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FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks.

B. Song, P. Khanduri, X. Zhang, J. Yi, and M. Hong. ICML, volume 202 of Proceedings of Machine Learning Research, page 32304-32330. PMLR, (2023)

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Prashant Sinha

Intermediate states in bivalent ion induced shrinking of polyacrylate coils on surfaces and in solutionP. Sinha. TU Dresden, (2009)

Prashant Duraphe

Prashant Khapane

Prashant Batra

Prashant Gogia

Other publications of authors with the same name

An Implicit Gradient-Type Method for Linearly Constrained Bilevel Problems.I. Tsaknakis, P. Khanduri, and M. Hong. ICASSP, page 5438-5442. IEEE, (2022)On Sequential Random Distortion Testing of Non-Stationary Processes.P. Khanduri, D. Pastor, V. Sharma, and P. Varshney. ICASSP, page 3944-3948. IEEE, (2018)On Distributed Stochastic Gradient Descent for Nonconvex Functions in the Presence of Byzantines.S. Bulusu, P. Khanduri, P. Sharma, and P. Varshney. ICASSP, page 3137-3141. IEEE, (2020)Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization.Y. Zhang, G. Zhang, P. Khanduri, M. Hong, S. Chang, and S. Liu. CoRR, (2021)A Momentum-Assisted Single-Timescale Stochastic Approximation Algorithm for Bilevel Optimization.P. Khanduri, S. Zeng, M. Hong, H. Wai, Z. Wang, and Z. Yang. CoRR, (2021)FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks.B. Song, P. Khanduri, X. Zhang, J. Yi, and M. Hong. ICML, volume 202 of Proceedings of Machine Learning Research, page 32304-32330. PMLR, (2023)FedAvg for Minimizing Polyak-Łojasiewicz Objectives: The Interpolation Regime.S. M., P. Khanduri, and B. Bharath. ACSSC, page 607-613. IEEE, (2023)Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation.H. Yang, P. Qiu, P. Khanduri, M. Fang, and J. Liu. CoRR, (2024)Byzantine Resilient Non-Convex SVRG with Distributed Batch Gradient Computations.P. Khanduri, S. Bulusu, P. Sharma, and P. Varshney. CoRR, (2019)Joint Collaboration and Compression Design for Random Signal Detection in Wireless Sensor Networks.X. Cheng, B. Geng, P. Khanduri, B. Chen, and P. Varshney. IEEE Signal Process. Lett., (2021)

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Disambiguation of "Khanduri, Prashant"

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FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks.

Please choose a person to relate this publication to

Prashant Sinha

Prashant Duraphe

Prashant Khapane

Prashant Batra

Prashant Gogia

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Khanduri, Prashant"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks.

Please choose a person to relate this publication to

Prashant Sinha

Prashant Duraphe

Prashant Khapane

Prashant Batra

Prashant Gogia

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks.