Publications

You can find my publications at Google Scholar and Research Gate.

Ph.D. Thesis

Learning a Multiview Weighted Majority Vote Classifier: Using PAC-Bayesian Theory and Boosting, Université de Lyon, October 2018 [Published Version] [Pdf] [Slides]

Nandhinee Periyakaruppan, Harinath Krishnamoorthy, Anil Goyal, Sudarsun Santhiappan, End-to-end system for extracting tabular data present in electronic documents and method thereof, 2022 [US Patent Application]
Tobias Jacobs, A. Goyal, Decentralized multi-task learning, 2020 [US Patent Application]
A. Goyal, Ammar Shaker, Francesco Alesiani, Machine learning knowledge management based on lifelong boosting in presence of less data, 2020 [US Patent Application]
A. Goyal, J. Khiari, Diversity-aware weighted majority vote classifier for imbalanced datasets, 2019 [US Patent Application]

A. Goyal, E. Morvant, P. Germain, M.R. Amini, “Multiview Boosting by Controlling the Diversity and the Accuracy of View-specific Voters”, Neurocomputing, 2019 [Published Version][arXiv] [Code] [Data]

Badal Gupta, Anil Goyal, Chirag Sharma, Divyansh Kumar, RE-RentFraud: A System to detect Frauds in rent payments for Real-Estate properties, CODS-COMAD, 2023 [Published Version]
Prateek Chhikara, Harshul Kuhar, Anil Goyal, Chirag Sharma, DIGITOUR: Automatic Digital Tours for Real-Estate Properties, CODS-COMAD, 2023 [Published Version] [arXiv]
Prateek Chhikara, Anil Goyal, Chirag Sharma, RE-Tagger: A light-weight Real-Estate Image Classifier, ECML-PKDD, 2022 [arXiv] [Demo Video]
A. Goyal, J. Khiari, Diversity-Aware Weighted Majority Vote Classifier for Imbalanced Data, IJCNN, 2020 [Published Version] [arXiv] [Code]
A. Goyal, E. Morvant, M.R. Amini, “Multiview Learning of Weighted Majority Vote by Bregman Divergence Minimization”, IDA, 2018 [Published Version] [arXiv]
A. Goyal, E. Morvant, P. Germain, M.R. Amini, “PAC-Bayesian Analysis for a two-step Hierarchical Mutliview Learning Approach”, ECML-PKDD, 2017 [Published Version] [arXiv]

A. Goyal, E. Morvant, M.R. Amini, “Une borne Apprentissage d’un vote de majorité hiérarchique pour l’apprentissage multivue”, French Conference on Machine Learning (CAp), 2018
A. Goyal, E. Morvant, P. Germain, Une borne PAC-Bayésienne en espérance et son extension à l’apprentissage multivues, French Conference on Machine Learning (CAp), 2017
A. Goyal, E. Morvant, P. Germain, M.R. Amini, Théorèmes PAC-Bayésiens pour l’apprentissage multi-vues, French Conference on Machine Learning (CAp), 2016
A. Goyal, G. Balikas, P. Goswami, M.R. Amini, E. Gaussier, Transfer Learning for IR Model Parameter Tuning, French Conference on Machine Learning (CAp), 2015
A. Goyal, M.K. Jadon, A.K. Pujari, Spectral Approach to find Number of Clusters of Short-text Documents, NCVPRIPG, 2013 [Published Version]