Alternate Learning and Compression Approaching R(D)

Autor:	Zamir, Ram, Rose, Kenneth
Rok vydání:	2024
Předmět:	Computer Science - Information Theory
Druh dokumentu:	Working Paper
Popis:	The inherent trade-off in on-line learning is between exploration and exploitation. A good balance between these two (conflicting) goals can achieve a better long-term performance. Can we define an optimal balance? We propose to study this question through a backward-adaptive lossy compression system, which exhibits a "natural" trade-off between exploration and exploitation. Comment: This paper was presented as a poster in the workshop `Learn 2 Compress', in ISIT 2024, Athens, Greece, July 2024. It was processed and reviewed in the Open Review system
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2411.03054 Zobrazit plný text záznamu View this record from Arxiv