Patrick Rebeschini

Patrick Rebeschini

Learning theory, Optimization, Implicit Regularization

I am an Associate Professor in the Department of Statistics at the University of Oxford, and a Tutorial Fellow at University College, Oxford. I work on developing methodologies and theoretical foundations for Machine Learning.

Publications

2020

  • D. Richards , P. Rebeschini , Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent, Journal of Machine Learning Research, vol. 21, no. 34, 1–44, 2020.

2019

  • D. Martı́nez-Rubio , V. Kanade , P. Rebeschini , Decentralized Cooperative Stochastic Bandits, in Advances in Neural Information Processing Systems 32, H. Wallach, H. Larochelle, A. Beygelzimer, F. d’ Alché-Buc, E. Fox, and R. Garnett, Eds. Curran Associates, Inc., 2019, 4529–4540.
  • T. Vaskevicius , V. Kanade , P. Rebeschini , Implicit Regularization for Optimal Sparse Recovery, in Advances in Neural Information Processing Systems 32, H. Wallach, H. Larochelle, A. Beygelzimer, F. d’ Alché-Buc, E. Fox, and R. Garnett, Eds. Curran Associates, Inc., 2019, 2972–2983.
  • D. Richards , P. Rebeschini , Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up, in Advances in Neural Information Processing Systems 32, H. Wallach, H. Larochelle, A. Beygelzimer, F. d’ Alché-Buc, E. Fox, and R. Garnett, Eds. Curran Associates, Inc., 2019, 1216–1227.
  • P. Rebeschini , S. Tatikonda , A new approach to Laplacian solvers and flow problems, Journal of Machine Learning Research, vol. 20, no. 36, 2019.

2017

  • P. Rebeschini , S. C. Tatikonda , Accelerated consensus via Min-Sum Splitting, in Advances in Neural Information Processing Systems 30, I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett, Eds. Curran Associates, Inc., 2017, 1374–1384.

2016

  • P. Rebeschini , S. Tatikonda , Decay of correlation in network flow problems, in 2016 Annual Conference on Information Science and Systems (CISS), 2016, 169–174.

2015

  • P. Rebeschini , R. Handel , Can local particle filters beat the curse of dimensionality?, Ann. Appl. Probab., vol. 25, no. 5, 2809–2866, Oct. 2015.
  • P. Rebeschini , R. Handel , Phase transitions in nonlinear filtering, Electron. J. Probab., vol. 20, 46 pp., 2015.
  • P. Rebeschini , A. Karbasi , Fast Mixing for Discrete Point Processes, in Proceedings of The 28th Conference on Learning Theory, Paris, France, 2015, vol. 40, 1480–1500.

2014

  • P. Rebeschini , R. Handel , Comparison Theorems for Gibbs Measures, Journal of Statistical Physics, vol. 157, no. 2, 234–281, Oct. 2014.