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» Simple Algorithms for a Weighted Interval Selection Problem
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99
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NAACL
2010
14 years 10 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 ...
101
Voted
ICML
2000
IEEE
16 years 1 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....
114
Voted
NIPS
1998
15 years 1 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
15 years 4 months 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...
102
Voted
CVPR
2008
IEEE
16 years 2 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