106 citations · 525 across the 44 of their papers we have counts for
5 papers · 1 filter
Improved Strongly Adaptive Online Learning using Coin Betting
Kwang-Sung Jun, Francesco Orabona, Rebecca Willett +1
This paper describes a new parameter-free online learning algorithm for changing environments. In comparing against algorithms with the same time complexity as ours, we obtain a st…
Coin Betting and Parameter-Free Online Learning
Francesco Orabona, Dávid Pál
In the recent years, a number of parameter-free algorithms have been developed for online linear optimization over Hilbert spaces and for learning with expert advice. These algorit…
High Dimensional Inference with Random Maximum A-Posteriori Perturbations
Tamir Hazan, Francesco Orabona, Anand D. Sarwate +2
This paper presents a new approach, called perturb-max, for high-dimensional statistical inference that is based on applying random perturbations followed by optimization. This fra…
Solving Ridge Regression using Sketched Preconditioned SVRG
Alon Gonen, Francesco Orabona, Shai Shalev-Shwartz
We develop a novel preconditioning method for ridge regression, based on recent linear sketching methods. By equipping Stochastic Variance Reduced Gradient (SVRG) with this precond…
Scale-Free Online Learning
Francesco Orabona, Dávid Pál
We design and analyze algorithms for online linear optimization that have optimal regret and at the same time do not need to know any upper or lower bounds on the norm of the loss…