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2020 – today
- 2024
[j2]Jianyu Wang, Rudrajit Das, Gauri Joshi, Satyen Kale, Zheng Xu, Tong Zhang:
On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data. Trans. Mach. Learn. Res. 2024 (2024)- [c6]Rudrajit Das, Xi Chen, Bertram Ieong, Parikshit Bansal, Sujay Sanghavi:
Understanding the Training Speedup from Sampling with Approximate Losses. ICML 2024 - [i12]Rudrajit Das, Xi Chen, Bertram Ieong, Parikshit Bansal, Sujay Sanghavi:
Understanding the Training Speedup from Sampling with Approximate Losses. CoRR abs/2402.07052 (2024) - [i11]Rudrajit Das, Naman Agarwal, Sujay Sanghavi, Inderjit S. Dhillon:
Towards Quantifying the Preconditioning Effect of Adam. CoRR abs/2402.07114 (2024) - [i10]Rudrajit Das, Inderjit S. Dhillon, Alessandro Epasto, Adel Javanmard, Jieming Mao, Vahab Mirrokni, Sujay Sanghavi, Peilin Zhong:
Retraining with Predicted Hard Labels Provably Increases Model Accuracy. CoRR abs/2406.11206 (2024) - 2023
- [c5]Rudrajit Das, Satyen Kale, Zheng Xu, Tong Zhang, Sujay Sanghavi:
Beyond Uniform Lipschitz Condition in Differentially Private Optimization. ICML 2023: 7066-7101 - [c4]Rudrajit Das, Sujay Sanghavi:
Understanding Self-Distillation in the Presence of Label Noise. ICML 2023: 7102-7140 - [i9]Rudrajit Das, Sujay Sanghavi:
Understanding Self-Distillation in the Presence of Label Noise. CoRR abs/2301.13304 (2023) - 2022
- [j1]Abolfazl Hashemi
, Anish Acharya, Rudrajit Das, Haris Vikalo, Sujay Sanghavi, Inderjit S. Dhillon:
On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Federated Learning. IEEE Trans. Parallel Distributed Syst. 33(11): 2727-2739 (2022) - [c3]Rudrajit Das, Anish Acharya, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu:
Faster non-convex federated learning via global and local momentum. UAI 2022: 496-506 - [i8]Jianyu Wang, Rudrajit Das, Gauri Joshi, Satyen Kale, Zheng Xu, Tong Zhang:
On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data. CoRR abs/2206.04723 (2022) - [i7]Rudrajit Das, Satyen Kale, Zheng Xu, Tong Zhang, Sujay Sanghavi:
Beyond Uniform Lipschitz Condition in Differentially Private Optimization. CoRR abs/2206.10713 (2022) - 2021
- [i6]Rudrajit Das, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon:
DP-NormFedAvg: Normalizing Client Updates for Privacy-Preserving Federated Learning. CoRR abs/2106.07094 (2021) - [i5]Anish Acharya, Rudrajit Das:
DISCO : efficient unsupervised decoding for discrete natural language problems via convex relaxation. CoRR abs/2107.05380 (2021) - 2020
- [i4]Abolfazl Hashemi, Anish Acharya, Rudrajit Das, Haris Vikalo, Sujay Sanghavi, Inderjit S. Dhillon:
On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Optimization. CoRR abs/2011.10643 (2020) - [i3]Rudrajit Das, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon:
Improved Convergence Rates for Non-Convex Federated Learning with Compression. CoRR abs/2012.04061 (2020)
2010 – 2019
- 2019
- [c2]Rudrajit Das, Ajit Rajwade:
Nonlinear Blind Compressed Sensing Under Signal-Dependent Noise. ICIP 2019: 2030-2034 - [i2]Rudrajit Das, Subhasis Chaudhuri:
On the Separability of Classes with the Cross-Entropy Loss Function. CoRR abs/1909.06930 (2019) - 2018
- [c1]Rudrajit Das, Aditya Golatkar, Suyash P. Awate:
Sparse Kernel PCA for Outlier Detection. ICMLA 2018: 152-157 - [i1]Rudrajit Das, Aditya Golatkar, Suyash P. Awate:
Sparse Kernel PCA for Outlier Detection. CoRR abs/1809.02497 (2018)
Coauthor Index
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last updated on 2024-09-04 01:24 CEST by the dblp team
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