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175 Results
Poster
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Wed 17:00 |
Sample Adaptive MCMC Michael Zhu |
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Poster
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Thu 10:45 |
Thompson Sampling and Approximate Inference My Phan · Yasin Abbasi Yadkori · Justin Domke |
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Poster
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Tue 10:45 |
AGEM: Solving Linear Inverse Problems via Deep Priors and Sampling Bichuan Guo · Yuxing Han · Jiangtao Wen |
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Poster
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Wed 10:45 |
An Adaptive Empirical Bayesian Method for Sparse Deep Learning Wei Deng · Xiao Zhang · Faming Liang · Guang Lin |
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Poster
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Tue 17:30 |
The Randomized Midpoint Method for Log-Concave Sampling Ruoqi Shen · Yin Tat Lee |
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Poster
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Tue 17:30 |
Pseudo-Extended Markov chain Monte Carlo Christopher Nemeth · Fredrik Lindsten · Maurizio Filippone · James Hensman |
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Poster
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Tue 17:30 |
Stochastic Gradient Hamiltonian Monte Carlo Methods with Recursive Variance Reduction Difan Zou · Pan Xu · Quanquan Gu |
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Poster
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Tue 17:30 |
Parameter elimination in particle Gibbs sampling Anna Wigren · Riccardo Sven Risuleo · Lawrence Murray · Fredrik Lindsten |
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Poster
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Tue 17:30 |
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond Xuechen (Chen) Li · Denny Wu · Lester Mackey · Murat Erdogdu |
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Poster
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Wed 17:00 |
Estimating Convergence of Markov chains with L-Lag Couplings Niloy Biswas · Pierre E Jacob · Paul Vanetti |
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Poster
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Tue 17:30 |
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates Adil Salim · Dmitry Kovalev · Peter Richtarik |
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Poster
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Wed 17:00 |
Gradient-based Adaptive Markov Chain Monte Carlo Michalis Titsias · Petros Dellaportas |