Linear regression

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In statistics, linear regression is an approach to modeling the relationship between a scalar variable y and one or more variables denoted X. (Wikipedia.org)


Conferences related to Linear regression

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2018 24th International Conference on Pattern Recognition (ICPR)

ICPR will be an international forum for discussions on recent advances in the fields of Pattern Recognition, Machine Learning and Computer Vision, and on applications of these technologies in various fields

  • 2016 23rd International Conference on Pattern Recognition (ICPR)

    ICPR'2016 will be an international forum for discussions on recent advances in the fields of Pattern Recognition, Machine Learning and Computer Vision, and on applications of these technologies in various fields.

  • 2014 22nd International Conference on Pattern Recognition (ICPR)

    ICPR 2014 will be an international forum for discussions on recent advances in the fields of Pattern Recognition; Machine Learning and Computer Vision; and on applications of these technologies in various fields.

  • 2012 21st International Conference on Pattern Recognition (ICPR)

    ICPR is the largest international conference which covers pattern recognition, computer vision, signal processing, and machine learning and their applications. This has been organized every two years by main sponsorship of IAPR, and has recently been with the technical sponsorship of IEEE-CS. The related research fields are also covered by many societies of IEEE including IEEE-CS, therefore the technical sponsorship of IEEE-CS will provide huge benefit to a lot of members of IEEE. Archiving into IEEE Xplore will also provide significant benefit to the all members of IEEE.

  • 2010 20th International Conference on Pattern Recognition (ICPR)

    ICPR 2010 will be an international forum for discussions on recent advances in the fields of Computer Vision; Pattern Recognition and Machine Learning; Signal, Speech, Image and Video Processing; Biometrics and Human Computer Interaction; Multimedia and Document Analysis, Processing and Retrieval; Medical Imaging and Visualization.

  • 2008 19th International Conferences on Pattern Recognition (ICPR)

    The ICPR 2008 will be an international forum for discussions on recent advances in the fields of Computer vision, Pattern recognition (theory, methods and algorithms), Image, speech and signal analysis, Multimedia and video analysis, Biometrics, Document analysis, and Bioinformatics and biomedical applications.

  • 2002 16th International Conference on Pattern Recognition


2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE


2018 IEEE 87th Vehicular Technology Conference (VTC Spring)

The technical scope of VTC2018-Spring includes:Ad-hoc, Mesh, and Sensor NetworksAntennas and Propagation and RF DesignCognitive Radio and Spectrum SensingCooperative Communications, Distributed MIMO and RelayingMobile Networks, Applications and ServicesMultiple Antenna Systems and ServicesSatellite Networks, Positioning Technologies, Localization and NavigationTransmission Technologies and Communication TheoryTransportation, Vehicular Networks, and Vehicular Electronics and Telematics; Wireless AccessWireless Networks and SecurityHealth, Body-Area and Medical Device NetworksGreen NetworksMedium access control and routing protocolsNarrowband, wideband and ultra-widebandPHY and MAC layer designChannel modeling, equalization, synchronization, modulation and codingOFDM, CDMA, WiMAXLTE AdvancedITS, Car-to-car, and Car-to-X


2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

FUZZ-IEEE is the top leading conferencein the area of theory and applications of fuzzy logic.


2018 IEEE International Conference on Robotics and Automation (ICRA)

ICRA is the IEEE Robotics and Automation Society's flagship conference and is a premier international forum for robotics researchers to present their work.


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Periodicals related to Linear regression

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Audio, Speech, and Language Processing, IEEE Transactions on

Speech analysis, synthesis, coding speech recognition, speaker recognition, language modeling, speech production and perception, speech enhancement. In audio, transducers, room acoustics, active sound control, human audition, analysis/synthesis/coding of music, and consumer audio. (8) (IEEE Guide for Authors) The scope for the proposed transactions includes SPEECH PROCESSING - Transmission and storage of Speech signals; speech coding; speech enhancement and noise reduction; ...


Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Automation Science and Engineering, IEEE Transactions on

The IEEE Transactions on Automation Sciences and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. We welcome results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Circuits and Systems for Video Technology, IEEE Transactions on

Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...


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Most published Xplore authors for Linear regression

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Xplore Articles related to Linear regression

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Spatial and temporal variability of surface cover at BOREAS using reflectance from a helicopter platform

[{u'author_order': 1, u'affiliation': u'Lab. for Global Remote Sensing Studies, Maryland Univ., College Park, MD, USA', u'full_name': u'S. E. Loechel'}, {u'author_order': 2, u'full_name': u'C. L. Walthall'}, {u'author_order': 3, u'full_name': u'E. B. de Colstoun'}, {u'author_order': 4, u'full_name': u'J. M. Chen'}, {u'author_order': 5, u'full_name': u'B. L. Markham'}] Geoscience and Remote Sensing Symposium, 1996. IGARSS '96. 'Remote Sensing for a Sustainable Future.', International, None

Helicopter-based radiometric measurements of forested sites acquired during the Boreal Ecosystem-Atmosphere Study (BOREAS) were used to examine the spatial, temporal, and spectral variability in surface reflectance and vegetation indices (VI), including the normalized difference vegetation index (NDVI) and the simple ratio (SR), and for comparison with surface cover and fluxes. In this analysis, the sensors, which were employed during all ...


Sparse linear regression for optimizing design parameters of double T-shaped monopole antennas

[{u'author_order': 1, u'affiliation': u'Department of Electrical and Computer Engineering, University of Arizona, Tucson, Arizona, USA', u'full_name': u'Yashika Sharma'}, {u'author_order': 2, u'affiliation': u'Department of Electrical and Computer Engineering, University of Arizona, Tucson, Arizona, USA', u'full_name': u'Junqiang Wu'}, {u'author_order': 3, u'affiliation': u'Department of Electrical and Computer Engineering, University of Arizona, Tucson, Arizona, USA', u'full_name': u'Hao Xin'}, {u'author_order': 4, u'affiliation': u'Department of Mathematics, University of Arizona, Tucson, Arizona, USA', u'full_name': u'Hao Helen Zhang'}] 2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, None

In this paper we propose using sparse linear regression for antenna design optimization. The new method provides an automatic, efficient, and reliable framework to identify optimal design parameters for a reference dual band double T-shaped monopole antenna in order to achieve the best performance in terms of the fractional bandwidth of its two bands.


Discriminant analysis based on exponential possibility distributions

[{u'author_order': 1, u'affiliation': u'Dept. of Ind. Eng., Osaka Prefectural Univ., Sakai, Japan', u'full_name': u'H. Tanaka'}, {u'author_order': 2, u'affiliation': u'Dept. of Ind. Eng., Osaka Prefectural Univ., Sakai, Japan', u'full_name': u'H. Ishibuchi'}, {u'author_order': 3, u'affiliation': u'Dept. of Ind. Eng., Osaka Prefectural Univ., Sakai, Japan', u'full_name': u'S. Yoshikaw'}] Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference, None

The paper deals with an exponential possibility distribution and its application to discriminant analysis. The proposed discriminant analysis is formulated by minimizing the possibility or the necessity measure when two possibility distributions are given. This formulation can be reduced to the well-known eigenvalue problem. An unknown input can be classified by the proposed discriminant rule. Furthermore, this discriminant analysis is ...


Analysis of stochastic gradient algorithms for linear regression problems

[{u'author_order': 1, u'full_name': u'L. Ljung'}] IEEE Transactions on Information Theory, 1984

Parameter estimation problems that can be formulated as linear regressions are quite common in many applications. Recursive (on-line, sequential) estimation of such parameters can be performed using the recursive least squares (RLS) algorithm or a stochastic gradient version of this algorithm. In this paper the convergence properties of the gradient algorithm are analyzed under the assumption that the gain tends ...


