Tegjyot Singh Sethi

According to our database, Tegjyot Singh Sethi authored at least 16 papers between 2013 and 2020.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2020

No Free Lunch Theorem for concept drift detection in streaming data classification: A review.

Hanqing Hu, Mehmed M. Kantardzic, Tegjyot Singh Sethi

WIREs Data Mining Knowl. Discov., 2020

2019

Sloppiness mitigation in crowdsourcing: detecting and correcting bias for crowd scoring tasks.

Lingyu Lyu, Mehmed M. Kantardzic, Tegjyot Singh Sethi

Int. J. Data Sci. Anal., 2019

2018

A dynamic-adversarial mining approach to the security of machine learning.

Tegjyot Singh Sethi, Mehmed M. Kantardzic, Lingyu Lyu, Jiashun Chen

WIREs Data Mining Knowl. Discov., 2018

When Good Machine Learning Leads to Bad Security: Big Data (Ubiquity symposium).

Tegjyot Singh Sethi, Mehmed M. Kantardzic

Ubiquity, 2018

Data driven exploratory attacks on black box classifiers in adversarial domains.

Tegjyot Singh Sethi, Mehmed M. Kantardzic

Neurocomputing, 2018

Handling adversarial concept drift in streaming data.

Tegjyot Singh Sethi, Mehmed M. Kantardzic

Expert Syst. Appl., 2018

2017

On the reliable detection of concept drift from streaming unlabeled data.

Tegjyot Singh Sethi, Mehmed M. Kantardzic

Expert Syst. Appl., 2017

'Security Theater': On the Vulnerability of Classifiers to Exploratory Attacks.

Tegjyot Singh Sethi, Mehmed M. Kantardzic, Joung Woo Ryu

Proceedings of the Intelligence and Security Informatics - 12th Pacific Asia Workshop, 2017

A partial labeling framework for multi-class imbalanced streaming data.

Elaheh Arabmakki, Mehmed M. Kantardzic, Tegjyot Singh Sethi

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2016

A grid density based framework for classifying streaming data in the presence of concept drift.

Tegjyot Singh Sethi, Mehmed M. Kantardzic, Hanqing Hu

J. Intell. Inf. Syst., 2016

Monitoring Classification Blindspots to Detect Drifts from Unlabeled Data.

Tegjyot Singh Sethi, Mehmed M. Kantardzic, Elaheh Arabmakki

Proceedings of the 17th IEEE International Conference on Information Reuse and Integration, 2016

Ensemble Classifier for Imbalanced Streaming Data Using Partial Labeling.

Elaheh Arabmakki, Mehmed M. Kantardzic, Tegjyot Singh Sethi

Proceedings of the 17th IEEE International Conference on Information Reuse and Integration, 2016

2015

Don't Pay for Validation: Detecting Drifts from Unlabeled data Using Margin Density.

Tegjyot Singh Sethi, Mehmed M. Kantardzic

Proceedings of the INNS Conference on Big Data 2015, 2015

2014

An ensemble classification approach for handling spatio-temporal drifts in partially labeled data streams.

Tegjyot Singh Sethi, Mehmed M. Kantardzic, Elaheh Arabmakki, Hanqing Hu

Proceedings of the 15th IEEE International Conference on Information Reuse and Integration, 2014

RLS-A reduced labeled samples approach for streaming imbalanced data with concept drift.

Elaheh Arabmakki, Mehmed M. Kantardzic, Tegjyot Singh Sethi

Proceedings of the 15th IEEE International Conference on Information Reuse and Integration, 2014

2013

Selecting samples for labeling in unbalanced streaming data environments.

Hanqing Hu, Mehmed M. Kantardzic, Tegjyot Singh Sethi

Proceedings of the XXIV International Symposium on Information, 2013