58 search results - page 3 / 12 » Approximation accuracy, gradient methods, and error bound fo... |
JMLR
2010
13 years 24 days ago
2010
We consider regularized stochastic learning and online optimization problems, where the objective function is the sum of two convex terms: one is the loss function of the learning...
NIPS
2008
13 years 7 months ago
2008
We present a multi-label multiple kernel learning (MKL) formulation in which the data are embedded into a low-dimensional space directed by the instancelabel correlations encoded ...
IWCM
2004
Springer
13 years 11 months ago
2004
Springer
Abstract. Differential motion estimation is based on detecting brightness changes in local image structures. Filters approximating the local gradient are applied to the image seque...
NIPS
2001
13 years 7 months ago
2001
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
PR
2007
13 years 5 months ago
2007
Tuning SVM hyperparameters is an important step in achieving a high-performance learning machine. It is usually done by minimizing an estimate of generalization error based on the...