24 citations · 157 across the 42 of their papers we have counts for
6 papers · 1 filter
Fast kernel half-space depth for data with non-convex supports
Arturo Castellanos, Pavlo Mozharovskyi, Florence d'Alché-Buc +1
Data depth is a statistical function that generalizes order and quantiles to the multivariate setting and beyond, with applications spanning over descriptive and visual statistics,…
Towards On-device Learning on the Edge: Ways to Select Neurons to Update under a Budget Constraint
Aël Quélennec, Enzo Tartaglione, Pavlo Mozharovskyi +1
In the realm of efficient on-device learning under extreme memory and computation constraints, a significant gap in successful approaches persists. Although considerable effort has…
Abnormal component analysis
Romain Valla, Pavlo Mozharovskyi, Florence d'Alché-Buc
At the crossway of machine learning and data analysis, anomaly detection aims at identifying observations that exhibit abnormal behaviour. Be it measurement errors, disease develop…
Tailoring Mixup to Data for Calibration
Quentin Bouniot, Pavlo Mozharovskyi, Florence d'Alché-Buc
Among all data augmentation techniques proposed so far, linear interpolation of training samples, also called Mixup, has found to be effective for a large panel of applications. Al…
Tackling Interpretability in Audio Classification Networks with Non-negative Matrix Factorization
Jayneel Parekh, Sanjeel Parekh, Pavlo Mozharovskyi +2
This paper tackles two major problem settings for interpretability of audio processing networks, post-hoc and by-design interpretation. For post-hoc interpretation, we aim to inter…
Optimized preprocessing and Tiny ML for Attention State Classification
Yinghao Wang, Rémi Nahon, Enzo Tartaglione +2
In this paper, we present a new approach to mental state classification from EEG signals by combining signal processing techniques and machine learning (ML) algorithms. We evaluate…