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02/20/2023
Simplifying Momentum-based Riemannian Submanifold Optimization
Riemannian submanifold optimization with momentum is computationally cha...
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07/22/2021
Structured second-order methods via natural gradient descent
In this paper, we propose new structured second-order methods and struct...
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02/15/2021
Tractable structured natural gradient descent using local parameterizations
Natural-gradient descent on structured parameter spaces (e.g., low-rank ...
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02/24/2020
Handling the Positive-Definite Constraint in the Bayesian Learning Rule
Bayesian learning rule is a recently proposed variational inference meth...
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10/29/2019
Stein's Lemma for the Reparameterization Trick with Exponential Family Mixtures
Stein's method (Stein, 1973; 1981) is a powerful tool for statistical ap...
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06/07/2019
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations
Natural-gradient methods enable fast and simple algorithms for variation...
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06/13/2018
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Uncertainty computation in deep learning is essential to design robust a...
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03/15/2018
Variational Message Passing with Structured Inference Networks
Recent efforts on combining deep models with probabilistic graphical mod...
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11/15/2017
Variational Adaptive-Newton Method for Explorative Learning
We present the Variational Adaptive Newton (VAN) method which is a black...
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10/31/2015