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» Reinforcement Learning with the Use of Costly Features
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JMLR
2011
148views more  JMLR 2011»
13 years 2 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara
WSC
2007
13 years 10 months ago
Simulation of adaptive project management analytics
Typically, IT projects are delivered over-budget and behind schedule. In this paper, we explore the effects of common project management practices that contribute to these problem...
Léa Amandine Deleris, Sugato Bagchi, Shubir...
GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
13 years 9 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
TEI
2010
ACM
160views Hardware» more  TEI 2010»
14 years 2 months ago
Think globally, build locally: a technological platform for low-cost, open-source, locally-assembled programmable bricks for edu
“Programmable bricks” are microcontroller-based devices that can be used in various educational projects, such as robotic prototypes, environmental sensing, and interactive ar...
Arnan Sipitakiat, Paulo Blikstein
AIPRF
2008
13 years 9 months ago
Spam Sender Detection with Classification Modeling on Highly Imbalanced Mail Server Behavior Data
Unsolicited commercial or bulk emails or emails containing viruses pose a great threat to the utility of email communications. A recent solution for filtering is reputation systems...
Yuchun Tang, Sven Krasser, Dmitri Alperovitch, Pau...