596 search results - page 20 / 120 » Learning noise |
ALT
2001
Springer
14 years 1 months ago
2001
Springer
We develop a theory for learning scenarios where multiple learners co-exist but there are mutual compatibility constraints on their outcomes. This is natural in cognitive learning...
IDA
2007
Springer
13 years 8 months ago
2007
Springer
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize th...
COLT
2007
Springer
14 years 2 months ago
2007
Springer
This paper analyzes the potential advantages and theoretical challenges of “active learning” algorithms. Active learning involves sequential sampling procedures that use infor...
ICML
2006
IEEE
14 years 9 months ago
2006
IEEE
We state and analyze the first active learning algorithm which works in the presence of arbitrary forms of noise. The algorithm, A2 (for Agnostic Active), relies only upon the ass...
EACL
2006
ACL Anthology
13 years 10 months ago
2006
ACL Anthology
We present a model for sentence compression that uses a discriminative largemargin learning framework coupled with a novel feature set defined on compressed bigrams as well as dee...