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ICML
1994
IEEE
13 years 11 months ago
Combining Top-down and Bottom-up Techniques in Inductive Logic Programming
This paper describes a new methodfor inducing logic programs from examples which attempts to integrate the best aspects of existingILP methodsintoa singlecoherent framework. In pa...
John M. Zelle, Raymond J. Mooney, Joshua B. Konvis...
CORR
2010
Springer
136views Education» more  CORR 2010»
13 years 8 months ago
On the Implementation of the Probabilistic Logic Programming Language ProbLog
The past few years have seen a surge of interest in the field of probabilistic logic learning and statistical relational learning. In this endeavor, many probabilistic logics have...
Angelika Kimmig, Bart Demoen, Luc De Raedt, V&iacu...
ISCA
1997
IEEE
137views Hardware» more  ISCA 1997»
14 years 6 days ago
A Language for Describing Predictors and Its Application to Automatic Synthesis
As processor architectures have increased their reliance on speculative execution to improve performance, the importance of accurate prediction of what to execute speculatively ha...
Joel S. Emer, Nicholas C. Gloy
MP
2010
135views more  MP 2010»
13 years 6 months ago
An inexact Newton method for nonconvex equality constrained optimization
Abstract We present a matrix-free line search algorithm for large-scale equality constrained optimization that allows for inexact step computations. For sufficiently convex problem...
Richard H. Byrd, Frank E. Curtis, Jorge Nocedal
IJCAI
2001
13 years 9 months ago
Neural Logic Network Learning using Genetic Programming
Neural Logic Network or Neulonet is a hybrid of neural network expert systems. Its strength lies in its ability to learn and to represent human logic in decision making using comp...
Chew Lim Tan, Henry Wai Kit Chia