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» Evaluating algorithms that learn from data streams
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NIPS
2007
15 years 8 months ago
A Constraint Generation Approach to Learning Stable Linear Dynamical Systems
Stability is a desirable characteristic for linear dynamical systems, but it is often ignored by algorithms that learn these systems from data. We propose a novel method for learn...
Sajid M. Siddiqi, Byron Boots, Geoffrey J. Gordon
UAI
1996
15 years 8 months ago
Learning Equivalence Classes of Bayesian Network Structures
Two Bayesian-network structures are said to be equivalent if the set of distributions that can be represented with one of those structures is identical to the set of distributions...
David Maxwell Chickering
EWCBR
2004
Springer
16 years 7 days ago
Learning Feature Taxonomies for Case Indexing
Taxonomic case retrieval systems significantly outperform standard conversational case retrieval systems. However, their feature taxonomies, which are the principal reason for thei...
Kalyan Moy Gupta, David W. Aha, Philip G. Moore
ACL
2011
14 years 10 months ago
Automated Whole Sentence Grammar Correction Using a Noisy Channel Model
Automated grammar correction techniques have seen improvement over the years, but there is still much room for increased performance. Current correction techniques mainly focus on...
Y. Albert Park, Roger Levy
ICDM
2009
IEEE
137views Data Mining» more  ICDM 2009»
16 years 1 months ago
Set-Based Boosting for Instance-Level Transfer
—The success of transfer to improve learning on a target task is highly dependent on the selected source data. Instance-based transfer methods reuse data from the source tasks to...
Eric Eaton, Marie desJardins