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» Stochastic complexity in learning
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ICMLA
2003
15 years 8 months ago
A Distributed Reinforcement Learning Approach to Pattern Inference in Go
— This paper shows that the distributed representation found in Learning Vector Quantization (LVQ) enables reinforcement learning methods to cope with a large decision search spa...
Myriam Abramson, Harry Wechsler
172
Voted
FUIN
2006
95views more  FUIN 2006»
15 years 6 months ago
Multistrategy Operators for Relational Learning and Their Cooperation
Traditional Machine Learning approaches based on single inference mechanisms have reached their limits. This causes the need for a framework that integrates approaches based on aba...
Floriana Esposito, Nicola Fanizzi, Stefano Ferilli...
CE
2007
99views more  CE 2007»
15 years 6 months ago
Self-organising navigational support in lifelong learning: How predecessors can lead the way
Increased flexibility and modularisation in higher education complicates the process of learners finding their way through the offerings of higher education institutions. In lifel...
José Janssen, Colin Tattersall, Wim Waterin...
ML
2008
ACM
15 years 6 months ago
Margin-based first-order rule learning
Abstract We present a new margin-based approach to first-order rule learning. The approach addresses many of the prominent challenges in first-order rule learning, such as the comp...
Ulrich Rückert, Stefan Kramer
JUCS
2007
84views more  JUCS 2007»
15 years 6 months ago
Formal Representations of Learning Scenarios: A Methodology to Configure E-Learning Systems
: Nowadays, advanced E-Learning systems are generally pedagogy-aware. Commonly, these systems include facilities for defining so-called learning scenarios that reflect sophisticate...
Denis Helic