Search Results for author: Francesco Silvestri

Found 7 papers, 3 papers with code

On the Bike Spreading Problem

1 code implementation1 Jul 2021 Elia Costa, Francesco Silvestri

A free-floating bike-sharing system (FFBSS) is a dockless rental system where an individual can borrow a bike and returns it anywhere, within the service area.

Sampling a Near Neighbor in High Dimensions -- Who is the Fairest of Them All?

1 code implementation26 Jan 2021 Martin Aumüller, Sariel Har-Peled, Sepideh Mahabadi, Rasmus Pagh, Francesco Silvestri

Given a set of points $S$ and a radius parameter $r>0$, the $r$-near neighbor ($r$-NN) problem asks for a data structure that, given any query point $q$, returns a point $p$ within distance at most $r$ from $q$.

Fairness

Similarity Search with Tensor Core Units

no code implementations22 Jun 2020 Thomas D. Ahle, Francesco Silvestri

Tensor Core Units (TCUs) are hardware accelerators developed for deep neural networks, which efficiently support the multiplication of two dense $\sqrt{m}\times \sqrt{m}$ matrices, where $m$ is a given hardware parameter.

Dimensionality Reduction

A Computational Model for Tensor Core Units

no code implementations19 Aug 2019 Rezaul Chowdhury, Francesco Silvestri, Flavio Vella

To respond to the need of efficient training and inference of deep neural networks, a plethora of domain-specific hardware architectures have been introduced, such as Google Tensor Processing Units and NVIDIA Tensor Cores.

Fair Near Neighbor Search: Independent Range Sampling in High Dimensions

1 code implementation5 Jun 2019 Martin Aumüller, Rasmus Pagh, Francesco Silvestri

There are several variants of the similarity search problem, and one of the most relevant is the $r$-near neighbor ($r$-NN) problem: given a radius $r>0$ and a set of points $S$, construct a data structure that, for any given query point $q$, returns a point $p$ within distance at most $r$ from $q$.

Fairness

Symmetry-free SDP Relaxations for Affine Subspace Clustering

no code implementations25 Jul 2016 Francesco Silvestri, Gerhard Reinelt, Christoph Schnörr

We consider clustering problems where the goal is to determine an optimal partition of a given point set in Euclidean space in terms of a collection of affine subspaces.

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