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118
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ICCBR
2010
Springer
15 years 6 months ago
Reducing the Memory Footprint of Temporal Difference Learning over Finitely Many States by Using Case-Based Generalization
In this paper we present an approach for reducing the memory footprint requirement of temporal difference methods in which the set of states is finite. We use case-based generaliza...
Matt Dilts, Héctor Muñoz-Avila
103
Voted
WIA
1999
Springer
15 years 7 months ago
Animation of the Generation and Computation of Finite Automata for Learning Software
Abstract. In computer science methods to aid learning are very imporcause abstract models are used frequently. For this conventional teaching methods do not suffice. We have develo...
Beatrix Braune, Stephan Diehl, Andreas Kerren, Rei...
103
Voted
ALT
2009
Springer
15 years 11 months ago
Learning Finite Automata Using Label Queries
We consider the problem of learning a finite automaton M of n states with input alphabet X and output alphabet Y when a teacher has helpfully or randomly labeled the states of M u...
Dana Angluin, Leonor Becerra-Bonache, Adrian Horia...
102
Voted
AMAI
2004
Springer
15 years 8 months ago
Learning via Finitely Many Queries
This work introduces a new query inference model that can access data and communicate with a teacher by asking finitely many boolean queries in a language L. In this model the pa...
Andrew C. Lee
205
Voted
COLT
2010
Springer
15 years 24 days ago
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
We present a new family of subgradient methods that dynamically incorporate knowledge of the geometry of the data observed in earlier iterations to perform more informative gradie...
John Duchi, Elad Hazan, Yoram Singer