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ML
2012
ACM
413views Machine Learning» more  ML 2012»
14 years 1 months ago
Gradient-based boosting for statistical relational learning: The relational dependency network case
Dependency networks approximate a joint probability distribution over multiple random variables as a product of conditional distributions. Relational Dependency Networks (RDNs) are...
Sriraam Natarajan, Tushar Khot, Kristian Kersting,...
SASO
2009
IEEE
16 years 17 days ago
Controlling Particle Swarm Optimization with Learned Parameters
—Controlling particle swarm optimization is typically an unintuitive task, involving a process of adjusting low-level parameters of the system that often do not have obvious corr...
Kevin Winner, Don Miner, Marie desJardins
ICCAD
2008
IEEE
107views Hardware» more  ICCAD 2008»
16 years 8 days ago
Importance sampled circuit learning ensembles for robust analog IC design
This paper presents ISCLEs, a novel and robust analog design method that promises to scale with Moore’s Law, by doing boosting-style importance sampling on digital-sized circuit...
Peng Gao, Trent McConaghy, Georges G. E. Gielen
ICRA
2006
IEEE
177views Robotics» more  ICRA 2006»
15 years 12 months ago
Autonomous Shape Model Learning for Object Localization and Recognition
— Mobile robots do not adequately represent the objects in their environment; this weakness hinders a robot’s ability to utilize past experience. In this paper, we describe a s...
Joseph Modayil, Benjamin Kuipers
ICDAR
2005
IEEE
15 years 11 months ago
Language Identification of Character Images Using Machine Learning Techniques
In this paper, we propose a new approach for identifying the language type of character images. We do this by classifying individual character images to determine the language bou...
Ying-Ho Liu, Fu Chang, Chin-Chin Lin