180 search results - page 22 / 36 » Improved bounds on the sample complexity of learning |
ALT
1999
Springer
13 years 11 months ago
1999
Springer
We introduce a new model for learning in the presence of noise, which we call the Nasty Noise model. This model generalizes previously considered models of learning with noise. Th...
FOCS
1999
IEEE
13 years 11 months ago
1999
IEEE
This paper connects two fundamental ideas from theoretical computer science: hard-core set construction, a type of hardness amplification from computational complexity, and boosti...
GECCO
2008
Springer
13 years 8 months ago
2008
Springer
Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
TIP
2008
13 years 7 months ago
2008
Abstract--Local learning methods, such as local linear regression and nearest neighbor classifiers, base estimates on nearby training samples, neighbors. Usually, the number of nei...