Subject
- Mathematics 285
- Biomedical Engineering 2
- Interdisciplinary Research 2
- Life Sciences 2
- Civil Engineering 1
- Communication 1
- Library Science 1
Creator
- Walter Gautschi, 0000-0001-9184-8899 286
- Mireille Boutin, 0000-0002-0837-6577 3
- Bartlomiej P. Rajwa 2
- Courtney Falk 2
- Jonas Hepp 2
- Murat Dundar 2
- Yellamraju Tarun 2
- Adnan Firoze, 0000-0002-2751-009X 1
- Akshaj Uppala 1
- Austin J. Klasa 1
Type
- Dataset 302
Date
subject: Computer Science type: dataset
Total is 302 Results
HPGT: High-precision Gauss-Turan quadrature rules
10.4231/R71V5BW8
04/23/2014
Matlab routines that calculate high-precision Gauss-Turan quadrature rules
Computer Science Gauss-type quadrature rules Hermite weight function Laguerre weight functions Mathematics Matlab Orthogonal polynomials Software source code Variable-precision arithmetic Walter Gautschi Archives
NEUTRAL: Neutralizing nearby singularities in numerical quadrature
10.4231/R75H7D6P
04/23/2014
Matlab routines for neutralizing nearby singularities in numerical quadrature
Computer Science Gaussian quadrature Mathematics Matlab nearby singularities Numerical quadrature Orthogonal polynomials Software source code Walter Gautschi Archives
POEXPINT: Polynomials orthogonal with respect to the exponential integral
10.4231/R7X34VD9
04/28/2014
Matlab scripts for computing orthogonal polynomials whose weight function involves an exponential integral
Computer Science exponential integrals Gaussian quadrature Logarithmic weight functions Mathematics Matlab Orthogonal polynomials Software source code Variable-precision arithmetic Walter Gautschi Archives
Graph of Flickr Photo-Sharing Social Network Crawled in May 2006
10.4231/D39P2W550
02/22/2012
Crawl of the Flickr photo-sharing social network from May 2006 returning a graph with 820,878 nodes and 9,837,214 edges. Dataset is distributed as a SMAT file with README file with code to read file in Python and MATLAB.
Controlling the cost and increasing the utility of network measurement infrastructures
10.4231/D3TH8BM5D
09/13/2012
Dissertation on the cost and utility of network measurement infrastructures, including mechanisms for admission control, identifying measurement patterns that will benefit from inference, and selecting vantage points for wide-scale measurement.
Simplicity of K-means versus deepness of Deep Learning. A Case of Unsupervised Feature Learning with Limited Data
10.4231/R7N58J9Z
Baichuan Zhang , Bartlomiej P. Rajwa , Murat Dundar , Qiang Kou , Yicheng He
10/01/2015
A study contrasting K-means-based unsupervised feature learning and deep learning techniques for small data sets with limited intra- as well as inter-class diversity
bacterial colonies BARDOT Biomedical Engineering Computer Science deep learning Elastic light scattering Interdisciplinary Research K-Means Clustering Life Sciences Machine Learning representation learning
HUBbub 2013 Survey Data
10.4231/R7JD4TQM
08/31/2015
A CSV and accompanying HTML zip file of data taken at a survey about data sharing during HUBbub 2013.
Source code for the paper Polynomial Fitting Known Plaintext Attack
10.4231/R7GH9FWM
11/20/2015
This file contains C++ source code for the numerical experiments described in the paper Polynomial Fitting Known Plaintext Attack.
Computer Science cryptanalysis encryption Information Security known plaintext attack polynomial fitting
OPCBSPL: Orthogonal polynomials relative to cardinal B-spline weight functions
10.4231/R7NG4NKC
10/28/2016
A stable and efficient discretization procedure is developed to compute recurrence coefficients for orthogonal polynomials whose weight function is a polynomial cardinal B-spline of order greater than, or equal to, one.
B-spline Computer Science Mathematics Modification algorithms for orthogonal polynomials Orthogonal polynomials polynomials Walter Gautschi Archives weight functions
Code and Dataset for Pattern Recognition Benchmarks
10.4231/R7610X8M
Jonas Hepp
,
Mireille Boutin
,
Yellamraju Tarun
02/03/2016
This code computed a sequence of bounds for the error rate of a pattern recognition method. The bounds correspond to the error rate that one would expect to achieve by simply selecting features at random and thresholding the feature (TARP) approach.
classification Computer Science Electrical and Computer Engineering feature evaluation image processing image recognition Pattern Recognition Pedestrian Classification
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