COLT
2008
Springer
13 years 5 months ago
2008
Springer
The problem of how a teacher and a learner can cooperate in the process of learning concepts from examples in order to minimize the required sample size without “coding tricksâ€...
COLT
2008
Springer
13 years 6 months ago
2008
Springer
Much attention has been paid to the theoretical explanation of the empirical success of AdaBoost. The most influential work is the margin theory, which is essentially an upper bou...
COLT
2008
Springer
13 years 6 months ago
2008
Springer
We study the potential benefits to classification prediction that arise from having access to unlabeled samples. We compare learning in the semi-supervised model to the standard, ...
COLT
2008
Springer
13 years 6 months ago
2008
Springer
We present a modification of the algorithm of Dani et al. [8] for the online linear optimization problem in the bandit setting, which with high probability has regret at most O ( ...
COLT
2008
Springer
13 years 6 months ago
2008
Springer
COLT
2008
Springer
13 years 6 months ago
2008
Springer
Consider the problem of estimating the -level set G = {x : f(x) } of an unknown d-dimensional density function f based on n independent observations X1, . . . , Xn from the densi...
COLT
2008
Springer
13 years 6 months ago
2008
Springer
We define a model of learning probabilistic acyclic circuits using value injection queries, in which an arbitrary subset of wires is set to fixed values, and the value on the sing...
COLT
2008
Springer
13 years 6 months ago
2008
Springer
We study the problem of learning mixtures of distributions, a natural formalization of clustering. A mixture of distributions is a collection of distributions D = {D1, . . . DT },...
COLT
2008
Springer
13 years 6 months ago
2008
Springer
We introduce an efficient algorithm for the problem of online linear optimization in the bandit setting which achieves the optimal O ( T) regret. The setting is a natural general...
COLT
2008
Springer
13 years 6 months ago
2008
Springer
