Archivio Istituzionale della RicercaNADALINI, DAVIDE
NADALINI, DAVIDE
Dipartimento di Automatica e Informatica
091483
Compressed Latent Replays for Lightweight Continual Learning on Spiking Neural Networks
2024 Dequino, Alberto; Carpegna, Alessio; Nadalini, Davide; Savino, Alessandro; Benini, Luca; Di Carlo, Stefano; Conti, Francesco
Structured Sparse Back-propagation for Lightweight On-Device Continual Learning on Microcontroller Units
2024 Paissan, Francesco; Nadalini, Davide; Rusci, Manuele; Ancilotto, Alberto; Conti, Francesco; Benini, Luca; Farella, Elisabetta
Reduced precision floating-point optimization for Deep Neural Network On-Device Learning on microcontrollers
2023 Nadalini, Davide; Rusci, Manuele; Benini, Luca; Conti, Francesco
PULP-TrainLib: Enabling On-Device Training for RISC-V Multi-core MCUs Through Performance-Driven Autotuning
2022 Nadalini, Davide; Rusci, Manuele; Tagliavini, Giuseppe; Ravaglia, Leonardo; Benini, Luca; Conti, Francesco
A TinyML Platform for On-Device Continual Learning with Quantized Latent Replays
2021 Ravaglia, Leonardo; Rusci, Manuele; Nadalini, Davide; Capotondi, Alessandro; Conti, Francesco; Benini, Luca
| Citazione | Data di pubblicazione | Autori | File |
|---|---|---|---|
| Compressed Latent Replays for Lightweight Continual Learning on Spiking Neural Networks / Dequino, Alberto; Carpegna, Alessio; Nadalini, Davide; Savino, Alessandro; Benini, Luca; Di Carlo, Stefano; Conti, Francesco. - ELETTRONICO. - 1:(2024), pp. 240-245. (Intervento presentato al convegno 2024 IEEE Computer Society Annual Symposium on VLSI (ISVLSI) tenutosi a Knoxville, TN (USA) nel 01-03 July 2024) [10.1109/isvlsi61997.2024.00052]. | 1-gen-2024 | Dequino, AlbertoCarpegna, AlessioNadalini, DavideSavino, AlessandroDi Carlo, Stefano + | Compressed_Latent_Replays_for_Lightweight_Continual_Learning_on_Spiking_Neural_Networks.pdf; Continual_Spiking_Prosciutti_Revival__ISVLSI_.pdf |
| Structured Sparse Back-propagation for Lightweight On-Device Continual Learning on Microcontroller Units / Paissan, Francesco; Nadalini, Davide; Rusci, Manuele; Ancilotto, Alberto; Conti, Francesco; Benini, Luca; Farella, Elisabetta. - (2024), pp. 2172-2181. (Intervento presentato al convegno 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) tenutosi a Seattle, WA (USA) nel 17-18 June 2024) [10.1109/CVPRW63382.2024.00222]. | 1-gen-2024 | Davide NadaliniFrancesco ContiLuca BeniniElisabetta Farella + | Structured_Sparse_Back-propagation_for_Lightweight_On-Device_Continual_Learning_on_Microcontroller_Units.pdf; Paissan_Structured_Sparse_Back-propagation_for_Lightweight_On-Device_Continual_Learning_on_Microcontroller_CVPRW_2024_paper.pdf |
| Reduced precision floating-point optimization for Deep Neural Network On-Device Learning on microcontrollers / Nadalini, Davide; Rusci, Manuele; Benini, Luca; Conti, Francesco. - In: FUTURE GENERATION COMPUTER SYSTEMS. - ISSN 0167-739X. - 149:(2023), pp. 212-226. [10.1016/j.future.2023.07.020] | 1-gen-2023 | Davide NadaliniLuca Benini + | ArXiv.pdf; 1-s2.0-S0167739X23002728-main.pdf |
| PULP-TrainLib: Enabling On-Device Training for RISC-V Multi-core MCUs Through Performance-Driven Autotuning / Nadalini, Davide; Rusci, Manuele; Tagliavini, Giuseppe; Ravaglia, Leonardo; Benini, Luca; Conti, Francesco. - STAMPA. - (2022), pp. 200-216. (Intervento presentato al convegno 22nd International Conference, SAMOS 2022 tenutosi a Samos, Greece nel July 3–7, 2022) [10.1007/978-3-031-15074-6_13]. | 1-gen-2022 | Nadalini, DavideBenini, Luca + | PULP-TrainLib - Springer Version.pdf; PULP-TrainLib-Editoriale-Compressed.pdf |
| A TinyML Platform for On-Device Continual Learning with Quantized Latent Replays / Ravaglia, Leonardo; Rusci, Manuele; Nadalini, Davide; Capotondi, Alessandro; Conti, Francesco; Benini, Luca. - In: IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS. - ISSN 2156-3365. - 11:4(2021), pp. 789-802. [10.1109/JETCAS.2021.3121554] | 1-gen-2021 | Nadalini DavideBenini Luca + | TinyML_redux.pdf; A_TinyML_Platform_for_On-Device_Continual_Learning_With_Quantized_Latent_Replays.pdf |