no code implementations • 8 May 2024 • Yixin Chen, Ankur Nath, Chunli Peng, Alan Kuhnle
In this work, we develop the first combinatorial algorithms to break the $1/e$ barrier: we obtain approximation ratio of $0. 385$ in $\mathcal O (kn)$ queries to the submodular set function for size constraint, and $0. 305$ for a general matroid constraint.
no code implementations • 30 Oct 2023 • Ankur Nath, Alan Kuhnle
In recent years, combining neural networks with local search heuristics has become popular in the field of combinatorial optimization.
no code implementations • 21 Dec 2020 • Mohammad Zunaed, Ankur Nath, Md. Saifur Rahman
This loss explores cycle-invariant PD-specific features, enabling the model to learn more robust, noise-invariant features for PD detection.