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CORR
2000
Springer
120views Education» more  CORR 2000»
14 years 11 months ago
Scaling Up Inductive Logic Programming by Learning from Interpretations
When comparing inductive logic programming (ILP) and attribute-value learning techniques, there is a trade-off between expressive power and efficiency. Inductive logic programming ...
Hendrik Blockeel, Luc De Raedt, Nico Jacobs, Bart ...
OSDI
2008
ACM
16 years 14 hour ago
From Optimization to Regret Minimization and Back Again
Internet routing is mostly based on static information-it's dynamicity is limited to reacting to changes in topology. Adaptive performance-based routing decisions would not o...
Ioannis C. Avramopoulos, Jennifer Rexford, Robert ...
TSMC
2002
136views more  TSMC 2002»
14 years 11 months ago
Expertness based cooperative Q-learning
By using other agents' experiences and knowledge, a learning agent may learn faster, make fewer mistakes, and create some rules for unseen situations. These benefits would be ...
Majid Nili Ahmadabadi, Masoud Asadpour
ICCV
2007
IEEE
15 years 6 months ago
Co-Tracking Using Semi-Supervised Support Vector Machines
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
Feng Tang, Shane Brennan, Qi Zhao, Hai Tao
PROMISE
2010
14 years 6 months ago
On the value of learning from defect dense components for software defect prediction
BACKGROUND: Defect predictors learned from static code measures can isolate code modules with a higher than usual probability of defects. AIMS: To improve those learners by focusi...
Hongyu Zhang, Adam Nelson, Tim Menzies