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Sound Probabilistic Inference via Guide Types [article]

Di Wang, Jan Hoffmann, Thomas Reps
2021 arXiv   pre-print
For Bayesian inference to be sound, guide programs must be compatible with model programs.  ...  Modern languages support programmable inference, which allows users to customize inference algorithms by incorporating guide programs to improve inference performance.  ...  Soundness of Inference Algorithms We now describe how guide types can help us reason about inference algorithms. Importance sampling (IS).  ... 
arXiv:2104.03598v1 fatcat:vpobeqiwhnb5bbvaxpicwzvyle

Personalizing video recorders using multimedia processing and integration

Nevenka Dimitrova, Radu Jasinschi, Lalitha Agnihotri, John Zimmerman, Thomas McGee, Dongge Li
2001 Proceedings of the ninth ACM international conference on Multimedia - MULTIMEDIA '01  
The retrieval module relies on users' personal preferences to deliver both full programs and video segments of interest.  ...  We tested retrieval concepts with real users and discovered that they see more value in segmenting non-narrative programs (e.g. news) than narrative programs (e.g. movies).  ...  The Bayesian Engine performed a bi-partite inference between financial news and talk shows on these sub-program units.  ... 
doi:10.1145/500213.500243 fatcat:ggqcor7gg5bw7lo6wtl5rr7wve

Personalizing video recorders using multimedia processing and integration

Nevenka Dimitrova, Radu Jasinschi, Lalitha Agnihotri, John Zimmerman, Thomas McGee, Dongge Li
2001 Proceedings of the ninth ACM international conference on Multimedia - MULTIMEDIA '01  
The retrieval module relies on users' personal preferences to deliver both full programs and video segments of interest.  ...  We tested retrieval concepts with real users and discovered that they see more value in segmenting non-narrative programs (e.g. news) than narrative programs (e.g. movies).  ...  The Bayesian Engine performed a bi-partite inference between financial news and talk shows on these sub-program units.  ... 
doi:10.1145/500141.500243 fatcat:3pbyufxzujf3njihwjpjsuulcm

Doubly Bayesian Optimization [article]

Alexander Lavin
2019 arXiv   pre-print
Probabilistic programming systems enable users to encode model structure and naturally reason about uncertainties, which can be leveraged towards improved Bayesian optimization (BO) methods.  ...  Not only can we utilize programmable structure to incorporate domain knowledge to aid optimization, but dealing with uncertainties and implementing advanced BO techniques become trivial, crucial for use  ...  We use the negative log of the EC50 for numerical reasons.  ... 
arXiv:1812.04562v4 fatcat:jaatj5drsbe5njwpl3fhs7tjeq

The Lumiere Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users [article]

Eric J. Horvitz, John S. Breese, David Heckerman, David Hovel, Koos Rommelse
2013 arXiv   pre-print
We review work on Bayesian user models that can be employed to infer a users needs by considering a user's background, actions, and queries.  ...  Several problems were tackled in Lumiere research, including (1) the construction of Bayesian models for reasoning about the time-varying goals of computer users from their observed actions and queries  ...  We discussed our studies with human subjects to elucidate sets of distinctions that are useful for making inferences about a user's goals and needs and our construction of Bayesian user models.  ... 
arXiv:1301.7385v1 fatcat:h6gtgwgb45aetm43puumcpc7vu

WiseR: An end-to-end structure learning and deployment framework for causal graphical models [article]

Shubham Maheshwari, Khushbu Pahwa, Tavpritesh Sethi
2021 arXiv   pre-print
We present wiseR, an open source application for learning, evaluating and deploying robust causal graphical models using graph neural networks and Bayesian networks.  ...  These can be used both for probabilistic reasoning and causal inference depending upon the study design.  ...  An intuitive left-to-right ordering of tabs guides the user into the analysis.  ... 
arXiv:2108.07046v2 fatcat:e5mnptvy65cd3j7kaa3alamela

A modular design of Bayesian networks using expert knowledge: Context-aware home service robot

Han-Saem Park, Sung-Bae Cho
2012 Expert systems with applications  
The proposed approach supplements uncertain sensor input using Bayesian network modeling and enhances the efficiency in modeling and reasoning processes using modular design based on domain knowledge.  ...  a number of Bayesian networks.  ...  Acknowledgements This research was supported by the Original Technology Research Program for Brain Science through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science  ... 
doi:10.1016/j.eswa.2011.08.118 fatcat:dtqcaan2kffhfjgiddz46ajnkm

Bayesian Cultural Consensus Theory

Zita Oravecz, Joachim Vandekerckhove, William H. Batchelder
2014 Field Methods  
In this paper we present a Bayesian inference framework for Cultural Consensus Theory (CCT) models for dichotomous (True/False) response data, and we provide an associated, user friendly software package  ...  We believe that the time is ripe for Bayesian statistical inference to become the default choice in the field of CCT.  ...  A document that downloads with the software package guides the user step by step through the installation. BCCT uses two accompanying programs that extract automatically.  ... 
doi:10.1177/1525822x13520280 fatcat:uhtkqat3nfbifgvzzidrqyc35e

