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» Approximate Learning of Dynamic Models
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AAAI
2008
15 years 9 months ago
Learning to Analyze Binary Computer Code
We present a novel application of structured classification: identifying function entry points (FEPs, the starting byte of each function) in program binaries. Such identification ...
Nathan E. Rosenblum, Xiaojin Zhu, Barton P. Miller...
190
Voted
ICAC
2006
IEEE
16 years 1 months ago
A Hybrid Reinforcement Learning Approach to Autonomic Resource Allocation
— Reinforcement Learning (RL) provides a promising new approach to systems performance management that differs radically from standard queuing-theoretic approaches making use of ...
Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mo...
IJCNN
2007
IEEE
16 years 1 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
191
Voted
HYBRID
2003
Springer
16 years 6 days ago
Mode Reconstruction for Source Coding and Multi-modal Control
s of Invited Presentations The Mathematics of Matter and the Mathematics of Mind . . . . . . . . . . . . . 1 David Berlinski A Grand Challenge: Full Reactive Modeling of a Multi-ce...
Adam Austin, Magnus Egerstedt
ECML
2007
Springer
16 years 1 months ago
Dual Strategy Active Learning
Abstract. Active Learning methods rely on static strategies for sampling unlabeled point(s). These strategies range from uncertainty sampling and density estimation to multi-factor...
Pinar Donmez, Jaime G. Carbonell, Paul N. Bennett