'Smoothing' presentation slideshows

1.46k views • 83 slides

Data Analysis framework in Brain Imaging STAT 992: Image Analysis March 23, 2004 Moo K. Chung

Data Analysis framework in Brain Imaging STAT 992: Image Analysis March 23, 2004 Moo K. Chung Department of Statistics Department of Biostatistics and Medical Informatics W.M. Keck Brain Laboratory University of Wisconsin-Madison http://www.stat.wisc.edu/~mchung. Acknowledgement:

931 views • 74 slides

Language modeling: Smoothing

670 views • 58 slides

Lecture 4: Smoothing for Language Models

Lecture 4: Smoothing for Language Models. CSCI 544: Applied Natural Language Processing Nanyun (Violet) Peng. based on slides of Jason Eisner. Never trust a sample under 30. 20. 200. 2000000. 2000. Never trust a sample under 30. Smooth out the bumpy histograms to look more like the truth

1.13k views • 46 slides

Enhancement-Retreatment

Enhancement-Retreatment. F.FAZEL Feiz Hospital. Refractive stability. - Usually 1-3 months after operation - The lower the correction, the sooner refraction will be stable myopia < -3 D : 1 month myopia 3-6 D : 2 months myopia > -6 D : 3 months. Why Retreatment ?.

811 views • 40 slides

A Proxy Smoothing Service for Variable-Bit-Rate Streaming Video

A Proxy Smoothing Service for Variable-Bit-Rate Streaming Video. Jennifer Rexford AT&T Labs - Research Florham Park NJ. http://www.research.att.com/~jrex. Joint work with Subhabrata Sen, Don Towsley, and Andrea Basso. Outline. Background and motivation

492 views • 40 slides

Andrew Nealen TU Berlin Takeo Igarashi The University of Tokyo / PRESTO JST Olga Sorkine

Laplacian Mesh Optimization. Andrew Nealen TU Berlin Takeo Igarashi The University of Tokyo / PRESTO JST Olga Sorkine Marc Alexa TU Berlin. What is it ?. Overview. Motivation Problem formulation Laplacian mesh processing basics Laplacian mesh optimization framework Applications

551 views • 38 slides

BABS 502 Moving Averages, Decomposition and Exponential Smoothing Revised March 14, 2010

BABS 502 Moving Averages, Decomposition and Exponential Smoothing Revised March 14, 2010. Moving Averages. F t (1) is average of last m observations Issue is to choose m Most appropriate if series is random variation around a mean This is the case if all autocorrelations are near zero

459 views • 33 slides

2nd YOUNGER MEMBERS CONVENTION

abcd. 2nd YOUNGER MEMBERS CONVENTION. 1-2 December 2003 Moat House, Glasgow. abcd. Developing a New Style With-Profits Product in the Post Sandler World. James Crispin. What is With Profits? Sandler Review HMT Stakeholder WP Are these funds With profits

430 views • 33 slides

Self Stabilizing Smoothing and Counting

Self Stabilizing Smoothing and Counting. Maurice Herlihy, Brown University Srikanta Tirthapura, Iowa State University. Overview. Smoothing and Counting Networks Analysis of behavior without proper initialization - upper and lower bounds Self stabilization of smoothing networks.

435 views • 31 slides

Aquarius Level 3 Processing

493 views • 31 slides

Language Models

Language Models. Hongning Wang CS@UVa. Relevance. P(d ? q) or P(q ? d) Probabilistic inference. ? (Rep(q), Rep(d)) Similarity. P(r=1|q,d) r ?{0,1} Probability of Relevance. Regression Model (Fox 83). Generative Model. Different inference system. Different

444 views • 31 slides

Flexible smoothing with B-splines and Penalties or P-splines

Flexible smoothing with B-splines and Penalties or P-splines. P-splines = B-splines + Penalization Applications : Generalized Linear and non linear Modelling ; Density smoothing P-splines have their grounding in Classical regression methods and Generalized linear models

526 views • 26 slides

ADVANCED INTERDISCIPLINARY DATA ASSIMILATION: FILTERING AND SMOOTHING VIA ESSE

ADVANCED INTERDISCIPLINARY DATA ASSIMILATION: FILTERING AND SMOOTHING VIA ESSE P.F.J. Lermusiaux, A.R. Robinson, P.J.H. Haley and W.G. Leslie OCEANS 2002, Biloxi, MS, Oct. 29, 2002. ERROR SUBSPACE STATISTICAL ESTIMATION (ESSE) PHYSICAL SMOOTHING IN THE LEVANTINE SEA

341 views • 23 slides

8 th Atmospheric Composition Constellation Meeting (ACC-8), 18-19 April 2012, Columbia, MD

8 th Atmospheric Composition Constellation Meeting (ACC-8), 18-19 April 2012, Columbia, MD Smoothing and Sampling Issues Affecting Data Comparisons Jean-Christopher Lambert (1)

292 views • 21 slides

Cartographic quality contouring in PHOTOMOD 5.0

X th International Scientific and Technical Conference From Imagery to Map: Digital Photogrammetric Technologies. Cartographic quality contouring in PHOTOMOD 5.0. A. Sechin Scientific Director. September 20 10 , Gaeta , Italy. PHOTOMOD 5.0 today. Main changes for the last year.

376 views • 20 slides

Sensor Data Management: Challenges and (some) Solutions

Sensor Data Management: Challenges and (some) Solutions. Amol Deshpande, University of Maryland. RFID. Distributed measurement networks (e.g. GPS). Wireless sensor networks. Industrial Monitoring. Motivation. Unprecedented, and rapidly increasing, instrumentation of our every-day world.

269 views • 14 slides

LS1 activities for the SPS Complex

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Exponential Smoothing

Exponential Smoothing. All statistical fitting methods involve some type of smoothing e.g., in regression, a trend line is fitter to the data points Consider the following forecasting scheme f t = wy t-1 + (1-w)f t-1 or, if you update by one period f t+1 = wy t + (1-w)f t

259 views • 5 slides

Software: a stand alone program using ITK and an ITK filter

Team. Xiaodong Tao, GE Dennis Jen, MGH. Angular smoothing and interpolation of DW MRI Develop an ITK filter to smooth and interpolate DW MR measurements angularly. Plan/Expected Challenges/Publication. Goals. Develop an ITK filter to smooth and interpolate DW MR measurements angularly;

92 views • 1 slides