WOLFE: An NLP-friendly Declarative Machine Learning Stack

Sameer Singh, Tim Rocktäschel, Luke Hewitt, Jason Naradowsky, Sebastian Riedel
2015 Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations  
Existing probabilistic program languages (PPLs) only provide partial solutions; most of them do not support commonly used models such as matrix factorization or neural networks, and do not facilitate interactive  ...  and iterative programming that is crucial for rapid development of these models.  ...  (FCRP) a Semiconductor Research Corporation program sponsored by MARCO and DARPA.  ... 
doi:10.3115/v1/n15-3013 dblp:conf/naacl/SinghRHNR15 fatcat:uenwiqvy55fotp3xxdt4un6psy

A TV Program Recommender Framework

Na Chang, Mhd Irvan, Takao Terano
2013 Procedia Computer Science  
The proposed framework could be used to help designers/developers to build TV program recommender systems/engines for smart TV.  ...  In this paper, we focus on TV program recommender systems.  ...  They used Bayesian classifier to generate recommendations based on initial user profile and adaptive user profile.  ... 
doi:10.1016/j.procs.2013.09.136 fatcat:dj2jdwrsjzecjnba4a2zfcb26m

Designing an Internet-based group decision support system

Kung-Jeng Wang, Chen-Fu Chien
2003 Robotics and Computer-Integrated Manufacturing  
Then, the users can use the decision inference module to derive plausible alternatives while referring to collected and classified information.  ...  reasoning model for a certain situation or by a Bayesian network-based reasoning model for a probabilistic situation.  ...  This function is implemented on a web base in which ASP is used to build programs to operate the user interface, knowledge acquisition interface and inference engine.  ... 
doi:10.1016/s0736-5845(02)00063-7 fatcat:ealqhh3uznfp3kg3nsictiqagi

ENTDEx: ENT Diagnosis Expert System Using Bayesian Networks

Ann Lorraine D. C. Alonzo, Jealarr Joseph M. Campos, Luis Lloyd M. Layco, Charmaine A. Maratas, Ria A. Sagum
2014 Journal of Advances in Computer Networks  
This application uses Bayesian Networks in diagnosing the diseases.  ...  This kind of innovation gave rise to the researchers in creating ENTDEx: ENT Diagnosis Expert System using Bayesian Networks, a system developed to help ENT patients and non-patients to diagnose common  ...  These programs use a collection of facts, rules of thumb, and other knowledge about limited field to help make inferences in the field.  ... 
doi:10.7763/jacn.2014.v2.108 fatcat:dthhnlcr7fbk5lsjopa75ohes4

Accounting Theory as a Bayesian Discipline

David Johnstone
2018 Foundations and Trends® in Accounting  
(Barth, 2006b, p. 95) It could be argued that using information for decision-making -and hence logical (i.e. Bayesian) reasoning -all goes without saying.  ...  It is not only the presumed rule of reasoning in analytical models of accounting disclosure but also the default position for empiricists when hypothesizing about how the users of financial statements  ... 
doi:10.1561/1400000056 fatcat:pxalq27sobcyhcy7qnajpc6ndy

Decreased Business Uncertainty by Using Bayesian Networks for the Paradigm Shift in Business Simulator

Alberto Ochoa, Miguel Ruiz-Jaimes, Sandra Leon, Yadira Toledo, Iván Ramírez
2016 Research in Computing Science  
Strategies as the use of Bayesian networks are associated with the behaviors are linked with the variables and scenarios that can be a presenter during the life of the business.  ...  He served as the basis for Microsoft Office wizard when the user used the aid, since the inference engine considers the Bayesian network user actions, application events and user profiles.  ...  The simulators are mostly computer programs that are using a programming language.  ... 
doi:10.13053/rcs-122-1-7 fatcat:ht37smifbbeatm426fb32znopm

A Two-Stage Bayesian Network for Effective Development of Conversational Agent [chapter]

Jin-Hyuk Hong, Sung-Bae Cho
2003 Lecture Notes in Computer Science  
Actually implementing it for a guide of web pages, we can confirm the usefulness of the proposed architecture for conversational agent.  ...  Composing Bayesian network as two stages, we aim to design conversational agent easily and analyze user's query in detail.  ...  This paper was supported by Biometrics Engineering Research Center, and Brain Science and Engineering Research Program sponsored by Korean Ministry of Science and Technology.  ... 
doi:10.1007/978-3-540-45080-1_1 fatcat:4hg6sfkqpzcwvgnn7db6cnhwfu
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