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One-Dimensional and Multi-Dimensional Substring Selectivity Estimation

by H.V. Jagadish, Olga Kapitskaia, Raymond T. Ng, Olga Kaudfu, T. Ng, Divesh Srivastava , 2000
"... this paper,we uw pru,C cou,CF1p fix trees (PSTs) as the basic datastruC tur forsu,3kRk, selectivity estimation. For the 1-D problem, we present a novel techniqu called MO (Maximal Overlap). We then develop and analyze two 1-D estimation algorithms, MOC and MOLC,based on MO and a constraint-based cha ..."
Abstract - Cited by 36 (7 self) - Add to MetaCart
and experimentally,that MO is both practical and su,CF1p8,C8 suR,u1 to competing algorithms. Key words: String selectivity -- Maximal overlap -- Short memory property --PruNp couNp&, fix tree 1 Introduction One often wishes to obtain aqu8k estimate of thenu,C1 of times a particuRk suticuR occuc in a database

Generalized substring selectivity estimation

by Zhiyuan Chen , Flip Korn, Nick Koudas, S. Muthukrishnan , 2003
"... In a variety of settings from relational databases to LDAP to Web applications, there is an increasing need to quickly and accurately estimate the count of tuples (LDAP entries, Webdocuments, etc.) matching Boolean substring queries. In providing such selectivity estimates, the correlation between d ..."
Abstract - Cited by 4 (1 self) - Add to MetaCart
different occurrences of substrings is crucial. Selectivity estimation for generalized Boolean queries has not been studied previously; our own prior work, which is discussed and extended herein, applies to the case of onedimensional Boolean queries [CKKM00]. Existing methods for the case

Finite element methods in probabilistic structural analysis: A selected review”.

by H Benaroya , M Rehak - Appl. Mech. Rew. , 1988
"... This review examines the field of structural analysis where finite element methods (FEMs) are used in a probabilistic setting. The finite element method is widely used, and its application in the field of structural analysis is universally accepted as an efficient numerical solution method. The ana ..."
Abstract - Cited by 30 (0 self) - Add to MetaCart
, recursive relations for the mean and variance are derived. The finite element and finite difference solutions are compared to an exact solution. Individual applications Tasaka and Matsuoka (1982) and Tasaka (1985) for the nonstationary case, consider the one-dimensional heat diffusion equation with random

2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications (SPAWC) On the Selection of Testbeds for the Evaluation of Sensor Network Protocols and Applications

by Pablo E. Guerrero, Iliya Gurov, Silvia Santini, Ro Buchmann, Technische Universität Darmstadt Darmstadt
"... Abstract—Wireless sensor network protocols and applications typically need to be evaluated and tested not only using simulators but also on testbeds. While simulations allow studying the performance of protocols and applications in a controlled environment, they usually do not provide a sufficient l ..."
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level of realism. On the contrary, testbeds allow exposing protocols and applications to the real vagaries of wireless communication as well as to other “non-idealities ” that typically occur in real wireless sensor network scenarios. Experimental results gathered in one or more testbeds are thus

AND MATHEMATICAL ENGINEERING

by Madeleine Udell, Professor Lester Mackey , 2015
"... ii ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
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1 Near-Oracle Performance of Greedy Block-Sparse Estimation Techniques from Noisy Measurements

by Zvika Ben-haim, Student Member, Yonina C. Eldar, Senior Member
"... ar ..."
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Statistical Nested Sensor Array Signal Processing

by Keyong Han, I. Norman Katz, Nan Lin, Hiro Mukai, Heinz Schaettler, Keyong Han, Saint Louis Missouri , 2015
"... ..."
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For Peer Review Scenario generation

by John Wiley
"... Keywords: stochastic programming, scenario, quasi-Monte Carlo, scenario reduction, scenario tree ..."
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Keywords: stochastic programming, scenario, quasi-Monte Carlo, scenario reduction, scenario tree

RICE UNIVERSITY Regime Change: Sampling Rate vs. Bit-Depth in Compressive Sensing

by Jason Noah Laska , 2011
"... The compressive sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by exploiting inherent structure in natural and man-made signals. It has been demon-strated that structured signals can be acquired with just a small number of linear measurements, on the order of t ..."
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accommodate the otherwise limiting quantizer of conventional ADCs. In this thesis, we consider a different approach to CS ADC by shifting towards lower quantizer bit-depths rather than lower sampling rates. We explore the extreme case where each measurement is quantized to just one bit, representing its sign

port Vector Machines, Kernel Fisher Discriminant analysis

by Sebastian Mika, Koji Tsuda
"... Abstract | This review provides an introduction to Sup- ..."
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Abstract | This review provides an introduction to Sup-
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