@article{Dayanik2003,
	title = {On the optimal stopping problem for one-dimensional diffusions},
	author = {Savas Dayanik and Ioannis Karatzas},
	journal = {Stochastic Processes and their Applications},
	month = {Oct},
	number = {2},
	pages = {173--212},
	url = {http://www.sciencedirect.com/science/article/B6V1B-48V7PKB-1/1/3d6631cffa8a7469e234344f82b3b8fd},
	volume = {107},
	year = {2003},
	biburl = {http://www.bibsonomy.org/bibtex/274981add796d2e38210a8d0a44d352fc/smicha},
	description = {Stochastic Processes and their Applications},
	keywords = {Optimal stopping }
}

@article{Bayraktar2005,
	title = {The standard Poisson disorder problem revisited},
	author = {Erhan Bayraktar and Savas Dayanik and Ioannis Karatzas},
	journal = {Stochastic Processes and their Applications},
	month = {Sep},
	number = {9},
	pages = {1437--1450},
	url = {http://www.sciencedirect.com/science/article/B6V1B-4G98WYN-3/1/5730f13e413a694f2788a5b7e9c78d07},
	volume = {115},
	year = {2005},
	biburl = {http://www.bibsonomy.org/bibtex/25e69823697bf49f9bb7c8ad73c1da1a3/smicha},
	description = {Stochastic Processes and their Applications},
	keywords = {Poisson disorder problem }
}

@article{Dayanik2006,
	title = {Sequential testing of simple hypotheses about compound Poisson processes},
	author = {Savas Dayanik and Semih O. Sezer},
	journal = {Stochastic Processes and their Applications},
	month = {Dec},
	number = {12},
	pages = {1892--1919},
	url = {http://www.sciencedirect.com/science/article/B6V1B-4K4WFH9-2/1/ffd45f28a31c65aed0054ce3e6c6a9bb},
	volume = {116},
	year = {2006},
	biburl = {http://www.bibsonomy.org/bibtex/24fc52c21c6eac896936329aef8bbe3db/smicha},
	description = {Stochastic Processes and their Applications},
	keywords = {Sequential hypothesis testing }
}

@article{journals/corr/abs-0710-4847,
	title = {Bayesian sequential change diagnosis},
	author = {Savas Dayanik and Christian Goulding and H. Vincent Poor},
	journal = {CoRR},
	note = {informal publication},
	url = {http://dblp.uni-trier.de/db/journals/corr/corr0710.html#abs-0710-4847},
	volume = {abs/0710.4847},
	year = {2007},
	biburl = {http://www.bibsonomy.org/bibtex/20be4ad777c4bacddbdeaf34c9cb911e0/dblp},
	description = {dblp},
	ee = {http://arxiv.org/abs/0710.4847}, date = {2008-01-02},
	keywords = {dblp }
}

@article{journals/corr/abs-0708-0224,
	title = {Multisource Bayesian sequential change detection},
	author = {Savas Dayanik and Harold Vincent Poor and Semih Onur Sezer},
	journal = {CoRR},
	note = {informal publication},
	url = {http://dblp.uni-trier.de/db/journals/corr/corr0708.html#abs-0708-0224},
	volume = {abs/0708.0224},
	year = {2007},
	biburl = {http://www.bibsonomy.org/bibtex/2073ceb2feefffce3bdac484c7fdacb7c/dblp},
	description = {dblp},
	ee = {http://arxiv.org/abs/0708.0224}, date = {2008-01-02},
	keywords = {dblp }
}

@article{journals/corr/abs-math-0610184,
	title = {Adaptive Poisson disorder problem},
	author = {Erhan Bayraktar and Savas Dayanik and Ioannis Karatzas},
	journal = {CoRR},
	note = {informal publication},
	url = {http://dblp.uni-trier.de/db/journals/corr/corr0610.html#abs-math-0610184},
	volume = {abs/math/0610184},
	year = {2006},
	biburl = {http://www.bibsonomy.org/bibtex/28682d5a1188dd37db05fcd62d62b2c1a/dblp},
	description = {dblp},
	ee = {http://arxiv.org/abs/math/0610184}, date = {2008-01-02},
	keywords = {dblp }
}

