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Papers

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Basis Learning as an Algorithmic Primitive
Mikhail Belkin, Luis Rademacher, James Voss
2016 COLT
Batch Bayesian Optimization via Local Penalization
Javier Gonzalez, Zhenwen Dai, Philipp Hennig et al.
2016 AISTATS
2016 NIPS
Bayesian Generalised Ensemble Markov Chain Monte Carlo
Jes Frellsen, Ole Winther, Zoubin Ghahramani et al.
2016 AISTATS
Bayesian Graphical Models for Multivariate Functional Data
Hongxiao Zhu, Nate Strawn, David B. Dunson
2016 JMLR
Bayesian group factor analysis with structured sparsity
Shiwen Zhao, Chuan Gao, Sayan Mukherjee et al.
2016 JMLR
Bayesian Intermittent Demand Forecasting for Large Inventories
Matthias W Seeger, David Salinas, Valentin Flunkert
2016 NIPS
Bayesian latent structure discovery from multi-neuron recordings
Scott Linderman, Ryan P. Adams, Jonathan W Pillow
2016 NIPS
2016 JMLR
Bayesian Markov Blanket Estimation
Dinu Kaufmann, Sonali Parbhoo, Aleksander Wieczorek et al.
2016 AISTATS
Bayesian Networks for Variable Groups
Pekka Parviainen, Samuel Kaski
2016 PGM
Bayesian Nonparametric Kernel-Learning
Junier B. Oliva, Avinava Dubey, Andrew G. Wilson et al.
2016 AISTATS
Bayesian optimization for automated model selection
Gustavo Malkomes, Charles Schaff, Roman Garnett
2016 NIPS
Bayesian optimization for automated model selection
Gustavo Malkomes, Chip Schaff, Roman Garnett
2016 AUTOML
Bayesian Optimization for Probabilistic Programs
Tom Rainforth, Tuan Anh Le, Jan-Willem van de Meent et al.
2016 NIPS
2016 NIPS
Bayesian Optimization with Robust Bayesian Neural Networks
Jost Tobias Springenberg, Aaron Klein, Stefan Falkner et al.
2016 NIPS