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» Machine Learning by Function Decomposition
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ICML
2007
IEEE
16 years 2 months ago
Approximate maximum margin algorithms with rules controlled by the number of mistakes
We present a family of incremental Perceptron-like algorithms (PLAs) with margin in which both the "effective" learning rate, defined as the ratio of the learning rate t...
Petroula Tsampouka, John Shawe-Taylor
ML
2006
ACM
15 years 1 months ago
Relational IBL in classical music
It is well known that many hard tasks considered in machine learning and data mining can be solved in a rather simple and robust way with an instanceand distance-based approach. In...
Asmir Tobudic, Gerhard Widmer
ICML
2007
IEEE
16 years 2 months ago
Analyzing feature generation for value-function approximation
We analyze a simple, Bellman-error-based approach to generating basis functions for valuefunction approximation. We show that it generates orthogonal basis functions that provably...
Ronald Parr, Christopher Painter-Wakefield, Lihong...
ICML
1990
IEEE
15 years 5 months ago
Average Case Analysis of Conjunctive Learning Algorithms
We present an approach to modeling the average case behavior of learning algorithms. Our motivation is to predict the expected accuracy of learning algorithms as a function of the...
Michael J. Pazzani, Wendy Sarrett
ECTEL
2006
Springer
15 years 5 months ago
Language Technology for eLearning
Abstract. Given the huge amount of static and dynamic content created for eLearning tasks, the major challenge for extending their use is to improve the effectiveness of retrieval ...
Paola Monachesi, Lothar Lemnitzer, Kiril Ivanov Si...