Random Fourier features for kernel ridge regression: Approximation bounds and statistical guarantees H Avron, M Kapralov, C Musco, C Musco, A Velingker, A Zandieh International conference on machine learning, 253-262, 2017 | 191 | 2017 |

Restricted isometry of Fourier matrices and list decodability of random linear codes M Cheraghchi, V Guruswami, A Velingker SIAM Journal on Computing 42 (5), 1888-1914, 2013 | 131 | 2013 |

Oblivious sketching of high-degree polynomial kernels TD Ahle, M Kapralov, JBT Knudsen, R Pagh, A Velingker, DP Woodruff, ... Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020 | 119 | 2020 |

Scalable and differentially private distributed aggregation in the shuffled model B Ghazi, R Pagh, A Velingker arXiv preprint arXiv:1906.08320, 2019 | 107 | 2019 |

On the power of multiple anonymous messages: Frequency estimation and selection in the shuffle model of differential privacy B Ghazi, N Golowich, R Kumar, R Pagh, A Velingker Annual International Conference on the Theory and Applications of …, 2021 | 98 | 2021 |

Exphormer: Sparse transformers for graphs H Shirzad, A Velingker, B Venkatachalam, DJ Sutherland, AK Sinop International Conference on Machine Learning, 31613-31632, 2023 | 86 | 2023 |

Private aggregation from fewer anonymous messages B Ghazi, P Manurangsi, R Pagh, A Velingker Advances in Cryptology–EUROCRYPT 2020: 39th Annual International Conference …, 2020 | 60 | 2020 |

Private robust estimation by stabilizing convex relaxations P Kothari, P Manurangsi, A Velingker Conference on Learning Theory, 723-777, 2022 | 57 | 2022 |

Pure differentially private summation from anonymous messages B Ghazi, N Golowich, R Kumar, P Manurangsi, R Pagh, A Velingker arXiv preprint arXiv:2002.01919, 2020 | 50 | 2020 |

A universal sampling method for reconstructing signals with simple fourier transforms H Avron, M Kapralov, C Musco, C Musco, A Velingker, A Zandieh Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing …, 2019 | 40 | 2019 |

Streaming complexity of approximating max 2csp and max acyclic subgraph V Guruswami, A Velingker, S Velusamy Approximation, Randomization, and Combinatorial Optimization. Algorithms and …, 2017 | 35 | 2017 |

(1+ Ω (1))-Αpproximation to MAX-CUT Requires Linear Space M Kapralov, S Khanna, M Sudan, A Velingker Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete …, 2017 | 33 | 2017 |

Dimension-independent sparse Fourier transform M Kapralov, A Velingker, A Zandieh Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete …, 2019 | 29 | 2019 |

Communication with partial noiseless feedback B Haeupler, P Kamath, A Velingker Approximation, randomization, and combinatorial optimization. Algorithms and …, 2015 | 25 | 2015 |

Affinity-aware graph networks A Velingker, A Sinop, I Ktena, P Veličković, S Gollapudi Advances in Neural Information Processing Systems 36, 2024 | 20 | 2024 |

Bridging the capacity gap between interactive and one-way communication B Haeupler, A Velingker Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete …, 2017 | 20 | 2017 |

Locality-aware graph-rewiring in gnns F Barbero, A Velingker, A Saberi, M Bronstein, F Di Giovanni arXiv preprint arXiv:2310.01668, 2023 | 18 | 2023 |

Linear space streaming lower bounds for approximating CSPs CN Chou, A Golovnev, M Sudan, A Velingker, S Velusamy Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing …, 2022 | 18 | 2022 |

Scaling up kernel ridge regression via locality sensitive hashing A Zandieh, N Nouri, A Velingker, M Kapralov, I Razenshteyn International Conference on Artificial Intelligence and Statistics, 4088-4097, 2020 | 17 | 2020 |

An entropy sumset inequality and polynomially fast convergence to Shannon capacity over all alphabets V Guruswami, A Velingker arXiv preprint arXiv:1411.6993, 2014 | 15 | 2014 |