24 citations · 45 across the 5 of their papers we have counts for
5 papers
Graph-based Clustering under Differential Privacy
Rafael Pinot, Anne Morvan, Florian Yger +2
In this paper, we present the first differentially private clustering method for arbitrary-shaped node clusters in a graph. This algorithm takes as input only an approximate Minimu…
On the Needs for Rotations in Hypercubic Quantization Hashing
Anne Morvan, Antoine Souloumiac, Krzysztof Choromanski +2
The aim of this paper is to endow the well-known family of hypercubic quantization hashing methods with theoretical guarantees. In hypercubic quantization, applying a suitable (ran…
Graph sketching-based Space-efficient Data Clustering
Anne Morvan, Krzysztof Choromanski, Cédric Gouy-Pailler +1
In this paper, we address the problem of recovering arbitrary-shaped data clusters from datasets while facing \emph{high space constraints}, as this is for instance the case in man…
Structured adaptive and random spinners for fast machine learning computations
Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski +6
We consider an efficient computational framework for speeding up several machine learning algorithms with almost no loss of accuracy. The proposed framework relies on projections v…
TripleSpin - a generic compact paradigm for fast machine learning computations
Krzysztof Choromanski, Francois Fagan, Cedric Gouy-Pailler +3
We present a generic compact computational framework relying on structured random matrices that can be applied to speed up several machine learning algorithms with almost no loss o…