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EBSCO_on1317772343 |
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OCoLC |
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20231017213018.0 |
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m o d |
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cr cnu---unuuu |
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220517s2022 ne o 000 0 eng d |
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|a IOSPR
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| 020 |
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|a 9781643682679
|q (electronic bk.)
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|a 1643682679
|q (electronic bk.)
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|z 9781643682662
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|a (OCoLC)1317772343
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|a 9781643682679
|b IOS Press
|n http://www.iospress.nl
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|a Q325.5
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|a 006.3/1
|2 23
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|a UAMI
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| 100 |
1 |
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|a Morettin, Paolo,
|e author.
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| 245 |
1 |
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|a Learning and reasoning in hybrid structured spaces /
|c Paolo Morettin.
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| 264 |
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1 |
|a Amsterdam, Netherlands :
|b IOS Press,
|c 2022.
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| 300 |
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|a 1 online resource.
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 490 |
1 |
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|a Frontiers in artificial intelligence and applications ;
|v volume 350
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| 588 |
0 |
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|a Online resource; title from] PDF title page (IOS Press, viewed May 17, 2022).
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| 505 |
0 |
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|a Intro -- Title Page -- Abstract -- Acknowledgments -- Contents -- Introduction -- Motivation -- Contributions -- Outline of the Thesis -- Background -- Probabilistic Graphical Models -- Bayesian Networks -- Markov Networks -- Factor graphs -- The belief propagation algorithm -- Inference by Weighted Model Counting -- Propositional satisfiability -- Weighted Model Counting -- Logical structure -- Inference by Weighted Model Integration -- Satisfiability Modulo Theories -- Weighted Model Integration -- Related work -- Modelling and inference -- Learning -- WMI-PA -- Predicate Abstraction
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| 505 |
8 |
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|a Weighted Model Integration, Revisited -- Basic case: WMI Without Atomic Propositions -- General Case: WMI With Atomic Propositions -- Conditional Weight Functions -- From WMI to WMIold and vice versa -- A Case Study -- Modelling a journey with a fixed path -- Modelling a journey under a conditional plan -- Efficiency of the encodings -- Efficient WMI Computation -- The Procedure WMI-AllSMT -- The Procedure WMI-PA -- WMI-PA vs. WMI-AllSMT -- Experiments -- Synthetic Setting -- Strategic Road Network with Fixed Path -- Strategic Road Network with Conditional Plans -- Discussion -- Final remarks
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| 505 |
8 |
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|a MP-MI -- Preliminaries -- Computing MI -- Hybrid inference via MI -- On the inherent hardness of MI -- MP-MI: exact MI inference via message passing -- Propagation scheme -- Amortizing Queries -- Complexity of MP-MI -- Experiments -- Final remarks -- lariat -- Learning WMI distributions -- Learning the support -- Learning the weight function -- Normalization -- Experiments -- Final remarks -- Conclusion
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| 590 |
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|a eBooks on EBSCOhost
|b EBSCO eBook Subscription Academic Collection - Worldwide
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| 650 |
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0 |
|a Machine learning.
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| 650 |
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|a Apprentissage automatique.
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| 650 |
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7 |
|a Machine learning
|2 fast
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|a Frontiers in artificial intelligence and applications ;
|v v. 350.
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|b EBLB
|n EBL29238892
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