Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Stavros Lopatatzidis"'
Publikováno v:
International Journal of Approximate Reasoning. 80:137-173
We provide simple methods for computing exact bounds on expected first-passage and return times in finite-state birth-death chains, when the transition probabilities are imprecise, in the sense that they are only known to belong to convex closed sets
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::42433514f941baa73286f7a35afbc42e
https://doi.org/10.1016/j.ijar.2016.08.008
https://doi.org/10.1016/j.ijar.2016.08.008
Publikováno v:
International Journal of Approximate Reasoning. 76:18-46
We justify and discuss expressions for joint lower and upper expectations in imprecise probability trees, in terms of the sub- and supermartingales that can be associated with such trees. These imprecise probability trees can be seen as discrete-time
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d761200c5b8ab2265809fb03faa0112b
https://doi.org/10.1016/j.ijar.2016.04.009
https://doi.org/10.1016/j.ijar.2016.04.009
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319615806
ECSQARU
ECSQARU
The notion of stability in semi-graphoid independency models was introduced to describe the dynamics of (probabilistic) independency upon inference. We revisit the notion in view of establishing compact representations of semi-graphoid models in gene
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::36d290c50762681947fc4a4017436bf4
https://doi.org/10.1007/978-3-319-61581-3_10
https://doi.org/10.1007/978-3-319-61581-3_10
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319208060
ECSQARU
ECSQARU
The conditional independencies from a joint probability distribution constitute a model which is closed under the semi-graphoid properties of independency. These models typically are exponentially large in size and cannot be feasibly enumerated. For
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::750246a24e5353c532e197d599b4c0e7
https://doi.org/10.1007/978-3-319-20807-7_26
https://doi.org/10.1007/978-3-319-20807-7_26
Publikováno v:
SIGDOC
The concept of social networks in conjunction with concepts from economics has attracted considerable attention in recent years. In this paper we propose the Stochastic Diffusion Market Search (SDMS), a novel contextual advertising method for mutual
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::891116c23c4fb4e867ea2bbd8875b3d5
https://doi.org/10.1145/1878450.1878464
https://doi.org/10.1145/1878450.1878464