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SDM
2012
SIAM
273views Data Mining» more  SDM 2012»
13 years 6 months ago
A Framework for the Evaluation and Management of Network Centrality
Network-analysis literature is rich in node-centrality measures that quantify the centrality of a node as a function of the (shortest) paths of the network that go through it. Exi...
Vatche Ishakian, Dóra Erdös, Evimaria ...
121
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SIAMJO
2008
74views more  SIAMJO 2008»
15 years 3 months ago
Lagrangian-Dual Functions and Moreau--Yosida Regularization
In this paper, we consider the Lagrangian dual problem of a class of convex optimization problems. We first discuss the semismoothness of the Lagrangian-dual function . This prope...
Fanwen Meng, Gongyun Zhao, Mark Goh, Robert de Sou...
STACS
2007
Springer
15 years 10 months ago
Pure Stationary Optimal Strategies in Markov Decision Processes
Markov decision processes (MDPs) are controllable discrete event systems with stochastic transitions. Performances of an MDP are evaluated by a payoff function. The controller of ...
Hugo Gimbert
JMLR
2010
121views more  JMLR 2010»
14 years 10 months ago
Sparse Semi-supervised Learning Using Conjugate Functions
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...
Shiliang Sun, John Shawe-Taylor
GECCO
2009
Springer
164views Optimization» more  GECCO 2009»
15 years 1 months ago
Solving iterated functions using genetic programming
An iterated function f(x) is a function that when composed with itself, produces a given expression f(f(x))=g(x). Iterated functions are essential constructs in fractal theory and...
Michael D. Schmidt, Hod Lipson