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» Optimizing Generic Functions
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127
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ENTCS
2007
121views more  ENTCS 2007»
15 years 5 months ago
Incremental Parametric Development of Greedy Algorithms
The event B method provides a general framework for modelling both data structures and algorithms. B models are validated by discharging proof obligations ensuring safety properti...
Dominique Cansell, Dominique Méry
ICML
2010
IEEE
15 years 6 months ago
Toward Off-Policy Learning Control with Function Approximation
We present the first temporal-difference learning algorithm for off-policy control with unrestricted linear function approximation whose per-time-step complexity is linear in the ...
Hamid Reza Maei, Csaba Szepesvári, Shalabh ...
MP
1998
134views more  MP 1998»
15 years 4 months ago
Second-order global optimality conditions for convex composite optimization
In recent years second-order sufficient conditions of an isolated local minimizer for convex composite optimization problems have been established. In this paper, second-order opt...
Xiaoqi Yang
136
Voted
EC
2008
103views ECommerce» more  EC 2008»
15 years 5 months ago
A Graphical Model for Evolutionary Optimization
We present a statistical model of empirical optimization that admits the creation of algorithms with explicit and intuitively defined desiderata. Because No Free Lunch theorems di...
Christopher K. Monson, Kevin D. Seppi
MOBIHOC
2001
ACM
16 years 4 months ago
Localized algorithms in wireless ad-hoc networks: location discovery and sensor exposure
The development of practical, localized algorithms is probably the most needed and most challenging task in wireless ad-hoc sensor networks (WASNs). Localized algorithms are a spe...
Seapahn Meguerdichian, Sasha Slijepcevic, Vahag Ka...