Efficient Vertex-Oriented Polytopic Projection for Web-Scale Applications
Rohan Ramanath, S. Sathiya Keerthi, Yao Pan, Konstantin Salomatin, Kinjal Basu
摘要
We consider applications involving a large set of instances of projecting points to polytopes. We develop an intuition guided by theoretical and empirical analysis to show that when these instances follow certain structures, a large majority of the projections lie on vertices of the polytopes. To do these projections efficiently we derive a vertex-oriented incremental algorithm to project a point onto any arbitrary polytope, as well as give specific algorithms to cater to simplex projection and polytopes where the unit box is cut by planes. Such settings are especially useful in web-scale applications such as optimal matching or allocation problems. Several such problems in internet marketplaces (e-commerce, ride-sharing, food delivery, professional services, advertising, etc.), can be formulated as Linear Programs (LP) with such polytope constraints that require a projection step in the overall optimization process. We show that in some of the very recent works, the polytopic projection is the most expensive step and our efficient projection algorithms help in gaining massive improvements in performance.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
它引用的顶会 Paper1
相关 Paper
- Two-stage Stochastic Matching with Application to Ride HailingYiding Feng, Rad Niazadeh, Amin SaberiSODA 2021 · 被引用 12 次
- Accelerated Approximate Optimization of Multi-commodity Flows on Directed GraphsLi Chen, Andrei Graur, Aaron SidfordSTOC 2025 · 被引用 1 次
- Quasi-popular Matchings, Optimality, and Extended FormulationsYuri Faenza, Telikepalli KavithaSODA 2020 · 被引用 4 次
- Online Ridesharing with Meeting PointsJiachuan Wang, Peng Cheng, Libin Zheng, Lei Chen 等VLDB 2022 · 被引用 13 次
- Fast Projection onto the Capped Simplex with Applications to Sparse Regression in BioinformaticsAndersen Man Shun Ang, Jianzhu Ma, Nianjun Liu, Kun Huang 等NeurIPS 2021 · 被引用 9 次
