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» Learning to Solve QBF
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156
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IUI
2009
ACM
16 years 16 days ago
What were you thinking?: filling in missing dataflow through inference in learning from demonstration
Recent years have seen a resurgence of interest in programming by demonstration. As end users have become increasingly sophisticated, computer and artificial intelligence technolo...
Melinda T. Gervasio, Janet L. Murdock
163
Voted
KSEM
2009
Springer
15 years 10 months ago
A Competitive Learning Approach to Instance Selection for Support Vector Machines
Abstract. Support Vector Machines (SVM) have been applied successfully in a wide variety of fields in the last decade. The SVM problem is formulated as a convex objective function...
Mario Zechner, Michael Granitzer
139
Voted
NIPS
1998
15 years 5 months ago
Risk Sensitive Reinforcement Learning
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
Ralph Neuneier, Oliver Mihatsch
129
Voted
CE
2008
128views more  CE 2008»
15 years 3 months ago
Beyond threaded discussion: Representational guidance in asynchronous collaborative learning environments
Although most online learning environments are predominately text based, researchers have argued that representational support for the conceptual structure of a problem would addr...
Daniel D. Suthers, Ravi K. Vatrapu, Richard Medina...
130
Voted
AI
2000
Springer
15 years 3 months ago
Learning to construct knowledge bases from the World Wide Web
The World Wide Web is a vast source of information accessible to computers, but understandable only to humans. The goal of the research described here is to automatically create a...
Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew M...