Filters








12,848 Hits in 4.3 sec

Modelling retrieval models in a probabilistic relational algebra with a new operator: the relational Bayes

Thomas Roelleke, Hengzhi Wu, Jun Wang, Hany Azzam
2007 The VLDB journal  
[ valueKey=valueKey ] ( Project distinct ( r ), Bayes [] ( Project distinct[valueKey] (r))))) Since the general concept of an ivf -based probability has its origin in the IR concept of idf -based probabilities  ...  The contributions of this paper include the specification of probabilistic SQL (PSQL) and probabilistic relational algebra (PRA), a new relational operator for probability estimation (the relational Bayes  ...  The generalised notion of value-based versus documentbased, and the value-based versus tuple-based probabilities play an important role when modelling retrieval models (section 7).  ... 
doi:10.1007/s00778-007-0073-y fatcat:qiexpftcfvgs7eonakx3xocb7e

Two Types of Distributed CFAR Detection Based on Weighting Functions in Fusion Center for Weibull Clutter

Amir Zaimbashi
2013 Journal of Engineering  
In the fuzzy type, we consider the various distributed detectors based on algebraic product, algebraic sum, probabilistic OR, and Lukasiewicz t-conorm fuzzy rules in fusion center.  ...  before transmitting data to the fusion center.  ...  In this type, we consider the various distributed detectors based on ML (OS) CFAR processor in local detectors and algebraic product, algebraic sum, probabilistic OR, and Lukasiewicz tconorm fuzzy rules  ... 
doi:10.1155/2013/648190 fatcat:qqlfv432kze5na73dodeqd5oyy

Independent Component Analysis for Source Localization of EEG Sleep Spindle Components

Erricos M. Ventouras, Periklis Y. Ktonas, Hara Tsekou, Thomas Paparrigopoulos, Ioannis Kalatzis, Constantin R. Soldatos
2010 Computational Intelligence and Neuroscience  
The purpose of the present study was to process sleep spindles with Independent Component Analysis (ICA) in order to investigate the possibility of extracting, through visual analysis of the spindle EEG  ...  Results indicated that SCs can be extracted by reconstructing the EEG through back-projection of separate groups of ICs, based on a temporal and spectral analysis of ICs.  ...  Cavouras, "Probabilistic Neural Network versus Cubic Least-Squares Minimum-Distance in Classifying EEG Signals".  ... 
doi:10.1155/2010/329436 pmid:20369057 pmcid:PMC2847376 fatcat:hkwqlv254jfghiorpqc5sodavm

Page 3832 of Mathematical Reviews Vol. , Issue 87g [page]

1987 Mathematical Reviews  
Immer- man, Sparse sets in NP-P: EXPTIME versus NEXPTIME (pp. 382-391); P. Young, Some structural properties of polynomial re- ducibilities and sets in NP (pp. 392-401). L. M.  ...  Srinivas, Data structures for on-line updating of matroid intersection solutions (pp. 383-390). C.  ... 

Introduction to the special issue on database and information retrieval integration

W. Bruce Croft, Hans-J. Schek
2007 The VLDB journal  
efficient indexing and optimization techniques for Web-scale data.  ...  To provide some context, it is worth briefly reviewing some of the work that was done in the past, particularly in the more distant pre-Web days.  ...  Schmitt's paper describes how a new modeling approach based on quantum logic that is being used in IR may be used as the basis for an integrated data base and IR system. Lau et al.'  ... 
doi:10.1007/s00778-007-0074-x fatcat:ld66ny4vvrbuze7hwhhl7xu2ca

Detecting Dependencies in Sparse, Multivariate Databases Using Probabilistic Programming and Non-parametric Bayes [article]

Feras Saad, Vikash Mansinghka
2017 arXiv   pre-print
Users can access these capabilities using BayesDB, a probabilistic programming platform for probabilistic data analysis, by writing queries in a simple, SQL-like language.  ...  It shows how to use Bayesian non-parametric modeling to (i) build an ensemble of joint probability models for all the variables; (ii) efficiently detect marginal independencies; and (iii) estimate the  ...  First, the Monte Carlo estimator in [16] is based on resampling empirical data.  ... 
arXiv:1611.01708v2 fatcat:skzsiytqijeabludcmogli2ew4

Book announcements

1984 Discrete Applied Mathematics  
Reif On the power of probabilistic choice in synchronous parallel computations. C. Reutenzuer: Biprefix codes and semisimple algebras. A. Sulwicki: Algorithmic theories of data structures. D.  ...  Loos: Deterministic versus probabilistic factorization of integral polynomials. D. Lazard: On polynomial factorization. P.S. Wang: Hacijan's algorithm in VAXIMA: improvements and difficulties. J.H.  ... 
doi:10.1016/0166-218x(84)90070-2 fatcat:75txrigmzzaw5ef5itdxwfbdea

