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» Learning programming with Erlang
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KCAP
2009
ACM
14 years 4 months ago
Interactively shaping agents via human reinforcement: the TAMER framework
As computational learning agents move into domains that incur real costs (e.g., autonomous driving or financial investment), it will be necessary to learn good policies without n...
W. Bradley Knox, Peter Stone
ICML
2007
IEEE
14 years 11 months ago
Direct convex relaxations of sparse SVM
Although support vector machines (SVMs) for binary classification give rise to a decision rule that only relies on a subset of the training data points (support vectors), it will ...
Antoni B. Chan, Nuno Vasconcelos, Gert R. G. Lanck...
ECML
2007
Springer
14 years 4 months ago
Statistical Debugging Using Latent Topic Models
Abstract. Statistical debugging uses machine learning to model program failures and help identify root causes of bugs. We approach this task using a novel Delta-Latent-Dirichlet-Al...
David Andrzejewski, Anne Mulhern, Ben Liblit, Xiao...
ESOP
2007
Springer
14 years 4 months ago
A Rewriting Semantics for Type Inference
When students first learn programming, they often rely on a simple operational model of a program’s behavior to explain how particular features work. Because such models build o...
George Kuan, David MacQueen, Robert Bruce Findler
SIGCSE
2000
ACM
119views Education» more  SIGCSE 2000»
14 years 2 months ago
Bugs as features: teaching network protocols through debugging
Being exposed to well-written code is a valuable experience for students -- especially when the code is larger or more complex than they are currently capable of writing. In addit...
Brad Richards