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EUROCOLT
1997
Springer
15 years 1 months ago
Vapnik-Chervonenkis Dimension of Recurrent Neural Networks
Most of the work on the Vapnik-Chervonenkis dimension of neural networks has been focused on feedforward networks. However, recurrent networks are also widely used in learning app...
Pascal Koiran, Eduardo D. Sontag
HOTOS
1993
IEEE
15 years 1 months ago
Object Groups May Be Better Than Pages
I argue against trying to solve the problem of clustering objects into disk pages. Instead, I propose that objects be fetched in groups that may be specific to an application or ...
Mark Day
EURODAC
1994
IEEE
127views VHDL» more  EURODAC 1994»
15 years 1 months ago
Optimal equivalent circuits for interconnect delay calculations using moments
In performance-driven interconnect design, delay estimators are used to determine both the topology and the layout of good routing trees. We address the class of moment-matching, ...
Sudhakar Muddu, Andrew B. Kahng
STOC
2010
ACM
224views Algorithms» more  STOC 2010»
15 years 1 months ago
Satisfiability Allows No Nontrivial Sparsification Unless The Polynomial-Time Hierarchy Collapses
Consider the following two-player communication process to decide a language L: The first player holds the entire input x but is polynomially bounded; the second player is computa...
Holger Dell and Dieter van Melkebeek
COLT
1993
Springer
15 years 1 months ago
Bounding the Vapnik-Chervonenkis Dimension of Concept Classes Parameterized by Real Numbers
The Vapnik-Chervonenkis (V-C) dimension is an important combinatorial tool in the analysis of learning problems in the PAC framework. For polynomial learnability, we seek upper bou...
Paul W. Goldberg, Mark Jerrum
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