Papers
Unwrapping ADMM: Efficient Distributed Computing via Transpose Reduction
Tom Goldstein, Gavin Taylor, Kawika Barabin et al.
Variational Gaussian Copula Inference
Shaobo Han, Xuejun Liao, David Dunson et al.
Variational Tempering
Stephan Mandt, James McInerney, Farhan Abrol et al.
A Bayes consistent 1-NN classifier
Aryeh Kontorovich, Roi Weiss
Accurate and conservative estimates of MRF log-likelihood using reverse annealing
Yuri Burda, Roger Grosse, Ruslan Salakhutdinov
A Consistent Method for Graph Based Anomaly Localization
Satoshi Hara, Tetsuro Morimura, Toshihiro Takahashi et al.
Active Pointillistic Pattern Search
Yifei Ma, Danica J. Sutherland, Roman Garnett et al.
A Dirichlet Process Mixture Model for Spherical Data
Julian Straub, Jason Chang, Oren Freifeld et al.
A Greedy Homotopy Method for Regression with Nonconvex Constraints
Fabian Wauthier, Peter Donnelly
A la Carte – Learning Fast Kernels
Zichao Yang, Andrew Wilson, Alex Smola et al.
A Scalable Algorithm for Structured Kernel Feature Selection
Shaogang Ren, Shuai Huang, John Onofrey et al.
A Simple Homotopy Algorithm for Compressive Sensing
Lijun Zhang, Tianbao Yang, Rong Jin et al.
A Spectral Algorithm for Inference in Hidden semi-Markov Models
Igor Melnyk, Arindam Banerjee
A Topic Modeling Approach to Ranking
Weicong Ding, Prakash Ishwar, Venkatesh Saligrama
A totally unimodular view of structured sparsity
Marwa El Halabi, Volkan Cevher
Averaged Least-Mean-Squares: Bias-Variance Trade-offs and Optimal Sampling Distributions
Alexandre Defossez, Francis Bach
Back to the Past: Source Identification in Diffusion Networks from Partially Observed Cascades
Mehrdad Farajtabar, Manuel Gomez Rodriguez, Mohammad Zamani et al.
Calibration of conditional composite likelihood for Bayesian inference on Gibbs random fields
Julien Stoehr, Nial Friel
Column Subset Selection with Missing Data via Active Sampling
Yining Wang, Aarti Singh
Compressed Sensing with Very Sparse Gaussian Random Projections
Ping Li, Cun-Hui Zhang
Computational Complexity of Linear Large Margin Classification With Ramp Loss
Søren Frejstrup Maibing, Christian Igel
Conditional Restricted Boltzmann Machines for Multi-label Learning with Incomplete Labels
Xin Li, Feipeng Zhao, Yuhong Guo