Mahalakshmi Sabanayagam

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Debarghya GhoshdastidarTechnical University of MunichVerified email at cit.tum.de
Pascal M. EsserTechnical University of MunichVerified email at in.tum.de
Sivasankar ElangoAssociate Professor ,Department of Computer Science & Engineering ,National Institute of TechnologyVerified email at nitt.edu
SELVI CHANDRANAssistant Professor, Indian Institute of Information Technology Kottayam, KeralaVerified email at iiitkottayam.ac.in
Leena Chennuru VankadaraAmazon Research; Previously University of Tübingen and Max Planck Institute, TübingenVerified email at uni-tuebingen.de
Freya BehrensEPFL, LausanneVerified email at epfl.ch
Anna DawidLeiden UniversityVerified email at liacs.leidenuniv.nl
Urte AdomaitytePhD Student, King's College LondonVerified email at kcl.ac.uk
Satyaki MukherjeeNational University of SingaporeVerified email at nus.edu.sg
Krikamol MuandetCISPA - Helmholtz Center for Information SecurityVerified email at cispa.de
ANURAG SINGHCISPA Helmholtz Center for Information SecurityVerified email at nsit.net.in

Mahalakshmi Sabanayagam

PhD, Technical University of Munich

Verified email at tum.de - Homepage

Statistical Learning Theory Deep Learning Theory Graph based learning


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Rough set-based feature selection for credit risk prediction using weight-adjusted boosting ensemble method E Sivasankar, C Selvi, S Mahalakshmi Soft Computing 24 (6), 3975-3988, 2020	29	2020
Cross domain sentiment analysis using different machine learning techniques S Mahalakshmi, E Sivasankar Proceedings of the Fifth International Conference on Fuzzy and Neuro …, 2015	18	2015
Analysis of Convolutions, Non-linearity and Depth in Graph Neural Networks using Neural Tangent Kernel M Sabanayagam, P Esser, D Ghoshdastidar Transactions on Machine Learning Research 2023, 2022	10*	2022
Graphon based Clustering and Testing of Networks: Algorithms and Theory M Sabanayagam, LC Vankadara, D Ghoshdastidar Tenth International Conference on Learning Representations (ICLR, 2022), 2022	8	2022
New insights into graph convolutional networks using neural tangent kernels M Sabanayagam, P Esser, D Ghoshdastidar arXiv preprint arXiv:2110.04060, 2021	8	2021
Unveiling the Hessian's Connection to the Decision Boundary M Sabanayagam, F Behrens, U Adomaityte, A Dawid arXiv preprint arXiv:2306.07104, 2023	3	2023
Analysis of Graph Convolutional Networks using Neural Tangent Kernels M Sabanayagam, P Esser, D Ghoshdastidar INTERNATIONAL WORKSHOP ON MINING AND LEARNING WITH GRAPHS, 2022	1	2022
Machine learning-based image detection for lensless microscopy in life science J Brunckhorst, A Pirchner, NR Naik, M Sabanayagam, MDK Paul-Yuan, ...	1	2019
Robust Feature Inference: A Test-time Defense Strategy using Spectral Projections A Singh, M Sabanayagam, K Muandet, D Ghoshdastidar Transactions on Machine Learning Research, 2024		2024
Provable Robustness of (Graph) Neural Networks Against Data Poisoning and Backdoor Attacks L Gosch, M Sabanayagam, D Ghoshdastidar, S Günnemann arXiv preprint arXiv:2407.10867, 2024		2024
Kernels, Data & Physics F Cagnetta, D Oliveira, M Sabanayagam, N Tsilivis, J Kempe arXiv preprint arXiv:2307.02693, 2023		2023
Improved Representation Learning Through Tensorized Autoencoders PM Esser, S Mukherjee, M Sabanayagam, D Ghoshdastidar The 26th International Conference on Artificial Intelligence and Statistics …, 2022		2022

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