Keith Rush
Publications by Year
Research Areas
Privacy-Preserving Technologies in Data, Stochastic Gradient Optimization Techniques, Mathematical functions and polynomials, Sparse and Compressive Sensing Techniques, Random Matrices and Applications
Most-Cited Works
- → Improving Federated Learning Personalization via Model Agnostic Meta Learning(2019)368 cited
- → Adaptive Federated Optimization(2020)128 cited
- → Federated Reconstruction: Partially Local Federated Learning(2021)24 cited
- → Does Federated Dropout actually work?(2022)21 cited
- (Nearly) Dimension Independent Private ERM with AdaGrad Rates\{via Publicly Estimated Subspaces(2021)
- Dimension Independence in Unconstrained Private ERM via Adaptive Preconditioning.(2020)
- → Orthogonal Polynomials on the Circle for the Weight w Satisfying Conditions $$w,w^{-1}\in \mathrm{BMO}$$ w , w - 1 ∈ BMO(2016)9 cited
- → Fast Dimension Independent Private AdaGrad on Publicly Estimated Subspaces(2020)9 cited
- → Modeling economic and carbon consequences of a shift to wood-based energy in a rural ‘cluster’; a network analysis in southeast Alaska(2014)7 cited
- → Multi-Epoch Matrix Factorization Mechanisms for Private Machine Learning(2022)6 cited