WebFaster Matchings via Learned Duals. Advances in Neural Information Processing Systems (NeurIPS 2024). Selected for Oral Presentation (1% of all submissions) 9. Greg Bodwin, Michael Dinitz, and Caleb Robelle. Optimal Vertex Fault-Tolerant Spanners in Polynomial Time. In Proceedings of the 32nd Annual ACM-SIAM Sym- WebJun 2, 2024 · Faster Matchings via Learned Duals A recent line of research investigates how algorithms can be augmented w... 0 Michael Dinitz, et al. ∙. share ...
Faster Matchings via Learned Duals DeepAI
WebFaster Matchings via Learned Duals. Dinitz, Michael; ... We identify three key challenges when using learned dual variables in a primal-dual algorithm. First, predicted duals may be infeasible, so we give an algorithm that efficiently maps predicted infeasible duals to nearby feasible solutions. Second, once the duals are feasible, they may not ... WebApr 4, 2024 · ATLANTA— No. 11-ranked Georgia State beach volleyball will host the annual GSU Diggin' Duals at the GSU Beach Volleyball Complex in Atlanta on Friday and … blanchfield army community hospital obgyn
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WebFaster Matchings via Learned Duals . Working Papers. TODO. Work experience. Summer 2024: Google Research Intern; Teaching. ... Online Scheduling via Learned Weights . January 07, 2024. Conference proceedings talk at ACM-SIAM Symposium on Discrete Algorithms (SODA) 2024, Salt Lake City, Utah, USA. WebFaster Matchings via Learned Duals Michael Dinitz · Sungjin Im · Thomas Lavastida · Benjamin Moseley · Sergei Vassilvitskii Keywords: ... predicted duals may be infeasible, … WebMay 20, 2024 · Dinitz, Im, Lavastida, Moseley, and Vassilvitskii (2024) have demonstrated that a warm start with learned dual solutions can improve the time complexity of the Hungarian method for weighted perfect bipartite matching. We extend and improve their framework in a principled manner via discrete convex analysis (DCA), a discrete analog … blanchfield army community hospital maternity