The Optimal Smoothings of Sublinear Functions and Convex Cones
Published in ArXiv Preprint, 2025
This paper provides smooth, convex functions (or sets) of fixed curvature that minimize the distance to the original function (or set).
Publications
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Scalable Projection-Free Optimization Methods via MultiRadial Duality Theory
Published in ArXiv Preprint, 2024
This paper presents the multiradial method for solving constrained convex optimization problems. This method assumes minimal structure on the objective function and does not rely on projections to the feasible region.
On the consistency of graph-based Bayesian semi-supervised learning and the scalability of sampling algorithms
Published in Journal of Machine Learning Research, 2020
This paper presents interesting theoretical properties of a Bayesian approach to semi-supervised learning on graphs.