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ECSQARU
1995
Springer
15 years 1 months ago
Parametric Structure of Probabilities in Bayesian Networks
The paper presents a method for uncertainty propagation in Bayesian networks in symbolic, as opposed to numeric, form. The algebraic structure of probabilities is characterized. Th...
Enrique Castillo, José Manuel Gutiér...
WWW
2008
ACM
15 years 10 months ago
Dynamic cost-per-action mechanisms and applications to online advertising
We study the Cost-Per-Action or Cost-Per-Acquisition (CPA) charging scheme in online advertising. In this scheme, instead of paying per click, the advertisers pay only when a user...
Hamid Nazerzadeh, Amin Saberi, Rakesh Vohra
JMLR
2010
149views more  JMLR 2010»
14 years 4 months ago
Learning Bayesian Network Structure using LP Relaxations
We propose to solve the combinatorial problem of finding the highest scoring Bayesian network structure from data. This structure learning problem can be viewed as an inference pr...
Tommi Jaakkola, David Sontag, Amir Globerson, Mari...
NIPS
2008
14 years 11 months ago
Online Metric Learning and Fast Similarity Search
Metric learning algorithms can provide useful distance functions for a variety of domains, and recent work has shown good accuracy for problems where the learner can access all di...
Prateek Jain, Brian Kulis, Inderjit S. Dhillon, Kr...
EUROCOLT
1995
Springer
15 years 1 months ago
A decision-theoretic generalization of on-line learning and an application to boosting
k. The model we study can be interpreted as a broad, abstract extension of the well-studied on-line prediction model to a general decision-theoretic setting. We show that the multi...
Yoav Freund, Robert E. Schapire