Jun 8, 2021 · This paper studies the online correlated selection (OCS) problem. It was introduced by Fahrbach, Huang, Tao, and Zadimoghaddam (2020)

Abstract—This paper studies online correlated selection. (OCS). Suppose that we receive a pair of elements in each round and select one of them.

This paper studies the online correlated selection (OCS) problem. It was introduced by. Fahrbach, Huang, Tao, and Zadimoghaddam (2020) to obtain the first edge- ...

This paper studies online correlated selection (OCS). Suppose that we receive a pair of elements in each round and select one of them.

Abstract: This paper studies online correlated selection (OCS). Suppose that we receive a pair of elements in each round and select one of them.

It is proved that the optimal “level of negative correlation” is between 0.167 and 0.25, improving the previous bounds of 0.109 and 1 by Fahrbach et al.

The proposed techniques employ a method for adjusting the adaptive weight (forgetting factor) of the RLS algorithm to exploit the time correlation of the ...

Aug 22, 2024 · We study Stochastic Online Correlated Selection (SOCS), a family of online rounding algorithms for Non-IID Stochastic Online Submodular Welfare Maximization ...

Duration: 20:46
Posted: Feb 10, 2022

Aug 23, 2024 · Intro: What is Online Correlated Selection? ❑ Optimal two-way OCS for matching. ❑ OCS for Display Ads. Part II.