mingzhang-yin/Probabilistic-Best-Subset

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Created over 4 years ago
Updated over 2 years ago

mingzhang-yin/Probabilistic-Best-Subset

mingzhang-yin

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A probabilistic solution to the exact best subset selection problem via continuous reformulation and gradient-based optimization.

SIVI

A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural networks and hierarchical distribution (ICML 2018).

ARM-gradient

Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)

Meta-learning-without-memorization

A study on the following problems: what the memorization problem is in meta-learning; why memorization problem happens; and how we can prevent it. (ICLR 2020)

Jupyter Notebook

CoCo

An optimization-based algorithm to accurately estimate the causal effects and robustly predict under distribution shifts. It leverages the invariance of causality over multiple environments.

mingzhang-yin.github.io

Personal webpage

Convergence-of-Gradient-EM-on-Multi-component-Mixture-of-Gaussians

Proof of local convergence region and convergence rate of gradient EM on general GMM, for both population and finite sample setting. (NeurIPS 2017)

Conformal-sensitivity-analysis

Analyzing the sensitivity of an individual treatment effect over a potential violation of unconfoundedness.