Search Results for author: Arin Chaudhuri

Found 13 papers, 3 papers with code

Visualizing the Finer Cluster Structure of Large-Scale and High-Dimensional Data

no code implementations17 Jul 2020 Yu Liang, Arin Chaudhuri, Haoyu Wang

Dimension reduction and visualization of high-dimensional data have become very important research topics because of the rapid growth of large databases in data science.

Dimensionality Reduction

Automatic Hyperparameter Tuning Method for Local Outlier Factor, with Applications to Anomaly Detection

1 code implementation1 Feb 2019 Zekun Xu, Deovrat Kakde, Arin Chaudhuri

In recent years, there have been many practical applications of anomaly detection such as in predictive maintenance, detection of credit fraud, network intrusion, and system failure.

Anomaly Detection

A New SVDD-Based Multivariate Non-parametric Process Capability Index

no code implementations13 Nov 2018 Deovrat Kakde, Arin Chaudhuri, Diana Shaw

Process capability index (PCI) is a commonly used statistic to measure ability of a process to operate within the given specifications or to produce products which meet the required quality specifications.

The Mean and Median Criterion for Automatic Kernel Bandwidth Selection for Support Vector Data Description

no code implementations16 Aug 2017 Arin Chaudhuri, Deovrat Kakde, Carol Sadek, Laura Gonzalez, Seunghyun Kong

The computation of the SVDD classifier requires a kernel function, and the Gaussian kernel is a common choice for the kernel function.

Online Robust Principal Component Analysis with Change Point Detection

2 code implementations19 Feb 2017 Wei Xiao, Xiaolin Huang, Jorge Silva, Saba Emrani, Arin Chaudhuri

Robust PCA methods are typically batch algorithms which requires loading all observations into memory before processing.

Change Point Detection Two-sample testing

Kernel Bandwidth Selection for SVDD: Peak Criterion Approach for Large Data

no code implementations31 Oct 2016 Sergiy Peredriy, Deovrat Kakde, Arin Chaudhuri

When training datasets are large, the time required to obtain the optimal value of the Gaussian kernel bandwidth parameter according to Peak method can become prohibitively large.

Outlier Detection

Leveraging Unstructured Data to Detect Emerging Reliability Issues

no code implementations26 Jul 2016 Deovrat Kakde, Arin Chaudhuri

However, there is a delay between the time of a customer complaint and the time of a failure or a claim.

A Non-Parametric Control Chart For High Frequency Multivariate Data

no code implementations25 Jul 2016 Deovrat Kakde, Sergriy Peredriy, Arin Chaudhuri, Anya Mcguirk

The non-parametric K-chart provides an attractive alternative to the traditional control charts such as the Hotelling's $T^2$ charts when distribution of the underlying multivariate data is either non-normal or is unknown.

Outlier Detection

Sampling Method for Fast Training of Support Vector Data Description

no code implementations16 Jun 2016 Arin Chaudhuri, Deovrat Kakde, Maria Jahja, Wei Xiao, Hansi Jiang, Seunghyun Kong, Sergiy Peredriy

Support Vector Data Description (SVDD) is a popular outlier detection technique which constructs a flexible description of the input data.

Outlier Detection

Peak Criterion for Choosing Gaussian Kernel Bandwidth in Support Vector Data Description

no code implementations17 Feb 2016 Deovrat Kakde, Arin Chaudhuri, Seunghyun Kong, Maria Jahja, Hansi Jiang, Jorge Silva

For example, it is observed that with a Gaussian kernel, as the value of kernel bandwidth is lowered, the data boundary changes from spherical to wiggly.

General Classification Outlier Detection

Cannot find the paper you are looking for? You can Submit a new open access paper.