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FOCS
2004
IEEE
15 years 10 months ago
Stochastic Optimization is (Almost) as easy as Deterministic Optimization
Stochastic optimization problems attempt to model uncertainty in the data by assuming that (part of) the input is specified in terms of a probability distribution. We consider the...
David B. Shmoys, Chaitanya Swamy
DIS
2006
Springer
15 years 10 months ago
Incremental Algorithm Driven by Error Margins
Incremental learning is an approach to deal with the classification task when datasets are too large or when new examples can arrive at any time. One possible approach uses concent...
Gonzalo Ramos-Jiménez, José del Camp...
SPIN
2000
Springer
15 years 10 months ago
Model Checking Based on Simultaneous Reachability Analysis
Abstract. Simultaneous reachability analysis SRA is a recently proposed approach to alleviating the state space explosion problem in reachability analysis of concurrent systems. Th...
Bengi Karaçali, Kuo-Chung Tai
ACSC
2008
IEEE
15 years 8 months ago
An investigation of the state formation and transition limitations for prediction problems in recurrent neural networks
Recurrent neural networks are able to store information about previous as well as current inputs. This "memory" allows them to solve temporal problems such as language r...
Angel Kennedy, Cara MacNish
CSCW
2008
ACM
15 years 8 months ago
Mopping up: modeling wikipedia promotion decisions
This paper presents a model of the behavior of candidates for promotion to administrator status in Wikipedia. It uses a policy capture framework to highlight similarities and diff...
Moira Burke, Robert Kraut