Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Per-Block-Convex Data Modeling by Accelerated Stochastic Approximation   Applications involving dictionary learning, non-negative matrix
factorization, subspace clustering, and parallel factor tensor decomposition
tasks motivate well algorithms for per-block-convex and non-smooth optimization
problems. By leveraging the stochastic approximation paradigm and first-order
acceleration schemes, this paper develops an online and modular learning
algorithm for a large class of non-convex data models, where convexity is
manifested only per-block of variables whenever the rest of them are held
fixed. The advocated algorithm incurs computational complexity that scales
linearly with the number of unknowns. Under minimal assumptions on the cost
functions of the composite optimization task, without bounding constraints on
the optimization variables, or any explicit information on bounds of Lipschitz
coefficients, the expected cost evaluated online at the resultant iterates is
provably convergent with quadratic rate to an accumulation point of the
(per-block) minima, while subgradients of the expected cost asymptotically
vanish in the mean-squared sense. The merits of the general approach are
demonstrated in two online learning setups: (i) Robust linear regression using
a sparsity-cognizant total least-squares criterion; and (ii) semi-supervised
dictionary learning for network-wide link load tracking and imputation with
missing entries. Numerical tests on synthetic and real data highlight the
potential of the proposed framework for streaming data analytics by
demonstrating superior performance over block coordinate descent, and reduced
complexity relative to the popular alternating-direction method of multipliers.

10
The categories of this paper are: q-bio
18
The categories of this paper are: econ
34
The categories of this paper are: chem-ph
25
The categories of this paper are: patt-sol
11
The categories of this paper are: hep-lat
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
24
The categories of this paper are: dg-ga
23
The categories of this paper are: solv-int
4
The categories of this paper are: cond-mat
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The categories of this paper are: nlin
17
The categories of this paper are: q-fin
13
The categories of this paper are: quant-ph
29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th
32
The categories of this paper are: atom-ph