'High dimensional' presentation slideshows

High Dimensional Data Analysis

The Sixth Sino-Japan-Korea Bioinformatics Training Course Yu Shyr ( ? ? ), Ph.D. March 30, 2007 Yu.Shyr@vanderbilt.edu. High Dimensional Data Analysis. Shyr, Yu ( ? ? ) , Ph.D. Ingram Distinguished Professor of Cancer Research Director

1.4k views • 99 slides

Statistical Analyses of Life Science and Pathology from Genomic Perspective

Statistical Analyses of Life Science and Pathology from Genomic Perspective. Unit of Statistical Genetics, Kyoto University Ryo Yamada ryamada@genome.med.kyoto-u.ac.jp. Roles of statistics/data science for genome/omics. Quality Control of Noisy High-Throughput Data

642 views • 64 slides

Yu Shyr ( ? ? ), Ph.D. May 14, 2008 China Medical University Yu.Shyr@vanderbilt

Yu Shyr ( ? ? ), Ph.D. May 14, 2008 China Medical University Yu.Shyr@vanderbilt.edu. The Biostatistical & Bioinformatics Challenges in the High Dimensional Data Derived from High Throughput Assays: Today and Tomorrow. Vanderbilt University ?????.

781 views • 63 slides

Monte Carlo Integration

921 views • 59 slides

Monte Carlo Integration

598 views • 59 slides

Classification

Classification. 10/03/07. Diagnose disease by gene expression pattern. Golub et al. 1999. Diagnose disease by gene expression pattern. Golub et al. 1999. Two types of statistical learning. Supervised

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The MusicExplorer Project: Mapping the World of Music

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Agenda

Agenda. Dimension reduction Principal component analysis (PCA) Multi-dimensional scaling (MDS) Microarray visualization. Why Dimension Reduction. Computation: The complexity grows exponentially with the dimension. Visualization: projection of high-dimensional data to 2D or 3D.

568 views • 42 slides

Pattern Recognition and Machine Learning Deep Alternative Architectures

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Mode-detection via Median-shift

Lior Shapira, Tel-Aviv University. Mode-detection via Median-shift. Joint work with Shai Avidan , Adobe Inc. Ariel Shamir, Interdisciplinary Center, Herzliya. Clustering. An important problem Vision and Image processing Segmentation Tracking Classification (images, textures etc.)

478 views • 34 slides

Fast mining of distance-based outliers in high-dimensional datasets

Fast mining of distance-based outliers in high-dimensional datasets. Amol Ghoting, Srinivasan Parthasarathy, Matthew Eric Otey Data Mining and Knowledge Discovery Vol. 16 No. 3, 2008. Reporter : CHENG-WEI, CHOU Jan. 13 2010. ????? 89721002 ??? ???. Outline.

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Overview

Overview. Earlier lecture Statistical sampling and Monte Carlo integration Last lecture Signal processing view of sampling Today Variance reduction Importance sampling Stratified sampling Multidimensional sampling patterns Discrepancy and Quasi-Monte Carlo Latter

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Real-time optimization of neurophysiology experiments

Real-time optimization of neurophysiology experiments. Jeremy Lewi 1 , Robert Butera 1 , Liam Paninski 2 1 Department of Bioengineering, Georgia Institute of Technology, 2. Department of Statistics, Columbia University. Neural Encoding. The neural code: what is P( response | stimulus )

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SEED Center for Data Farming Overview

http://harvest.nps.edu. SEED Center for Data Farming Overview. Tom Lucas and Susan Sanchez Operations Research Department Naval Postgraduate School Monterey, CA.

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Announcements

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Support Vector Machine basierte Klassifikation und Regression in der Geofernerkundung

Support Vector Machine basierte Klassifikation und Regression in der Geofernerkundung. Andreas Rabe* Sebastian van der Linden Benjamin Jakimow Patrick Hostert. * andreas.rabe@geo.hu-berlin.de. 26. Oktober 2011. Support Vector Machines (SVMs) What would be of interest for the audience?.

317 views • 19 slides

Scientific Data Management Center (SDM-ISIC) Arie Shoshani Computing Sciences Directorate

Scientific Data Management Center (SDM-ISIC) Arie Shoshani Computing Sciences Directorate Lawrence Berkeley National Laboratory http://sdm.lbl.gov/sdmcenter. Participants. Center Director: Arie Shoshani DOE Laboratories: ANL: Bill Gropp <gropp@mcs.anl.gov> (coordinating PI)

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https://www.edocr.com/v/0ba11o4g/edukite/Certificate-In-High-Dimensional-Statistics-Edukite

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Booster in High Dimensional Data Classification

Classification issues in high dimensional information with modest number of perceptions are ending up additional normal particularly in microarray data. The increasing measure of content data on the Internet pages influences the grouping analysis 1 . The content grouping is a great examination method utilized for dividing an enormous measure of data into groups. Henceforth, the significant issue that influences the content grouping method is the nearness uninformative and inadequate highlights in content reports. A wide class of boosting calculations can be translated as performing coordinate wise angle drop to limit some potential capacity of the edges of an information set 1 . This paper proposes another assessment measure Q measurement that joins the solidness of the chose highlight subset in expansion to the expectation precision. At that point we propose the Booster of a FS calculation that lifts the estimation of the Qstatistic of the calculation connected. Paruchuri Geethika | Voleti Prasanthi "Booster in High Dimensional Data Classification" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: https://www.ijtsrd.com/papers/ijtsrd11368.pdf Paper URL: http://www.ijtsrd.com/computer-science/other/11368/booster-in-high-dimensional-data-classification/paruchuri-geethika

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Impact and Champions

Modeling and Simulation of High Dimensional Stochastic Multiscale PDE Systems at the Exascale. IMD. Novel Ideas. Development of m ulti-output Gaussian process model for stochastic problem with discontinuity in the parametric space.

103 views • 1 slides