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An Improved Algorithm for Learning Drifting Discrete Distributions
March 11, 2024, 4:41 a.m. | Alessio Mazzetto
cs.LG updates on arXiv.org arxiv.org
Abstract: We present a new adaptive algorithm for learning discrete distributions under distribution drift. In this setting, we observe a sequence of independent samples from a discrete distribution that is changing over time, and the goal is to estimate the current distribution. Since we have access to only a single sample for each time step, a good estimation requires a careful choice of the number of past samples to use. To use more samples, we must …
abstract algorithm arxiv cs.lg current distribution drift independent observe samples stat.ml type
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