Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Computationally Efficient Estimation of the Spectral Gap of a Markov
  Chain   We consider the problem of estimating from sample paths the absolute spectral
gap $\gamma_*$ of a reversible, irreducible and aperiodic Markov chain
$(X_t)_{t \in \mathbb{N}}$ over a finite state space $\Omega$. We propose the
${\tt UCPI}$ (Upper Confidence Power Iteration) algorithm for this problem, a
low-complexity algorithm which estimates the spectral gap in time ${\cal O}(n)$
and memory space ${\cal O}((\ln n)^2)$ given $n$ samples. This is in stark
contrast with most known methods which require at least memory space ${\cal
O}(|\Omega|)$, so that they cannot be applied to large state spaces.
Furthermore, ${\tt UCPI}$ is amenable to parallel implementation.

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The categories of this paper are: physics
18
The categories of this paper are: econ
12
The categories of this paper are: nucl-th
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The categories of this paper are: supr-con
19
The categories of this paper are: eess
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The categories of this paper are: dg-ga
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The categories of this paper are: alg-geom
29
The categories of this paper are: funct-an
15
The categories of this paper are: nucl-ex
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The categories of this paper are: q-fin
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The categories of this paper are: plasm-ph
20
The categories of this paper are: acc-phys
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The categories of this paper are: gr-qc
35
The categories of this paper are: mtrl-th
23
The categories of this paper are: solv-int
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The categories of this paper are: math