137 search results - page 8 / 28 » Quantifying the Impact of Learning Algorithm Parameter Tunin... |
ICML
2010
IEEE
13 years 9 months ago
2010
IEEE
Optimization problems with a nuclear norm regularization, such as e.g. low norm matrix factorizations, have seen many applications recently. We propose a new approximation algorit...
IROS
2007
IEEE
14 years 2 months ago
2007
IEEE
— In this paper, we introduce a modified Kalman filter that can perform robust, real-time outlier detection in the observations, without the need for parameter tuning. Robotic ...
ECAI
2004
Springer
14 years 2 months ago
2004
Springer
The purpose of this paper is to show that a well known machine learning technique based on Decision Trees can be effectively used to select the best approach (in terms of efficien...
ICB
2009
Springer
14 years 3 months ago
2009
Springer
The small sample size problem and the difficulty in determining the optimal reduced dimension limit the application of subspace learning methods in the gait recognition domain. To...
ICML
2006
IEEE
14 years 9 months ago
2006
IEEE
Mobile robots often rely upon systems that render sensor data and perceptual features into costs that can be used in a planner. The behavior that a designer wishes the planner to ...