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46 papers · 1 filter
On the choice of the optimal temporal support for audio classification with Pre-trained embeddings
Aurian Quelennec, Michel Olvera, Geoffroy Peeters +1
Current state-of-the-art audio analysis systems rely on pre-trained embedding models, often used off-the-shelf as (frozen) feature extractors. Choosing the best one for a set of ta…
SCoTTi: Save Computation at Training Time with an adaptive framework
Ziyu Lin, Enzo Tartaglione, Van-Tam Nguyen
On-device training is an emerging approach in machine learning where models are trained on edge devices, aiming to enhance privacy protection and real-time performance. However, ed…
Collaborating Foundation Models for Domain Generalized Semantic Segmentation
Yasser Benigmim, Subhankar Roy, Slim Essid +2
Domain Generalized Semantic Segmentation (DGSS) deals with training a model on a labeled source domain with the aim of generalizing to unseen domains during inference. Existing DGS…
Assessing the Threat Level of Software Supply Chains with the Log Model
Luıs Soeiro, Thomas Robert, Stefano Zacchiroli
The use of free and open source software (FOSS) components in all software systems is estimated to be above 90%. With such high usage and because of the heterogeneity of FOSS tools…
Hybrid Quantum Cryptography from Communication Complexity
Francesco Mazzoncini, Balthazar Bauer, Peter Brown +1
We introduce an explicit construction for a key distribution protocol in the Quantum Computational Timelock (QCT) security model, where one assumes that computationally secure encr…
Information-theoretic generalization bounds for learning from quantum data
Matthias Caro, Tom Gur, Cambyse Rouzé +2
Learning tasks play an increasingly prominent role in quantum information and computation. They range from fundamental problems such as state discrimination and metrology over the…