Conditioning probabilistic databases

Christoph Koch, Dan Olteanu
2008 Proceedings of the VLDB Endowment  
We assume independence between John's and Bill's alternatives, thus the world in which John has SSN 1 and Bill has SSN 7 has probability .2 · .7 = .14.  ...  We can compute these probabilities in a probabilistic database by asking for the confidence values of the tuples in the result of the query select SSN, conf(SSN) from R where NAME = 'Bill'; which will  ...  Processing relational algebra queries on probabilistic databases was discussed in Section 2.  ... 
doi:10.14778/1453856.1453894 fatcat:aprnpguqh5dzxkfvvu4wu2utwu

Conditioning Probabilistic Databases [article]

Christoph Koch, Dan Olteanu
2008 arXiv   pre-print
Application scenarios of probabilistic databases however often involve the conditioning of a database using additional information in the form of new evidence.  ...  In this paper we present efficient techniques for both problems.  ...  Processing relational algebra queries on probabilistic databases was discussed in Section 2.  ... 
arXiv:0803.2212v2 fatcat:rgjuuq6brvhdjmlgkb2myv62de

Page 1308 of Mathematical Reviews Vol. , Issue 2002B [page]

2002 Mathematical Reviews  
2002b:68068 representation for the asynchronous z-calculus.” 2002b:68068 68Q85 Corradini, Flavio (I-LAQL-PM; L'Aquila) Absolute versus relative time in process algebras.  ...  Summary: “We present a process algebra, SPADES, based on Milner’s CCS, which may be used to describe discrete event simu- lations with parallelism.  ... 

Symbolic Computing in Probabilistic and Stochastic Analysis

Marcin Kamiński
2015 International Journal of Applied Mathematics and Computer Science  
We recover in this context the probabilistic structural response in engineering systems and show how to solve partial differential equations including Gaussian randomness in their coefficients.  ...  The main aim is to present recent developments in applications of symbolic computing in probabilistic and stochastic analysis, and this is done using the example of the well-known MAPLE system.  ...  Center CYFRONET in Cracow, Poland.  ... 
doi:10.1515/amcs-2015-0069 fatcat:zqwuua3rxbbxlo5xgdnyxlhfae

Deterministic and Probabilistic Conditions for Finite Completability of Low-rank Multi-View Data [article]

Morteza Ashraphijuo and Xiaodong Wang and Vaneet Aggarwal
2017 arXiv   pre-print
We also give a probabilistic condition in terms of the number of samples per column that guarantees finite completability with high probability.  ...  In particular, we investigate the fundamental conditions on the sampling pattern, i.e., locations of the sampled entries for finite completability of such a multi-view data given the corresponding rank  ...  Numerical results are provided in Section VI to compare the number of samples per column for finite and unique completions based on our proposed analysis versus the existing method.  ... 
arXiv:1701.00737v2 fatcat:46akuhl52vgwpoknsb2las3t4a

Special issue on Combining Probability and Logic

Jon Williamson, Dov Gabbay
2003 Journal of Applied Logic  
The papers in this volume concern either the special focus on the connection between probabilistic logic and probabilistic networks or the more general question of the links between probability and logic  ...  Here we introduce probabilistic logic, probabilistic networks, current and future directions of research and also the themes of the papers that follow.  ...  Ochoa Luna examine network-based representations for independence relations in probabilistic logics.  ... 
doi:10.1016/s1570-8683(03)00009-0 fatcat:ldvbd3jza5axlkp2x4isedswze

Special issue: Combining probability and logic

Jürgen Landes, Jon Williamson
2016 Journal of Applied Logic  
The papers in this volume concern either the special focus on the connection between probabilistic logic and probabilistic networks or the more general question of the links between probability and logic  ...  Here we introduce probabilistic logic, probabilistic networks, current and future directions of research and also the themes of the papers that follow.  ...  Ochoa Luna examine network-based representations for independence relations in probabilistic logics.  ... 
doi:10.1016/j.jal.2015.09.009 fatcat:37jxfr4tjrcinlk6vvlontftha

Probabilistic graphs using coupled random variables [article]

Kenric P. Nelson, Madalina Barbu, Brian J. Scannell
2014 arXiv   pre-print
Graphical probabilistic models ground network design in probabilistic reasoning, but the restrictions reduce the expressive capability of each node making network designs complex.  ...  A coupled Markov random field is designed for the inferencing and classification of UCI's MLR 'Multiple Features Data Set' such that thousands of linear correlation parameters can be replaced with a single  ...  COUPLED MARKOV MODEL OF THE MULTIPLE FEATURES DATA SET To illustrate the utility of a probabilistic graph using a coupled Markov random field the Machine Learning Repository's Multiple Features Data Set  ... 
arXiv:1404.6955v1 fatcat:ufyf5grrbzamjcfl5mxcpdkdiy
« Previous Showing results 1 — 15 out of 12,848 results