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» Learning Bounds for Domain Adaptation
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ICML
2005
IEEE
16 years 1 months ago
Using additive expert ensembles to cope with concept drift
We consider online learning where the target concept can change over time. Previous work on expert prediction algorithms has bounded the worst-case performance on any subsequence ...
Jeremy Z. Kolter, Marcus A. Maloof
IJCNN
2006
IEEE
15 years 6 months ago
Adaptation of Artificial Neural Networks Avoiding Catastrophic Forgetting
— In connectionist learning, one relevant problem is “catastrophic forgetting” that may occur when a network, trained with a large set of patterns, has to learn new input pat...
Dario Albesano, Roberto Gemello, Pietro Laface, Fr...
ECAI
2010
Springer
15 years 1 months ago
The Dynamics of Multi-Agent Reinforcement Learning
Abstract. Infinite-horizon multi-agent control processes with nondeterminism and partial state knowledge have particularly interesting properties with respect to adaptive control, ...
Luke Dickens, Krysia Broda, Alessandra Russo
115
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EMNLP
2007
15 years 2 months ago
A Discriminative Learning Model for Coordinate Conjunctions
We propose a sequence-alignment based method for detecting and disambiguating coordinate conjunctions. In this method, averaged perceptron learning is used to adapt the substituti...
Masashi Shimbo, Kazuo Hara
PGLDB
2003
166views Database» more  PGLDB 2003»
15 years 1 months ago
ROSA: A Data Model and Query Language for e-Learning Objects
Learning Content Management Systems (LCMS) supports e-learning applications with storage and efficient access for e-learning objects (LO)s. ROSA is a LCMS built as a semantic laye...
Fabio Porto, Ana Maria de Carvalho Moura, Adriana ...