Zobrazeno 1 - 10
of 13
pro vyhledávání: '"John Mark Agosta"'
Autor:
John-Mark Agosta, Robert Horton, Mengyue Zhao, Debraj GuhaThakurta, Mario Inchiosa, Srini Kumar
Publikováno v:
KDD
R is one of the most popular languages in the data science, statistical and machine learning (ML) community. However, when it comes to scalable data analysis and ML using R, many data scientists are blocked or hindered by (a) its limitations of avail
Publikováno v:
Advanced Information Systems Engineering ISBN: 9783642387081
ECML/PKDD (1)
ECML/PKDD (1)
In this paper, we present a method to iteratively refine the parameters of a Markov Decision Process by leveraging constraints implied from an expert's review of the policy. We impose a constraint on the parameters of the model for every case where t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77361bdedfd0a67d5bdbb9970ae907af
https://doi.org/10.1007/978-3-642-40988-2_11
https://doi.org/10.1007/978-3-642-40988-2_11
Publikováno v:
INFOCOM
In this work we focus on modeling a little studied type of traffic, namely the network traffic generated from endhosts. We introduce a parsimonious parametric model of the marginal distribution for connection arrivals. We employ mixture models based
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98cb3bc0e336c1ec0d0fea0914baa2ac
Publikováno v:
WICOW
We present a method for automatically acquiring of a corpus of disputed claims from the web. We consider a factual claim to be disputed if a page on the web suggests both that the claim is false and also that other people say it is true.Our tool extr
Publikováno v:
WWW
We describe Dispute Finder, a browser extension that alerts a user when information they read online is disputed by a source that they might trust. Dispute Finder examines the text on the page that the user is browsing and highlights any phrases that
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783540874027
RAID
RAID
Collaborative environments present a happy hunting ground for worms due to inherent trust present amongst the peers. We present a novel control-theoretic approach to respond to zero-day worms in a signature independent fashion in a collaborative envi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2a3221fb09652f5a20752d7ff226e363
https://doi.org/10.1007/978-3-540-87403-4_13
https://doi.org/10.1007/978-3-540-87403-4_13
Autor:
John Mark Agosta
Publikováno v:
Intel Technology Journal. 10
Autor:
Denver Dash, John Mark Agosta, Karl Levitt, Jeff Rowe, Senthilkumar G. Cheetancheri, Eve M. Schooler
Publikováno v:
Proceedings of the 2006 SIGCOMM workshop on Large-scale attack defense.
We present a method for detecting large-scale worm attacks using only end-host detectors. These detectors propagate and aggregate alerts to cooperating partners to detect large-scale distributed attacks in progress. The properties of the host-based d
Autor:
John Mark Agosta
Publikováno v:
SPIE Proceedings.
Bayes probability networks, also termed `influence diagrams,' promise to be a versatile, rigorous, and expressive uncertainty reasoning tool. This paper presents an example of how a Bayes network can express constraints among visual hypotheses. An ex