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» Minimization of an M-convex Function
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ICML
2007
IEEE
14 years 8 months ago
Tracking value function dynamics to improve reinforcement learning with piecewise linear function approximation
Reinforcement learning algorithms can become unstable when combined with linear function approximation. Algorithms that minimize the mean-square Bellman error are guaranteed to co...
Chee Wee Phua, Robert Fitch
ISCAS
2006
IEEE
119views Hardware» more  ISCAS 2006»
14 years 1 months ago
Finite state machine state assignment for area and power minimization
— In this paper, we address the problem of FSM state assignment to minimize area and power. The objectives are targeted as single/independent as well as multi-objective optimizat...
Aiman H. El-Maleh, Sadiq M. Sait, F. Nawaz Khan
MOR
2010
120views more  MOR 2010»
13 years 6 months ago
Proximal Alternating Minimization and Projection Methods for Nonconvex Problems: An Approach Based on the Kurdyka-Lojasiewicz In
We study the convergence properties of an alternating proximal minimization algorithm for nonconvex structured functions of the type: L(x, y) = f(x)+Q(x, y)+g(y), where f : Rn → ...
Hedy Attouch, Jérôme Bolte, Patrick R...
TMC
2011
127views more  TMC 2011»
13 years 2 months ago
Discriminant Minimization Search for Large-Scale RF-Based Localization Systems
— In large-scale fingerprinting localization systems, fine-grained location estimation and quick location determination are conflicting concerns. To achieve finer-grained loc...
Sheng-Po Kuo, Yu-Chee Tseng
ISPD
1999
ACM
127views Hardware» more  ISPD 1999»
14 years 6 days ago
Buffer insertion for clock delay and skew minimization
 Buffer insertion is an effective approach to achieve both minimal clock signal delay and skew in high speed VLSI circuit design. In this paper, we develop an optimal buffer ins...
X. Zeng, D. Zhou, Wei Li