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VLSID
2005
IEEE
105views VLSI» more  VLSID 2005»
13 years 10 months ago
Placement and Routing for 3D-FPGAs Using Reinforcement Learning and Support Vector Machines
The primary advantage of using 3D-FPGA over 2D-FPGA is that the vertical stacking of active layers reduce the Manhattan distance between the components in 3D-FPGA than when placed...
R. Manimegalai, E. Siva Soumya, V. Muralidharan, B...
ESANN
2003
13 years 6 months ago
Improving iterative repair strategies for scheduling with the SVM
The resource constraint project scheduling problem (RCPSP) is an NP-hard benchmark problem in scheduling which takes into account the limitation of resources’ availabilities in ...
Kai Gersmann, Barbara Hammer
ECML
2004
Springer
13 years 10 months ago
Experiments in Value Function Approximation with Sparse Support Vector Regression
Abstract. We present first experiments using Support Vector Regression as function approximator for an on-line, sarsa-like reinforcement learner. To overcome the batch nature of S...
Tobias Jung, Thomas Uthmann
ICML
2005
IEEE
14 years 5 months ago
Dynamic preferences in multi-criteria reinforcement learning
The current framework of reinforcement learning is based on maximizing the expected returns based on scalar rewards. But in many real world situations, tradeoffs must be made amon...
Sriraam Natarajan, Prasad Tadepalli
NCA
2010
IEEE
13 years 3 months ago
Genetic algorithm-based training for semi-supervised SVM
The Support Vector Machine (SVM) is an interesting classifier with excellent power of generalization. In this paper, we consider applying the SVM to semi-supervised learning. We p...
Mathias M. Adankon, Mohamed Cheriet