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ECML
2003
Springer
15 years 11 months ago
Support Vector Machines with Example Dependent Costs
Abstract. Classical learning algorithms from the fields of artificial neural networks and machine learning, typically, do not take any costs into account or allow only costs depe...
Ulf Brefeld, Peter Geibel, Fritz Wysotzki
NIPS
1996
15 years 7 months ago
Why did TD-Gammon Work?
Although TD-Gammon is one of the major successes in machine learning, it has not led to similar impressive breakthroughs in temporal difference learning for other applications or ...
Jordan B. Pollack, Alan D. Blair
AIIA
2001
Springer
15 years 10 months ago
A Knowledge-Based Neurocomputing Approach to Extract Refined Linguistic Rules from Data
– This paper proposes a knowledge-based neurocomputing approach to extract and refine a set of linguistic rules from data. A neural network is designed along with its learning al...
Giovanna Castellano, Anna Maria Fanelli
AI
2007
Springer
16 years 2 days ago
Learning Network Topology from Simple Sensor Data
In this paper, we present an approach for recovering a topological map of the environment using only detection events from a deployed sensor network. Unlike other solutions to this...
Dimitri Marinakis, Philippe Giguère, Gregor...
ICANN
2005
Springer
15 years 11 months ago
Interpolation Mechanism of Functional Networks
In this paper, the interpolation mechanism of functional networks is discussed. A kind of fourlayer (with 1 input and 1 output unit) and a five-layer (with double input and single...
Yong-Quan Zhou, Licheng Jiao