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VLDB
2001
ACM
82views Database» more  VLDB 2001»
15 years 11 months ago
Supporting Incremental Join Queries on Ranked Inputs
This paper investigates the problem of incremental joins of multiple ranked data sets when the join condition is a list of arbitrary user-defined predicates on the input tuples. ...
Apostol Natsev, Yuan-Chi Chang, John R. Smith, Chu...
POPL
2007
ACM
16 years 7 months ago
Program verification as probabilistic inference
In this paper, we propose a new algorithm for proving the validity or invalidity of a pre/postcondition pair for a program. The algorithm is motivated by the success of the algori...
Sumit Gulwani, Nebojsa Jojic
ECCV
2006
Springer
16 years 8 months ago
Learning to Combine Bottom-Up and Top-Down Segmentation
Bottom-up segmentation based only on low-level cues is a notoriously difficult problem. This difficulty has lead to recent top-down segmentation algorithms that are based on class-...
Anat Levin, Yair Weiss
ICML
2007
IEEE
16 years 7 months ago
Combining online and offline knowledge in UCT
The UCT algorithm learns a value function online using sample-based search. The TD() algorithm can learn a value function offline for the on-policy distribution. We consider three...
Sylvain Gelly, David Silver
STOC
2003
ACM
154views Algorithms» more  STOC 2003»
16 years 7 months ago
Boosting in the presence of noise
Boosting algorithms are procedures that "boost" low-accuracy weak learning algorithms to achieve arbitrarily high accuracy. Over the past decade boosting has been widely...
Adam Kalai, Rocco A. Servedio