ML Anthology

Kapralov, Michael

11 publications

ICLR 2025 Improved Algorithms for Kernel Matrix-Vector Multiplication Under Sparsity Assumptions Piotr Indyk, Michael Kapralov, Kshiteej Sheth, Tal Wagner
NeurIPS 2025 Streaming Attention Approximation via Discrepancy Theory Ekaterina Kochetkova, Kshiteej Sheth, Insu Han, Amir Zandieh, Michael Kapralov
ICMLW 2024 Improved Algorithms for Kernel Matrix-Vector Multiplication Piotr Indyk, Michael Kapralov, Kshiteej Sheth, Tal Wagner
NeurIPS 2024 On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models Aditya Bhaskara, Agastya Vibhuti Jha, Michael Kapralov, Naren Sarayu Manoj, Davide Mazzali, Weronika Wrzos-Kaminska
NeurIPS 2021 Efficient and Local Parallel Random Walks Michael Kapralov, Silvio Lattanzi, Navid Nouri, Jakab Tardos
AISTATS 2020 Scaling up Kernel Ridge Regression via Locality Sensitive Hashing Amir Zandieh, Navid Nouri, Ameya Velingker, Michael Kapralov, Ilya Razenshteyn
NeurIPS 2019 Efficiently Learning Fourier Sparse Set Functions Andisheh Amrollahi, Amir Zandieh, Michael Kapralov, Andreas Krause
ICML 2017 Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
ICML 2016 How to Fake Multiply by a Gaussian Matrix Michael Kapralov, Vamsi Potluru, David Woodruff
NeurIPS 2011 Prediction Strategies Without Loss Michael Kapralov, Rina Panigrahy
NeurIPS 2009 Factor Modeling for Advertisement Targeting Ye Chen, Michael Kapralov, John Canny, Dmitry Y. Pavlov