the Radioactive Releases of Fukushima
Ryota Tomioka, Morten Mrup
A Composite Likelihood View for Multi-Label Classification
Yi Zhang, Jeff Schneider
Active Learning from Multiple Knowledge Sources
Yan Yan, Romer Rosales, Glenn Fung et al.
Adaptive MCMC with Bayesian Optimization
Nimalan Mahendran, Ziyu Wang, Firas Hamze et al.
Adaptive Metropolis with Online Relabeling
Remi Bardenet, Olivier Cappe, Gersende Fort et al.
A Differentially Private Stochastic Gradient Descent Algorithm for Multiparty Classification
Arun Rajkumar, Shivani Agarwal
A Family of MCMC Methods on Implicitly Defined Manifolds
Marcus Brubaker, Mathieu Salzmann, Raquel Urtasun
Age-Layered Expectation Maximization for Parameter Learning in Bayesian Networks
Avneesh Saluja, Priya Krishnan Sundararajan, Ole J Mengshoel
A General Framework for Structured Sparsity via Proximal Optimization
Luca Baldassarre, Jean Morales, Andreas Argyriou et al.
A Hybrid Neural Network-Latent Topic Model
Li Wan, Leo Zhu, Rob Fergus
A metric learning perspective of SVM: on the relation of LMNN and SVM
Huyen Do, Alexandros Kalousis, Jun Wang et al.
An Autoregressive Approach to Nonparametric Hierarchical Dependent Modeling
Zhihua Zhang, Dakan Wang, Edward Chang
A Nonparametric Bayesian Model for Multiple Clustering with Overlapping Feature Views
Donglin Niu, Jennifer Dy, Zoubin Ghahramani