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ICML
2004
IEEE
16 years 4 months ago
Training conditional random fields via gradient tree boosting
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
Thomas G. Dietterich, Adam Ashenfelter, Yaroslav B...
INFOCOM
2008
IEEE
15 years 10 months ago
Iso-Contour Queries and Gradient Descent with Guaranteed Delivery in Sensor Networks
—We study the problem of data-driven routing and navigation in a distributed sensor network over a continuous scalar field. Specifically, we address the problem of searching fo...
Rik Sarkar, Xianjin Zhu, Jie Gao, Leonidas J. Guib...
ATAL
2008
Springer
15 years 6 months ago
MB-AIM-FSI: a model based framework for exploiting gradient ascent multiagent learners in strategic interactions
Future agent applications will increasingly represent human users autonomously or semi-autonomously in strategic interactions with similar entities. Hence, there is a growing need...
Doran Chakraborty, Sandip Sen
ASPDAC
2004
ACM
101views Hardware» more  ASPDAC 2004»
15 years 9 months ago
A sub-mW MPEG-4 motion estimation processor core for mobile video application
This paper describes a sub-mW motion estimation processor core for MPEG-4 video encoding. It features a Gradient Descent Search algorithm whose computation power is only 7% of the...
Yuki Kuroda, Junichi Miyakoshi, Masayuki Miyama, K...
NIPS
1998
15 years 5 months ago
Gradient Descent for General Reinforcement Learning
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
Leemon C. Baird III, Andrew W. Moore