About This Website
Blog posts on computational aspects of differential, geometric, and algebraic structures (i.e., probability distributions and matrices). Many posts are related to information geometry and manifold optimization with their applications to numerical optimization and approximate inference.
For generalized natural-gradient methods, please see
- Structured natural gradient descent: long talk, short talk, paper, blog
- Riemannian gradient descent: talk, paper
For an introduction to natural-gradient methods, see this blog.
News
| Jul 2, 2021 | New workshop paper on Structured second-order methods via natural gradient descent out. Will be presented at the Beyond first-order methods in ML systems Workshop at ICML2021, see the spotlight talk. |
| Jun 30, 2021 | Tractable structured natural gradient descent using local parameterizations accepted at ICML2021! |
| Jun 30, 2020 | Handling the positive-definite constraint in the bayesian learning rule accepted at ICML2020, see the ICML talk. |
| Jun 30, 2019 | Fast and simple natural-gradient variational inference with mixture of exponential-family approximations accepted at ICML2019! |
| Jun 1, 2018 | Fast and scalable bayesian deep learning by weight-perturbation in Adam accepted at ICML2018! |