Payel Sadhukhan

According to our database, Payel Sadhukhan authored at least 21 papers between 2016 and 2024.

Collaborative distances:

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

2024

Natural-neighborhood based, label-specific undersampling for imbalanced, multi-label data.

Payel Sadhukhan, Sarbani Palit

Adv. Data Anal. Classif., September, 2024

Approximate DBSCAN on obfuscated data.

Payel Sadhukhan, Labani Halder, Sarbani Palit

J. Inf. Secur. Appl., February, 2024

Footprints of Data in a Classifier Model: The Privacy Issues and Their Mitigation through Data Obfuscation.

Payel Sadhukhan, Tanujit Chakraborty

CoRR, 2024

Explainable AI Using the Wasserstein Distance.

Shion Samadder Chaudhury, Payel Sadhukhan, Kausik Sengupta

IEEE Access, 2024

Parameter-Free Undersampling for Multi-Label Data.

Sarbani Palit, Payel Sadhukhan

Proceedings of the 16th International Conference on Agents and Artificial Intelligence, 2024

Knowing the class distinguishing abilities of the features, to build better decision-making models.

Payel Sadhukhan, Kausik Sengupta, Sarbani Palit, Tanujit Chakraborty

Proceedings of the 30th Americas Conference on Information Systems: Elevating Life through Digital Social Entrepreneurship, 2024

Deploying model obfuscation: towards the privacy of decision-making models on shared platforms.

Payel Sadhukhan, Tanujit Chakraborty, Kausik Sengupta

Proceedings of the 30th Americas Conference on Information Systems: Elevating Life through Digital Social Entrepreneurship, 2024

2023

Oversampling the minority class using a dedicated fitness function and genetic algorithmic progression.

Payel Sadhukhan, Sarbani Palt

Concurr. Comput. Pract. Exp., 2023

Integrating Unsupervised Clustering and Label-Specific Oversampling to Tackle Imbalanced Multi-Label Data.

Payel Sadhukhan, Arjun Pakrashi, Sarbani Palit, Brian Mac Namee

Proceedings of the 15th International Conference on Agents and Artificial Intelligence, 2023

2022

Random Walk-steered Majority Undersampling.

Payel Sadhukhan, Arjun Pakrashi, Brian Mac Namee

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2022

Be Informed of the Known to Catch the Unknown.

Payel Sadhukhan, Sarbani Palit

Proceedings of the PRICAI 2023: Trends in Artificial Intelligence, 2022

Exploring the Pertinence of Distance Functions for Nominal Multi-label Data.

Payel Sadhukhan

Proceedings of the Artificial Intelligence Applications and Innovations, 2022

2021

Multi-label learning on principles of reverse k-nearest neighbourhood.

Payel Sadhukhan, Sarbani Palit

Expert Syst. J. Knowl. Eng., 2021

ML-NCA: Multi-label Neighbourhood Component Analysis.

Arjun Pakrashi, Payel Sadhukhan, Brian Mac Namee

Proceedings of the Third International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2021

2020

Adaptive learning of minority class prior to minority oversampling.

Payel Sadhukhan, Sarbani Palit

Pattern Recognit. Lett., 2020

Lattice and Imbalance Informed Multi-Label Learning.

Payel Sadhukhan, Sarbani Palit

IEEE Access, 2020

Can Reverse Nearest Neighbors Perceive Unknowns?

Payel Sadhukhan

IEEE Access, 2020

2019

Reverse-nearest neighborhood based oversampling for imbalanced, multi-label datasets.

Payel Sadhukhan, Sarbani Palit

Pattern Recognit. Lett., 2019

Learning Minority Class prior to Minority Oversampling.

Payel Sadhukhan

Proceedings of the International Joint Conference on Neural Networks, 2019

2017

Multi-label Learning Through Minimum Spanning Tree-Based Subset Selection and Feature Extraction.

Payel Sadhukhan, C. A. Murthy

Proceedings of the Advances in Artificial Intelligence, 2017

2016

Fast Autonomous Crater Detection by Image Analysis-For Unmanned Landing on Unknown Terrain.

Payel Sadhukhan, Sarbani Palit

Proceedings of the Image and Signal Processing - 7th International Conference, 2016