LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence
Yedida, Rahul, Saha, Snehanshu, Prashanth, Tejas
Published in Applied intelligence (Dordrecht, Netherlands) (01.03.2021)
Published in Applied intelligence (Dordrecht, Netherlands) (01.03.2021)
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LipGene: Lipschitz Continuity Guided Adaptive Learning Rates for Fast Convergence on Microarray Expression Data Sets
Prashanth, Tejas, Saha, Snehanshu, Basarkod, Sumedh, Aralihalli, Suraj, Dhavala, Soma S, Saha, Sriparna, Aduri, Raviprasad
Published in IEEE/ACM transactions on computational biology and bioinformatics (01.11.2022)
Published in IEEE/ACM transactions on computational biology and bioinformatics (01.11.2022)
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LALR: Theoretical and Experimental validation of Lipschitz Adaptive Learning Rate in Regression and Neural Networks
Saha, Snehanshu, Prashanth, Tejas, Aralihalli, Suraj, Basarkod, Sumedh, Sudarshan, T. S. B, Dhavala, Soma S
Year of Publication 19.05.2020
Year of Publication 19.05.2020
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Journal Article
LALR: Theoretical and Experimental validation of Lipschitz Adaptive Learning Rate in Regression and Neural Networks
Saha, Snehanshu, Prashanth, Tejas, Aralihalli, Suraj, Basarkod, Sumedh, Sudarshan, T.S.B., Dhavala, Soma S
Published in 2020 International Joint Conference on Neural Networks (IJCNN) (01.07.2020)
Published in 2020 International Joint Conference on Neural Networks (IJCNN) (01.07.2020)
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