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Poster
Thu 7:00 Provable Smoothness Guarantees for Black-Box Variational Inference
Justin Domke
Poster
Thu 7:00 Variational Inference for Sequential Data with Future Likelihood Estimates
Geon-Hyeong Kim · Youngsoo Jang · Hongseok Yang · Kee-Eung Kim
Poster
Thu 17:00 On the (In)tractability of Computing Normalizing Constants for the Product of Determinantal Point Processes
Naoto Ohsaka · Tatsuya Matsuoka
Poster
Thu 7:00 Variance Reduction and Quasi-Newton for Particle-Based Variational Inference
Michael Zhu · Chang Liu · Jun Zhu
Poster
Wed 10:00 Batch Stationary Distribution Estimation
Junfeng Wen · Bo Dai · Lihong Li · Dale Schuurmans
Poster
Thu 6:00 Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics
Matthew Hoffman · Yian Ma
Poster
Tue 13:00 Likelihood-free MCMC with Amortized Approximate Ratio Estimators
Joeri Hermans · Volodimir Begy · Gilles Louppe
Poster
Wed 8:00 Stochastic Gradient and Langevin Processes
Xiang Cheng · Dong Yin · Peter Bartlett · Michael Jordan
Poster
Tue 10:00 Error Estimation for Sketched SVD via the Bootstrap
Miles Lopes · N. Benjamin Erichson · Michael Mahoney
Poster
Wed 12:00 Automatic Reparameterisation of Probabilistic Programs
Maria Gorinova · Dave Moore · Matthew Hoffman
Poster
Thu 12:00 Double-Loop Unadjusted Langevin Algorithm
Paul Rolland · Armin Eftekhari · Ali Kavis · Volkan Cevher
Poster
Wed 8:00 Undirected Graphical Models as Approximate Posteriors
Arash Vahdat · Evgeny Andriyash · William Macready