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» Approximation Algorithms for Free-Label Maximization
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ATAL
2010
Springer
13 years 9 months ago
Closing the learning-planning loop with predictive state representations
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon
BMCBI
2008
153views more  BMCBI 2008»
13 years 8 months ago
Estimating the size of the solution space of metabolic networks
Background: Cellular metabolism is one of the most investigated system of biological interactions. While the topological nature of individual reactions and pathways in the network...
Alfredo Braunstein, Roberto Mulet, Andrea Pagnani
ICMCS
2006
IEEE
192views Multimedia» more  ICMCS 2006»
14 years 2 months ago
Classifier Optimization for Multimedia Semantic Concept Detection
In this paper, we present an AUC (i.e., the Area Under the Curve of Receiver Operating Characteristics (ROC)) maximization based learning algorithm to design the classifier for ma...
Sheng Gao, Qibin Sun
CORR
2008
Springer
127views Education» more  CORR 2008»
13 years 8 months ago
MAPEL: Achieving Global Optimality for a Non-convex Wireless Power Control Problem
Achieving weighted throughput maximization (WTM) through power control has been a long standing open problem in interference-limited wireless networks. The complicated coupling bet...
Liping Qian, Ying Jun Zhang, Jianwei Huang
TAMC
2009
Springer
14 years 3 months ago
A Simple Greedy Algorithm for the k-Disjoint Flow Problem
In classical network flow theory the choice of paths, on which flow is sent, is only restricted by arc capacities. This, however, is not realistic in most applications. Many prob...
Maren Martens