Mahesh Chandra Mukkamala
Mahesh Chandra Mukkamala
Mathematical Optimization Group, University of Tübingen
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Variants of RMSProp and Adagrad with Logarithmic Regret Bounds
MC Mukkamala, M Hein
ICML 2017, 2017
On the loss landscape of a class of deep neural networks with no bad local valleys
Q Nguyen, MC Mukkamala, M Hein
ICLR 2019, 2019
Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions
Q Nguyen, MC Mukkamala, M Hein
ICML 2018, 2018
Convex-Concave backtracking for inertial Bregman proximal gradient algorithms in nonconvex optimization
MC Mukkamala, P Ochs, T Pock, S Sabach
SIAM Journal on Mathematics of Data Science 2 (3), 658-682, 2020
Beyond Alternating Updates for Matrix Factorization with Inertial Bregman Proximal Gradient Algorithms
MC Mukkamala, P Ochs
NeurIPS 2019, 2019
Bregman proximal framework for deep linear neural networks
MC Mukkamala, F Westerkamp, E Laude, D Cremers, P Ochs
arXiv preprint arXiv:1910.03638, 2019
Global Convergence of Model Function Based Bregman Proximal Minimization Algorithms
MC Mukkamala, J Fadili, P Ochs
arXiv preprint arXiv:2012.13161, 2020
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