@article{journals/corr/abs-0705-0043,
	title = {Joint Detection and Identification of an Unobservable Change in the Distribution of a Random Sequence},
	author = {Savas Dayanik and Christian Goulding and H. Vincent Poor},
	journal = {CoRR},
	note = {informal publication},
	url = {http://dblp.uni-trier.de/db/journals/corr/corr0705.html#abs-0705-0043},
	volume = {abs/0705.0043},
	year = {2007},
	biburl = {http://www.bibsonomy.org/bibtex/2777b52f10dae3381b52dd13211036d07/dblp},
	description = {dblp},
	ee = {http://arxiv.org/abs/0705.0043}, date = {2008-01-02},
	keywords = {dblp }
}

@inproceedings{conf/ijcai/MacskassyHBD01,
	title = {Using Text Classifiers for Numerical Classification.},
	author = {Sofus A. Macskassy and Haym Hirsh and Arunava Banerjee and Aynur A. Dayanik},
	booktitle = {IJCAI},
	crossref = {conf/ijcai/2001},
	editor = {Bernhard Nebel},
	pages = {885-890},
	publisher = {Morgan Kaufmann},
	url = {http://www.cise.ufl.edu/~arunava/papers/ijcai01.pdf},
	year = {2001},
	biburl = {http://www.bibsonomy.org/bibtex/25b25c6b148179c71721ab8574f83b467/jil},
	isbn = {1-55860-777-3}, date = {2003-05-23},
	keywords = {dichte feature mdl numeric split }
}

@inproceedings{conf/ciss/DayanikGP07,
	title = {Joint Detection and Identification of an Unobservable Change in the Distribution of a Random Sequence.},
	author = {Savas Dayanik and Christian Goulding and H. Vincent Poor},
	booktitle = {CISS},
	crossref = {conf/ciss/2007},
	pages = {68-73},
	publisher = {IEEE},
	url = {http://dblp.uni-trier.de/db/conf/ciss/ciss2007.html#DayanikGP07},
	year = {2007},
	biburl = {http://www.bibsonomy.org/bibtex/25c58440aa1790a0dc921460dd13cb350/dblp},
	description = {dblp},
	ee = {http://dx.doi.org/10.1109/CISS.2007.4298275}, date = {2007-09-07},
	keywords = {dblp }
}

@inproceedings{conf/sigir/DayanikLMMG06,
	title = {Constructing informative prior distributions from domain knowledge in text classification.},
	author = {Aynur A. Dayanik and David D. Lewis and David Madigan and Vladimir Menkov and Alexander Genkin},
	booktitle = {SIGIR},
	crossref = {conf/sigir/2006},
	editor = {Efthimis N. Efthimiadis and Susan T. Dumais and David Hawking and Kalervo Järvelin},
	pages = {493-500},
	publisher = {ACM},
	url = {http://dblp.uni-trier.de/db/conf/sigir/sigir2006.html#DayanikLMMG06},
	year = {2006},
	biburl = {http://www.bibsonomy.org/bibtex/2635997d34b77c2dde18c229867257017/flawed},
	abstract = { Supervised learning approaches to text classification are in practice often required to work with small and unsystematically collected training sets. The alternative to supervised learning is usually viewed to be building classifiers by hand, using a domain expert's understanding of which features of the text are related to the class of interest. This is expensive, requires a degree of sophistication about linguistics and classification, and makes it difficult to use combinations of weak predictors. We propose instead combining domain knowledge with training examples in a Bayesian framework. Domain knowledge is used to specify a prior distribution for the parameters of a logistic regression model, and labeled training data is used to produce a posterior distribution, whose mode we take as the final classifier. We show on three text categorization data sets that this approach can rescue what would otherwise be disastrously bad training situations, producing much more effective classifiers.},
	ee = {http://doi.acm.org/10.1145/1148170.1148255}, isbn = {1-59593-369-7}, date = {2006-08-30},
	keywords = {classification priors }
}