Target Setting for Technical Requirements in Time-Stamped Software Quality Function

[{u'author_order': 1, u'affiliation': u'Comput. Sci. Dept., Missouri Univ. of Sci. & Technol., Rolla, MO, USA', u'full_name': u'Xiaoqing Liu'}, {u'author_order': 2, u'affiliation': u'Comput. Sci. Dept., Missouri Univ. of Sci. & Technol., Rolla, MO, USA', u'full_name': u'Praveen Inuganti'}, {u'author_order': 3, u'affiliation': u'Software Eng. Center, Toshiba Corp., Japan', u'full_name': u'Kunio Noguchi'}, {u'author_order': 4, u'affiliation': u'Software Eng. Center, Toshiba Corp., Japan', u'full_name': u'Yuji Kyoya'}] 2010 IEEE 34th Annual Computer Software and Applications Conference, None

Technical requirements are hard to determine in software development. They are often specified subjectively in practice. Poorly determined technical requirements often lead to poor customer satisfaction, cost overrun, and delay in schedule, and poor quality. Quality Function Deployment (QFD) is one of major engineering methods used to elicit customer's needs and transforms them into technical requirements in industry. It has ...


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Educational Resources on Linear regression

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eLearning

No eLearning Articles are currently tagged "Linear regression"

IEEE.tv Videos

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A 20dBm Configurable Linear CMOS RF Power Amplifier for Multi-Standard Transmitters: RFIC Industry Showcase
A High-Efficiency Linear Power Amplifier for 28GHz Mobile Communications in 40nm CMOS: RFIC Interactive Forum 2017
Co-design of Power Amplifier and Dynamic Power Supplies for Radar and Communications Transmitters
Advances in Kernel Methods
Phase Retrieval with Application to Optical Imaging
Provably-Correct Robot Control with LTLMoP, OMPL and ROS
Sparse Fuzzy Modeling - Nikhil R Pal - WCCI 2016
WIE ILC 2015 - Being Fearless: A Keynote with Patty Hatter of Intel
Learning through Deterministic Assignment of Hidden Parameter
Interaction of ferromagnetic and superconducting permanent magnets - superconducting levitation
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Superconducting MAGLEV in Japan - ASC-2014 Plenary series - 13 of 13 - Friday 2014/8/15
A 200um x 200um x 100um, 63nW, 2.4GHz Injectable Fully-Monolithic Wireless BioSensing System: RFIC Industry Showcase 2017
IMS 2014: Broadband Continuous-mode Power Amplifiers

IEEE-USA E-Books

  • Regression Models in Risk Management

    This chapter discusses theory and application of generalized linear regression that minimizes a general error measure of regression residual subject to various constraints on regression coefficients and includes least-squares linear regression, median regression, quantile regression, mixed quantile regression, and robust regression as special cases. Application of generalized linear regression includes examples of financial index tracking, sparse signal reconstruction, therapy treatment planning, collateralized debt obligation, mutual fund return-based style classification, and mortgage pipeline hedging. The chapter introduces risk envelopes and risk identifiers, and also states the error decomposition theorem. It discusses special types of unconstrained and constrained linear regressions encountered in statistical decision problems. Constrained least-squares linear regression is used in an intensity- modulated radiation therapy (IMRT) treatment-planning problem. Robust regression aims to reduce influence of sample outliers on regression parameters, especially when regression error has heavy tails.

  • Feature and Model Transformation

    This chapter contains sections titled: Feature Transformation Techniques Model Transformation Techniques Acoustic Model Combination Summary and Further Reading Principal Symbols

  • Convertibility across Measurement Methods

    This chapter contains sections titled: * Introduction * Overview of Previous Convertibility Studies * A Convertibility Study of an Industry Dataset * FP to Cosmic Convertibility: Issues and Discussion


Standards related to Linear regression

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No standards are currently tagged "Linear regression"