Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning by random walks in the weight space of the Ising perceptron   Several variants of a stochastic local search process for constructing the
synaptic weights of an Ising perceptron are studied. In this process, binary
patterns are sequentially presented to the Ising perceptron and are then
learned as the synaptic weight configuration is modified through a chain of
single- or double-weight flips within the compatible weight configuration space
of the earlier learned patterns. This process is able to reach a storage
capacity of $\alpha \approx 0.63$ for pattern length N = 101 and $\alpha
\approx 0.41$ for N = 1001. If in addition a relearning process is exploited,
the learning performance is further improved to a storage capacity of $\alpha
\approx 0.80$ for N = 101 and $\alpha \approx 0.42$ for N=1001. We found that,
for a given learning task, the solutions constructed by the random walk
learning process are separated by a typical Hamming distance, which decreases
with the constraint density $\alpha$ of the learning task; at a fixed value of
$\alpha$, the width of the Hamming distance distributions decreases with $N$.

27
The categories of this paper are: comp-gas
21
The categories of this paper are: adap-org
14
The categories of this paper are: math-ph
7
The categories of this paper are: hep-th
30
The categories of this paper are: q-alg
28
The categories of this paper are: alg-geom
36
The categories of this paper are: cmp-lg
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph
22
The categories of this paper are: chao-dyn
25
The categories of this paper are: patt-sol
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
8
The categories of this paper are: hep-ex
16
The categories of this paper are: stat
23
The categories of this paper are: solv-int