Deepesh Data
7 papers · 2019–2023 · 4 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (4) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (17) π§ Keyword Pioneer π£ Hot Topic Early Bird
π
Cross-Pollinator
(15)
Conferences
NIPS (3)
AISTATS (2)
ICLR (1)
ICML (1)
Top co-authors
Keywords
federated learning
(4)
stochastic gradient descent
(3)
distributed optimization
(3)
differential privacy
(2)
distributed learning
(2)
communication efficiency
(2)
gradient compression
(1)
personalized model
(1)
distributed stochastic gradient descent
(1)
client-server architecture
(1)
privacy amplification
(1)
renyi differential privacy
(1)
error compensation
(1)
gradient quantization
(1)
robust mean estimation
(1)
shuffle model
(1)
local computation
(1)
byzantine resilience
(1)
gradient sparsification
(1)
local iteration
(1)
Papers
A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy
ICLR 2023
Flexible Accuracy for Differential Privacy
AISTATS 2022
Renyi Differential Privacy of The Subsampled Shuffle Model In Distributed Learning
NIPS 2021
Shuffled Model of Differential Privacy in Federated Learning
AISTATS 2021
QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning
NIPS 2021
Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data
ICML 2021
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification and Local Computations
NIPS 2019