Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: BAM: Bayes with Adaptive Memory   Online learning via Bayes' theorem allows new data to be continuously
integrated into an agent's current beliefs. However, a naive application of
Bayesian methods in non stationary environments leads to slow adaptation and
results in state estimates that may converge confidently to the wrong parameter
value. A common solution when learning in changing environments is to
discard/downweight past data; however, this simple mechanism of "forgetting"
fails to account for the fact that many real-world environments involve
revisiting similar states. We propose a new framework, Bayes with Adaptive
Memory (BAM), that takes advantage of past experience by allowing the agent to
choose which past observations to remember and which to forget. We demonstrate
that BAM generalizes many popular Bayesian update rules for non-stationary
environments. Through a variety of experiments, we demonstrate the ability of
BAM to continuously adapt in an ever-changing world.

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The categories of this paper are: mtrl-th
12
The categories of this paper are: nucl-th
36
The categories of this paper are: cmp-lg
30
The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat
23
The categories of this paper are: solv-int
17
The categories of this paper are: q-fin
9
The categories of this paper are: nlin
13
The categories of this paper are: quant-ph
18
The categories of this paper are: econ
33
The categories of this paper are: plasm-ph
2
The categories of this paper are: math
20
The categories of this paper are: acc-phys
5
The categories of this paper are: gr-qc
10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph