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» Can Learning in the Limit Be Done Efficiently?
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ALT
2003
Springer
12 years 3 months ago
Can Learning in the Limit Be Done Efficiently?
Abstract. Inductive inference can be considered as one of the fundamental paradigms of algorithmic learning theory. We survey results recently obtained and show their impact to pot...
Thomas Zeugmann
EDM
2010
154views Data Mining» more  EDM 2010»
11 years 10 months ago
Can We Get Better Assessment From A Tutoring System Compared to Traditional Paper Testing? Can We Have Our Cake (Better Assessme
Dynamic assessment (DA) has been advocated as an interactive approach to conduct assessments to students in the learning systems as it can differentiate student proficiency at a fi...
Mingyu Feng, Neil T. Heffernan
ICANN
2009
Springer
12 years 3 months ago
Efficient Uncertainty Propagation for Reinforcement Learning with Limited Data
In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...
Alexander Hans, Steffen Udluft
NIPS
2001
12 years 1 months ago
Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms
The paper studies machine learning problems where each example is described using a set of Boolean features and where hypotheses are represented by linear threshold elements. One ...
Roni Khardon, Dan Roth, Rocco A. Servedio
SIGMETRICS
2002
ACM
159views Hardware» more  SIGMETRICS 2002»
11 years 11 months ago
Limits of wide-area thin-client computing
While many application service providers have proposed using thin-client computing to deliver computational services over the Internet, little work has been done to evaluate the e...
Albert M. Lai, Jason Nieh
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