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IJACTAICIT
2010
163views more  IJACTAICIT 2010»
13 years 7 months ago
Modified Vector Field Histogram with a Neural Network Learning Model for Mobile Robot Path Planning and Obstacle Avoidance
In this work, a Modified Vector Field Histogram (MVFH) has been developed to improve path planning and obstacle avoidance for a wheeled driven mobile robot. It permits the detecti...
Bahaa I. Kazem, Ali H. Hamad, Mustafa M. Mozael
COLING
2010
13 years 4 months ago
Boosting Relation Extraction with Limited Closed-World Knowledge
This paper presents a new approach to improving relation extraction based on minimally supervised learning. By adding some limited closed-world knowledge for confidence estimation...
Feiyu Xu, Hans Uszkoreit, Sebastian Krause, Hong L...
ICML
2009
IEEE
14 years 10 months ago
Structure learning of Bayesian networks using constraints
This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
Cassio Polpo de Campos, Zhi Zeng, Qiang Ji
PAKDD
2004
ACM
96views Data Mining» more  PAKDD 2004»
14 years 3 months ago
Spectral Energy Minimization for Semi-supervised Learning
The use of unlabeled data to aid classification is important as labeled data is often available in limited quantity. Instead of utilizing training samples directly into semi-super...
Chun Hung Li, Zhi-Li Wu
AAAI
1994
13 years 11 months ago
Small is Beautiful: A Brute-Force Approach to Learning First-Order Formulas
We describe a method for learning formulas in firstorder logic using a brute-force, smallest-first search. The method is exceedingly simple. It generates all irreducible well-form...
Steven Minton, Ian Underwood