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» Bounds on marginal probability distributions
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COLT
1999
Springer
14 years 5 days ago
Covering Numbers for Support Vector Machines
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Ro...
QEST
2010
IEEE
13 years 5 months ago
Reasoning about MDPs as Transformers of Probability Distributions
We consider Markov Decision Processes (MDPs) as transformers on probability distributions, where with respect to a scheduler that resolves nondeterminism, the MDP can be seen as ex...
Vijay Anand Korthikanti, Mahesh Viswanathan, Gul A...
IJCAI
1997
13 years 9 months ago
A Symmetric View of Utilities and Probabilities
Motivated by the need to reason about utilities, and inspired by the success of bayesian networks in representing and reasoning about probabilities, we introduce the notion of uti...
Yoav Shoham
ICML
2008
IEEE
14 years 8 months ago
Laplace maximum margin Markov networks
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...
Jun Zhu, Eric P. Xing, Bo Zhang
ICC
2007
IEEE
14 years 2 months ago
Handoff Probability in Wireless Networks Over Rayleigh Fading Channel: A Cross-layer Approach
Abstract— Handoff probability is one of the significant metrics to characterize the handoff operation in wireless mobile networks. Handoff probability refers to the probability ...
Yan Zhang