10 citations · 35 across the 19 of their papers we have counts for
3 papers · 2 filters
A Bayesian nonparametric approach to count-min sketch under power-law data streams
Emanuele Dolera, Stefano Favaro, Stefano Peluchetti
The count-min sketch (CMS) is a randomized data structure that provides estimates of tokens' frequencies in a large data stream using a compressed representation of the data by ran…
Learning-augmented count-min sketches via Bayesian nonparametrics
Emanuele Dolera, Stefano Favaro, Stefano Peluchetti
The count-min sketch (CMS) is a time and memory efficient randomized data structure that provides estimates of tokens' frequencies in a data stream of tokens, i.e. point queries, b…
Infinite-channel deep stable convolutional neural networks
Daniele Bracale, Stefano Favaro, Sandra Fortini +1
The interplay between infinite-width neural networks (NNs) and classes of Gaussian processes (GPs) is well known since the seminal work of Neal (1996). While numerous theoretical r…