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ICML
2004
IEEE
16 years 4 months ago
Convergence of synchronous reinforcement learning with linear function approximation
Synchronous reinforcement learning (RL) algorithms with linear function approximation are representable as inhomogeneous matrix iterations of a special form (Schoknecht & Merk...
Artur Merke, Ralf Schoknecht
ICML
1999
IEEE
16 years 4 months ago
Simple DFA are Polynomially Probably Exactly Learnable from Simple Examples
E cient learning of DFA is a challenging research problem in grammatical inference. Both exact and approximate (in the PAC sense) identi ability of DFA from examples is known to b...
Rajesh Parekh, Vasant Honavar
ICCAD
2002
IEEE
176views Hardware» more  ICCAD 2002»
16 years 27 days ago
High capacity and automatic functional extraction tool for industrial VLSI circuit designs
In this paper we present an advanced functional extraction tool for automatic generation of high-level RTL from switch-level circuit netlist representation. The tool is called FEV...
Sasha Novakovsky, Shy Shyman, Ziyad Hanna
CVPR
2010
IEEE
16 years 11 days ago
Efficient Additive Kernels via Explicit Feature Maps
Maji and Berg [13] have recently introduced an explicit feature map approximating the intersection kernel. This enables efficient learning methods for linear kernels to be applied...
Andrea Vedaldi, Andrew Zisserman
FOSSACS
2009
Springer
15 years 10 months ago
On Global Model Checking Trees Generated by Higher-Order Recursion Schemes
Higher-order recursion schemes are systems of rewrite rules on typed non-terminal symbols, which can be used to define infinite trees. The Global Modal Mu-Calculus Model Checking...
Christopher Broadbent, C.-H. Luke Ong