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FOCS
1990
IEEE
15 years 1 months ago
Separating Distribution-Free and Mistake-Bound Learning Models over the Boolean Domain
Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
Avrim Blum
SIGMOD
2010
ACM
153views Database» more  SIGMOD 2010»
15 years 2 months ago
Threshold query optimization for uncertain data
The probabilistic threshold query (PTQ) is one of the most common queries in uncertain databases, where all results satisfying the query with probabilities that meet the threshold...
Yinian Qi, Rohit Jain, Sarvjeet Singh, Sunil Prabh...
192
Voted
ICDE
2006
IEEE
194views Database» more  ICDE 2006»
15 years 11 months ago
The Gauss-Tree: Efficient Object Identification in Databases of Probabilistic Feature Vectors
In applications of biometric databases the typical task is to identify individuals according to features which are not exactly known. Reasons for this inexactness are varying meas...
Alexey Pryakhin, Christian Böhm, Matthias Sch...
ICIP
2000
IEEE
15 years 11 months ago
Hierarchical Image Probability (HIP) Models
We formulate a model for probability distributions on image spaces. We show that any distribution of images can be factored exactly into conditional distributions of feature vecto...
Clay Spence, Lucas C. Parra, Paul Sajda
AAAI
2006
14 years 11 months ago
Identification of Joint Interventional Distributions in Recursive Semi-Markovian Causal Models
This paper is concerned with estimating the effects of actions from causal assumptions, represented concisely as a directed graph, and statistical knowledge, given as a probabilit...
Ilya Shpitser, Judea Pearl