323 search results - page 11 / 65 » New Algorithms for Learning in Presence of Errors |
COLT
2007
Springer
14 years 1 months ago
2007
Springer
We present data-dependent error bounds for transductive learning based on transductive Rademacher complexity. For specific algorithms we provide bounds on their Rademacher complex...
ML
2008
ACM
13 years 7 months ago
2008
ACM
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
GECCO
2000
Springer
13 years 11 months ago
2000
Springer
Reinforcement learning (RL) is one of the machine learning techniques and has been received much attention as a new self-adaptive controller for various systems. The RL agent auto...
IWANN
2001
Springer
13 years 12 months ago
2001
Springer
Abstract. Mechanisms for adapting models, filters, regulators and so on to changing properties of a system are of fundamental importance in many modern identification, estimation...
ML
2002
ACM
13 years 7 months ago
2002
ACM
Model selection is an important ingredient of many machine learning algorithms, in particular when the sample size in small, in order to strike the right trade-off between overfitt...