15,226 research outputs found
Distributed Nonconvex Multiagent Optimization Over Time-Varying Networks
We study nonconvex distributed optimization in multiagent networks where the
communications between nodes is modeled as a time-varying sequence of arbitrary
digraphs. We introduce a novel broadcast-based distributed algorithmic
framework for the (constrained) minimization of the sum of a smooth (possibly
nonconvex and nonseparable) function, i.e., the agents' sum-utility, plus a
convex (possibly nonsmooth and nonseparable) regularizer. The latter is usually
employed to enforce some structure in the solution, typically sparsity. The
proposed method hinges on Successive Convex Approximation (SCA) techniques
coupled with i) a tracking mechanism instrumental to locally estimate the
gradients of agents' cost functions; and ii) a novel broadcast protocol to
disseminate information and distribute the computation among the agents.
Asymptotic convergence to stationary solutions is established. A key feature of
the proposed algorithm is that it neither requires the double-stochasticity of
the consensus matrices (but only column stochasticity) nor the knowledge of the
graph sequence to implement. To the best of our knowledge, the proposed
framework is the first broadcast-based distributed algorithm for convex and
nonconvex constrained optimization over arbitrary, time-varying digraphs.
Numerical results show that our algorithm outperforms current schemes on both
convex and nonconvex problems.Comment: Copyright 2001 SS&C. Published in the Proceedings of the 50th annual
Asilomar conference on signals, systems, and computers, Nov. 6-9, 2016, CA,
US
An Algebraic-Coding Equivalence to the Maximum Distance Separable Conjecture
We formulate an Algebraic-Coding Equivalence to the Maximum Distance
Separable Conjecture. Specifically, we present novel proofs of the following
equivalent statements. Let be a fixed pair of integers satisfying
is a prime power and . We denote by the vector
space of functions from a finite field to itself, which can be
represented as the space of
polynomial functions. We denote by the
set of polynomials that are either the zero polynomial, or have at most
distinct roots in . Given two subspaces of ,
we denote by their span. We prove that the following are
equivalent.
[A] Suppose that either: 1. is odd 2. is even and .
Then there do not exist distinct subspaces and of
such that:
3. 4. . 5. 6. 7.
.
[B] Suppose is odd, or, if is even, . There is
no integer with such that the Reed-Solomon code
over of dimension can have columns
added to it, such that:
8. Any submatrix of containing
the first columns of is independent. 9. is independent.
[C] The MDS conjecture is true for the given .Comment: This is version: 5.6.18. arXiv admin note: substantial text overlap
with arXiv:1611.0235
Modeling spatial social complex networks for dynamical processes
The study of social networks --- where people are located, geographically,
and how they might be connected to one another --- is a current hot topic of
interest, because of its immediate relevance to important applications, from
devising efficient immunization techniques for the arrest of epidemics, to the
design of better transportation and city planning paradigms, to the
understanding of how rumors and opinions spread and take shape over time. We
develop a spatial social complex network (SSCN) model that captures not only
essential connectivity features of real-life social networks, including a
heavy-tailed degree distribution and high clustering, but also the spatial
location of individuals, reproducing Zipf's law for the distribution of city
populations as well as other observed hallmarks. We then simulate Milgram's
Small-World experiment on our SSCN model, obtaining good qualitative agreement
with the known results and shedding light on the role played by various network
attributes and the strategies used by the players in the game. This
demonstrates the potential of the SSCN model for the simulation and study of
the many social processes mentioned above, where both connectivity and
geography play a role in the dynamics.Comment: 10 pages, 6 figure
Adaptive Semi-supervised Learning for Cross-domain Sentiment Classification
We consider the cross-domain sentiment classification problem, where a
sentiment classifier is to be learned from a source domain and to be
generalized to a target domain. Our approach explicitly minimizes the distance
between the source and the target instances in an embedded feature space. With
the difference between source and target minimized, we then exploit additional
information from the target domain by consolidating the idea of semi-supervised
learning, for which, we jointly employ two regularizations -- entropy
minimization and self-ensemble bootstrapping -- to incorporate the unlabeled
target data for classifier refinement. Our experimental results demonstrate
that the proposed approach can better leverage unlabeled data from the target
domain and achieve substantial improvements over baseline methods in various
experimental settings.Comment: Accepted to EMNLP201
Density-dependent synthetic magnetism for ultracold atoms in optical lattices
Raman-assisted hopping can allow for the creation of density-dependent
synthetic magnetism for cold neutral gases in optical lattices. We show that
the density-dependent fields lead to a non-trivial interplay between density
modulations and chirality. This interplay results in a rich physics for atoms
in two-leg ladders, characterized by a density-driven Meissner- to
vortex-superfluid transition, and a non-trivial dependence of the density
imbalance between the legs. Density-dependent fields also lead to intriguing
physics in square lattices. In particular, it leads to a density-driven
transition between a non-chiral and a chiral superfluid, both characterized by
non-trivial charge density-wave amplitude. We finally show how the physics due
to the density-dependent fields may be easily probed in experiments by
monitoring the expansion of doublons and holes in a Mott insulator, which
presents a remarkable dependence on quantum fluctuations.Comment: 5 pages, 4 figure
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