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ICML
1998
IEEE
15 years 10 months ago
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions
This paper introduces a new algorithm, Q2, foroptimizingthe expected output ofamultiinput noisy continuous function. Q2 is designed to need only a few experiments, it avoids stron...
Andrew W. Moore, Jeff G. Schneider, Justin A. Boya...
ICDM
2009
IEEE
130views Data Mining» more  ICDM 2009»
15 years 4 months ago
Active Learning with Generalized Queries
—Active learning can actively select or construct examples to label to reduce the number of labeled examples needed for building accurate classifiers. However, previous works of...
Jun Du, Charles X. Ling
ICRA
2008
IEEE
206views Robotics» more  ICRA 2008»
15 years 4 months ago
Memory-based learning for visual odometry
Abstract— We present and examine a technique for estimating the ego-motion of a mobile robot using memory-based learning and a monocular camera. Unlike other approaches that rely...
Richard Roberts, Hai Nguyen, Niyant Krishnamurthi,...
EUROCAST
2007
Springer
182views Hardware» more  EUROCAST 2007»
15 years 4 months ago
A k-NN Based Perception Scheme for Reinforcement Learning
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
José Antonio Martin H., Javier de Lope Asia...
DGO
2008
126views Education» more  DGO 2008»
14 years 11 months ago
Active learning for e-rulemaking: public comment categorization
We address the e-rulemaking problem of reducing the manual labor required to analyze public comment sets. In current and previous work, for example, text categorization techniques...
Stephen Purpura, Claire Cardie, Jesse Simons