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80 Results
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Oral
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Thu 10:30 |
Stochastic Deep Networks with Linear Competing Units for Model-Agnostic Meta-Learning Konstantinos Kalais · Sotirios Chatzis |
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Poster
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Thu 15:00 |
NP-Match: When Neural Processes meet Semi-Supervised Learning Jianfeng Wang · Thomas Lukasiewicz · Daniela Massiceti · Xiaolin Hu · Vladimir Pavlovic · Alexandros Neophytou |
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Spotlight
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Wed 10:25 |
Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders Samuel Stanton · Wesley Maddox · Nate Gruver · Phillip Maffettone · Emily Delaney · Peyton Greenside · Andrew Wilson |
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Poster
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Wed 15:30 |
Sequential- and Parallel- Constrained Max-value Entropy Search via Information Lower Bound Shion Takeno · Tomoyuki Tamura · Kazuki Shitara · Masayuki Karasuyama |
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Oral
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Tue 13:15 |
Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes Insu Han · Mike Gartrell · Elvis Dohmatob · Amin Karbasi |
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Poster
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Thu 15:00 |
Distributionally-Aware Kernelized Bandit Problems for Risk Aversion Sho Takemori |
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Poster
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Wed 15:30 |
Bayesian Continuous-Time Tucker Decomposition Shikai Fang · Akil Narayan · Robert Kirby · Shandian Zhe |
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Poster
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Tue 15:30 |
Preconditioning for Scalable Gaussian Process Hyperparameter Optimization Jonathan Wenger · Geoff Pleiss · Philipp Hennig · John Cunningham · Jacob Gardner |
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Poster
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Tue 15:30 |
Bayesian Optimization for Distributionally Robust Chance-constrained Problem Yu Inatsu · Shion Takeno · Masayuki Karasuyama · Ichiro Takeuchi |
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Oral
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Wed 11:00 |
Function-space Inference with Sparse Implicit Processes Simon R Santana · Bryan Zaldivar · Daniel Hernandez-Lobato |
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Poster
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Tue 15:30 |
Bayesian Nonparametric Learning for Point Processes with Spatial Homogeneity: A Spatial Analysis of NBA Shot Locations Fan Yin · Jieying Jiao · Jun Yan · Guanyu Hu |
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Poster
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Tue 15:30 |
Probabilistic ODE Solutions in Millions of Dimensions Nicholas Krämer · Nathanael Bosch · Jonathan Schmidt · Philipp Hennig |