Applied Mathematics
The Polyak-Lojasiewicz condition as a framework for over-parameterized optimization and its application to deep learning
Fast & Accurate Randomized Algorithms for Linear Systems and Eigenvalue Problems
Kernel two-sample test: on manifold data and by neural tangent kernel
Manifold learning with non-Euclidean norms, and orbit recovery
How to apply manifold learning and random matrix theory to study complicated time series?
Uncertainties and inference in physical dynamics
Probabilistic Variable Selection
On the topic of topic modeling: enhancing machine learning approaches with topic features"
Efficient distribution classification via optimal transport embeddings
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