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ACL
2012
13 years 6 months ago
Unsupervised Morphology Rivals Supervised Morphology for Arabic MT
If unsupervised morphological analyzers could approach the effectiveness of supervised ones, they would be a very attractive choice for improving MT performance on low-resource in...
David Stallard, Jacob Devlin, Michael Kayser, Yoon...
138
Voted
ML
2000
ACM
15 years 3 months ago
Maximizing Theory Accuracy Through Selective Reinterpretation
Existing methods for exploiting awed domain theories depend on the use of a su ciently large set of training examples for diagnosing and repairing aws in the theory. In this paper,...
Shlomo Argamon-Engelson, Moshe Koppel, Hillel Walt...
ML
2007
ACM
156views Machine Learning» more  ML 2007»
15 years 3 months ago
Active learning for logistic regression: an evaluation
Which active learning methods can we expect to yield good performance in learning binary and multi-category logistic regression classifiers? Addressing this question is a natural ...
Andrew I. Schein, Lyle H. Ungar
171
Voted
TSE
2002
140views more  TSE 2002»
15 years 3 months ago
Test Case Prioritization: A Family of Empirical Studies
To reduce the cost of regression testing, software testers may prioritize their test cases so that those which are more important, by some measure, are run earlier in the regressi...
Sebastian G. Elbaum, Alexey G. Malishevsky, Gregg ...
ICML
2007
IEEE
16 years 4 months ago
An integrated approach to feature invention and model construction for drug activity prediction
We present a new machine learning approach for 3D-QSAR, the task of predicting binding affinities of molecules to target proteins based on 3D structure. Our approach predicts bind...
David Page, Jesse Davis, Soumya Ray, Vítor ...