Workshop · Paris

Generalization for Time Series in Tight Settings: Latency, Inference, Memory, prIvacy and Sustainability (TS-LIMITS)

Name: Generalization for Time Series in Tight Settings: Latency, Inference, Memory, prIvacy and Sustainability (TS-LIMITS)
Start: 2026-12-13T08:30:00+01:00
End: 2026-12-13T18:15:00+01:00
Location: Sorbonne Amphitheater 55A, Paris

When: Sun 13 Dec 2026, 08:30–18:15 CET
Where: Sorbonne Amphitheater 55A
Authors: Aurélie Boisbunon, Rémi Emonet, Valerio Frascolla, Elisa Fromont, Fabio Bonassi, June Sallou
Organisations: Ericsson, Hubert Curien Lab, Intel, Univ. Rennes, Uppsala University, Wageningen University
QRS classification: Safety, fairness and privacy, Time series and forecasting, Efficient and distributed ML systems, Representation and transfer learning

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