フォロー
Mahesh Chandra Mukkamala
Mahesh Chandra Mukkamala
Consultant
確認したメール アドレス: math.uni-tuebingen.de - ホームページ
タイトル
引用先
引用先
年
Variants of RMSProp and Adagrad with Logarithmic Regret Bounds
MC Mukkamala, M Hein
ICML 2017, 2017
3272017
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
862019
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
562020
Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions
Q Nguyen, MC Mukkamala, M Hein
ICML 2018, 2018
522018
Beyond Alternating Updates for Matrix Factorization with Inertial Bregman Proximal Gradient Algorithms
MC Mukkamala, P Ochs
NeurIPS 2019, 2019
272019
Bregman proximal framework for deep linear neural networks
MC Mukkamala, F Westerkamp, E Laude, D Cremers, P Ochs
arXiv preprint arXiv:1910.03638, 2019
102019
Global convergence of model function based Bregman proximal minimization algorithms
MC Mukkamala, J Fadili, P Ochs
Journal of Global Optimization, 1-29, 2022
82022
Bregman Proximal Gradient Algorithms for Deep Matrix Factorization
MC Mukkamala, F Westerkamp, Laude, Emanuel, D Cremers, P Ochs
Scale Space and Variational Methods in Computer Vision: 8th International …, 0
1*
Bregman proximal minimization algorithms, analysis and applications
MC Mukkamala
Universität Tübingen, 2022
2022
Cocain Bpg Matrix Factorization
MC Mukkamala, P Ochs
2019
現在システムで処理を実行できません。しばらくしてからもう一度お試しください。
論文 1–10