Fields- 2021-2022 Machine Learning Advances and Applications Seminar
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Title: SGD in the Large: Average-case Analysis, Asymptotics, and Stepsize Criticality
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Title: Kernel Thinning and Stein Thinning
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Title: SubLign: A deep generative model for clustering censored time-series data
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Title: How Humans Factor into AI Clinical Deployments
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Title: Safe and Efficient Exploration in Reinforcement Learning
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Title: On the Role of Data Structure in High-dimensional Learning
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Title: JAX: accelerated machine learning research via composable function transformations in Python
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Title: A Geometric Approach to Disentangling
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Title: Robot Learning - Quo Vadis?
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Title: Probabilistic Numerics for Inference with Simulations
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Title: The Extreme of Interpretability in Machine Learning
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Title: MCMC Training of Bayesian Neural Networks
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Title: Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces
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