no code implementations • 10 Jul 2022 • Boxiao Chen, Jiashuo Jiang, Jiawei Zhang, Zhengyuan Zhou
We aim to minimize the $T$-period cost, a problem that is known to be computationally intractable even under known distributions of demand and supply.
no code implementations • 21 Nov 2020 • Boxiao Chen, Selvaprabu Nadarajah, Parshan Pakiman, Stefanus Jasin
We also show that ARL, by being conscious of both model ambiguity and revenue, bridges the gap between a distributionally robust policy and a follow-the-leader policy, which focus on model ambiguity and revenue, respectively.
no code implementations • 6 Oct 2020 • Xiancheng Cheng, Prashant Khanduri, Boxiao Chen, Pramod K. Varshney
We propose two versions of compression design, one centralized where the compression strategies are derived at the FC and the other decentralized, where the local sensors compute their individual compression matrices independently.
