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» Simple Algorithms for a Weighted Interval Selection Problem
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NAACL
2010
13 years 5 months ago
Bayesian Inference for Finite-State Transducers
We describe a Bayesian inference algorithm that can be used to train any cascade of weighted finite-state transducers on end-toend data. We also investigate the problem of automat...
David Chiang, Jonathan Graehl, Kevin Knight, Adam ...
ICML
2000
IEEE
14 years 8 months ago
Meta-Learning by Landmarking Various Learning Algorithms
Landmarking is a novel approach to describing tasks in meta-learning. Previous approaches to meta-learning mostly considered only statistics-inspired measures of the data as a sou...
Bernhard Pfahringer, Hilan Bensusan, Christophe G....
NIPS
1998
13 years 9 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
AMET
1998
Springer
14 years 17 hour ago
Bid Evaluation and Selection in the MAGNET Automated Contracting System
We present an approach to the bid-evaluation problem in a system for multi-agent contract negotiation, called MAGNET. The MAGNET market infrastructure provides support for a variet...
Erik S. Steinmetz, John Collins, Scott Jamison, Ra...
CVPR
2008
IEEE
14 years 9 months ago
Approximate earth mover's distance in linear time
The earth mover's distance (EMD) [16] is an important perceptually meaningful metric for comparing histograms, but it suffers from high (O(N3 log N)) computational complexity...
Sameer Shirdhonkar, David W. Jacobs