Friedlander, Michael

7 publications

ICLR 2024 Fair and Efficient Contribution Valuation for Vertical Federated Learning Zhenan Fan, Huang Fang, Xinglu Wang, Zirui Zhou, Jian Pei, Michael Friedlander, Yong Zhang

ICLR 2021 Fast Convergence of Stochastic Subgradient Method Under Interpolation Huang Fang, Zhenan Fan, Michael Friedlander

AISTATS 2020 Greed Meets Sparsity: Understanding and Improving Greedy Coordinate Descent for Sparse Optimization Huang Fang, Zhenan Fan, Yifan Sun, Michael Friedlander

ICML 2020 Online Mirror Descent and Dual Averaging: Keeping Pace in the Dynamic Case Huang Fang, Nick Harvey, Victor Portella, Michael Friedlander

ICML 2015 Coordinate Descent Converges Faster with the Gauss-Southwell Rule than Random Selection Julie Nutini, Mark Schmidt, Issam Laradji, Michael Friedlander, Hoyt Koepke

ICML 2013 Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models Mohammad Emtiyaz Khan, Aleksandr Aravkin, Michael Friedlander, Matthias Seeger

AISTATS 2009 Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm Mark Schmidt, Ewout Berg, Michael Friedlander, Kevin Murphy