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ICML
2004
IEEE
14 years 8 months ago
Learning random walk models for inducing word dependency distributions
Many NLP tasks rely on accurately estimating word dependency probabilities P(w1|w2), where the words w1 and w2 have a particular relationship (such as verb-object). Because of the...
Kristina Toutanova, Christopher D. Manning, Andrew...
UAI
1996
13 years 8 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon
CP
2004
Springer
14 years 28 days ago
Leveraging the Learning Power of Examples in Automated Constraint Acquisition
Constraint programming is rapidly becoming the technology of choice for modeling and solving complex combinatorial problems. However, users of constraint programming technology nee...
Christian Bessière, Remi Coletta, Eugene C....
ICALT
2008
IEEE
14 years 2 months ago
NUCLEO: Adaptive Computer Supported Collaborative Learning in a Role Game Based Scenario
This paper presents the adaptation model used in NUCLEO, a pilot e-learning environment that is currently being developed at the Complutense University of Madrid. The NUCLEO syste...
Pilar Sancho, Rubén Fuentes-Fernánde...
ML
2002
ACM
114views Machine Learning» more  ML 2002»
13 years 7 months ago
Building a Basic Block Instruction Scheduler with Reinforcement Learning and Rollouts
The execution order of a block of computer instructions on a pipelined machine can make a difference in running time by a factor of two or more. Compilers use heuristic schedulers...
Amy McGovern, J. Eliot B. Moss, Andrew G. Barto