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FLAIRS
2007
15 years 8 months ago
Context-Sensitive MTL Networks for Machine Lifelong Learning
Context-sensitive Multiple Task Learning, or csMTL, is presented as a method of inductive transfer that uses a single output neural network and additional contextual inputs for le...
Daniel L. Silver, Ryan Poirier
ICML
1999
IEEE
16 years 7 months ago
Machine-Learning Applications of Algorithmic Randomness
Most machine learning algorithms share the following drawback: they only output bare predictions but not the con dence in those predictions. In the 1960s algorithmic information t...
Volodya Vovk, Alexander Gammerman, Craig Saunders
170
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SEKE
2007
Springer
16 years 15 days ago
An Approach to Software Testing of Machine Learning Applications
Some machine learning applications are intended to learn properties of data sets where the correct answers are not already known to human users. It is challenging to test such ML ...
Chris Murphy, Gail E. Kaiser, Marta Arias
AUSAI
2004
Springer
15 years 11 months ago
Using Machine Learning Techniques to Combine Forecasting Methods
We present here an original work that uses machine learning techniques to combine time series forecasts. In this proposal, a machine learning technique uses features of the series ...
Ricardo Bastos Cavalcante Prudêncio, Teresa ...
ESANN
2007
15 years 7 months ago
Convex optimization for the design of learning machines
This paper reviews the recent surge of interest in convex optimization in a context of pattern recognition and machine learning. The main thesis of this paper is that the design of...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...