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» Functional Differentiation of Computer Programs
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CIG
2005
IEEE
16 years 3 days ago
Nannon: A Nano Backgammon for Machine Learning Research
A newly designed game is introduced, which feels like Backgammon, but has a simplified rule set. Unlike earlier attempts at simplifying the game, Nannon maintains enough features a...
Jordan B. Pollack
AI
2001
Springer
15 years 10 months ago
Learning about Constraints by Reflection
A system's constraints characterizes what that system can do. However, a dynamic environment may require that a system alter its constraints. If feedback about a specific situ...
J. William Murdock, Ashok K. Goel
CORR
2010
Springer
110views Education» more  CORR 2010»
15 years 6 months ago
Advanced Software Protection Now
We introduce a novel software-protection method, which can be fully implemented with today's technologies, that provides traitor tracing and license-enforcement functionalitie...
Diego Bendersky, Ariel Futoransky, Luciano Notarfr...
ICALP
2007
Springer
16 years 19 days ago
Unbounded-Error One-Way Classical and Quantum Communication Complexity
This paper studies the gap between classical one-way communication complexity C(f) and its quantum counterpart Q(f), under the unbounded-error setting, i.e., it is enough that the ...
Kazuo Iwama, Harumichi Nishimura, Rudy Raymond, Sh...
IJCNN
2006
IEEE
16 years 15 days ago
On derivation of stagewise second-order backpropagation by invariant imbedding for multi-stage neural-network learning
— We present a simple, intuitive argument based on “invariant imbedding” in the spirit of dynamic programming to derive a stagewise second-order backpropagation (BP) algorith...
Eiji Mizutani, Stuart Dreyfus