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NIPS
2001
15 years 8 months ago
Linking Motor Learning to Function Approximation: Learning in an Unlearnable Force Field
Reaching movements require the brain to generate motor commands that rely on an internal model of the task's dynamics. Here we consider the errors that subjects make early in...
O. Donchin, Reza Shadmehr
ICDM
2006
IEEE
164views Data Mining» more  ICDM 2006»
16 years 21 days ago
Unsupervised Learning of Tree Alignment Models for Information Extraction
We propose an algorithm for extracting fields from HTML search results. The output of the algorithm is a database table– a data structure that better lends itself to high-level...
Philip Zigoris, Damian Eads, Yi Zhang
IWCLS
2007
Springer
16 years 24 days ago
On Lookahead and Latent Learning in Simple LCS
Learning Classifier Systems use evolutionary algorithms to facilitate rule- discovery, where rule fitness is traditionally payoff based and assigned under a sharing scheme. Most c...
Larry Bull
EMNLP
2004
15 years 8 months ago
Active Learning and the Total Cost of Annotation
Active learning (AL) promises to reduce the cost of annotating labeled datasets for trainable human language technologies. Contrary to expectations, when creating labeled training...
Jason Baldridge, Miles Osborne
CHI
2009
ACM
16 years 7 months ago
Why and why not explanations improve the intelligibility of context-aware intelligent systems
Context-aware intelligent systems employ implicit inputs, and make decisions based on complex rules and machine learning models that are rarely clear to users. Such lack of system...
Brian Y. Lim, Anind K. Dey, Daniel Avrahami