Mahesh Chandra Mukkamala

Publication Activity (10 Years)

Years Active: 2017-2022
Publications (10 Years): 14

Top Topics

Convex Optimization

Bregman Divergences

Matrix Factorization

Top Venues

SIAM J. Math. Data Sci.

Publications

Mahesh Chandra Mukkamala, Jalal Fadili, Peter Ochs
Global convergence of model function based Bregman proximal minimization algorithms. J. Glob. Optim. 83 (4) (2022)
Mahesh Chandra Mukkamala, Felix Westerkamp, Emanuel Laude, Daniel Cremers, Peter Ochs
Bregman Proximal Gradient Algorithms for Deep Matrix Factorization. SSVM (2021)
Mahesh Chandra Mukkamala, Peter Ochs, Thomas Pock, Shoham Sabach
Convex-Concave Backtracking for Inertial Bregman Proximal Gradient Algorithms in Nonconvex Optimization. SIAM J. Math. Data Sci. 2 (3) (2020)
Mahesh Chandra Mukkamala, Jalal Fadili, Peter Ochs
Global Convergence of Model Function Based Bregman Proximal Minimization Algorithms. CoRR (2020)
Mahesh Chandra Mukkamala, Felix Westerkamp, Emanuel Laude, Daniel Cremers, Peter Ochs
Bregman Proximal Framework for Deep Linear Neural Networks. CoRR (2019)
Quynh Nguyen, Mahesh Chandra Mukkamala, Matthias Hein
On the loss landscape of a class of deep neural networks with no bad local valleys. ICLR (Poster) (2019)
Mahesh Chandra Mukkamala, Peter Ochs, Thomas Pock, Shoham Sabach
Convex-Concave Backtracking for Inertial Bregman Proximal Gradient Algorithms in Non-Convex Optimization. CoRR (2019)
Mahesh Chandra Mukkamala, Peter Ochs
Beyond Alternating Updates for Matrix Factorization with Inertial Bregman Proximal Gradient Algorithms. NeurIPS (2019)
Mahesh Chandra Mukkamala, Peter Ochs
Beyond Alternating Updates for Matrix Factorization with Inertial Bregman Proximal Gradient Algorithms. CoRR (2019)
Quynh Nguyen, Mahesh Chandra Mukkamala, Matthias Hein
Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions. ICML (2018)
Quynh Nguyen, Mahesh Chandra Mukkamala, Matthias Hein
On the loss landscape of a class of deep neural networks with no bad local valleys. CoRR (2018)
Quynh Nguyen, Mahesh Chandra Mukkamala, Matthias Hein
Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions. CoRR (2018)
Mahesh Chandra Mukkamala, Matthias Hein
Variants of RMSProp and Adagrad with Logarithmic Regret Bounds. ICML (2017)
Mahesh Chandra Mukkamala, Matthias Hein
Variants of RMSProp and Adagrad with Logarithmic Regret Bounds. CoRR (2017)