97,307 research outputs found
Making It to the Major Leagues: Career Movement between Library and Archival Professions and from Small College to Large University Libraries
published or submitted for publicatio
Grid infrastructures supporting paediatric endocrinology across Europe
Paediatric endocrinology is a highly specialised area of clinical medicine with many experts with specific knowledge distributed over a wide geographical area. The European Society for Paediatric Endocrinology (ESPE) is an example of such a body of experts that require regular collaboration and sharing of data and knowledge. This paper describes work, developed as a corollary to the VOTES project [1] and implementing similar architectures, to provide a data grid that allows information to be efficiently distributed between collaborating partners, and also allows wide-scale analyses to be run over the entire data-set, which necessarily involves crossing domain boundaries and negotiating data access between administrations that only trust each other to a limited degree
Neural Architecture Search using Deep Neural Networks and Monte Carlo Tree Search
Neural Architecture Search (NAS) has shown great success in automating the
design of neural networks, but the prohibitive amount of computations behind
current NAS methods requires further investigations in improving the sample
efficiency and the network evaluation cost to get better results in a shorter
time. In this paper, we present a novel scalable Monte Carlo Tree Search (MCTS)
based NAS agent, named AlphaX, to tackle these two aspects. AlphaX improves the
search efficiency by adaptively balancing the exploration and exploitation at
the state level, and by a Meta-Deep Neural Network (DNN) to predict network
accuracies for biasing the search toward a promising region. To amortize the
network evaluation cost, AlphaX accelerates MCTS rollouts with a distributed
design and reduces the number of epochs in evaluating a network by transfer
learning, which is guided with the tree structure in MCTS. In 12 GPU days and
1000 samples, AlphaX found an architecture that reaches 97.84\% top-1 accuracy
on CIFAR-10, and 75.5\% top-1 accuracy on ImageNet, exceeding SOTA NAS methods
in both the accuracy and sampling efficiency. Particularly, we also evaluate
AlphaX on NASBench-101, a large scale NAS dataset; AlphaX is 3x and 2.8x more
sample efficient than Random Search and Regularized Evolution in finding the
global optimum. Finally, we show the searched architecture improves a variety
of vision applications from Neural Style Transfer, to Image Captioning and
Object Detection.Comment: To appear in the Thirty-Fourth AAAI conference on Artificial
Intelligence (AAAI-2020
A General Analysis of the Convergence of ADMM
We provide a new proof of the linear convergence of the alternating direction
method of multipliers (ADMM) when one of the objective terms is strongly
convex. Our proof is based on a framework for analyzing optimization algorithms
introduced in Lessard et al. (2014), reducing algorithm convergence to
verifying the stability of a dynamical system. This approach generalizes a
number of existing results and obviates any assumptions about specific choices
of algorithm parameters. On a numerical example, we demonstrate that minimizing
the derived bound on the convergence rate provides a practical approach to
selecting algorithm parameters for particular ADMM instances. We complement our
upper bound by constructing a nearly-matching lower bound on the worst-case
rate of convergence.Comment: 10 pages, 6 figure
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Navigating the information landscape
Preprint of column segment to be published in Serials Librarian 61(3), 2011.This article explores the tension between the structures by which the library organises and presents information, and the ways in which students and researchers access, use and conceptualise knowledge. I suggest that while knowledge structures are vital to learning and research, an overemphasis on structurality is mistaken, and can lead to an inappropriately positivist approach which impedes the research mission. The article examines various metaphoric ways of negotiating meaning and navigating information structures, and of crossing the threshold of structuralit
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