ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2007.13631
  4. Cited By
Memory-Latency-Accuracy Trade-offs for Continual Learning on a RISC-V
  Extreme-Edge Node

Memory-Latency-Accuracy Trade-offs for Continual Learning on a RISC-V Extreme-Edge Node

22 July 2020
Leonardo Ravaglia
Manuele Rusci
Alessandro Capotondi
Francesco Conti
Lorenzo Pellegrini
Vincenzo Lomonaco
Davide Maltoni
Luca Benini
ArXiv (abs)PDFHTML

Papers citing "Memory-Latency-Accuracy Trade-offs for Continual Learning on a RISC-V Extreme-Edge Node"

5 / 5 papers shown
Genesis: A Spiking Neuromorphic Accelerator With On-chip Continual Learning
Genesis: A Spiking Neuromorphic Accelerator With On-chip Continual Learning
Vedant Karia
Abdullah M. Zyarah
Dhireesha Kudithipudi
162
0
0
06 Sep 2025
Design Principles for Lifelong Learning AI Accelerators
Design Principles for Lifelong Learning AI AcceleratorsNature Electronics (Nat. Electron.), 2023
Dhireesha Kudithipudi
Anurag Daram
Abdullah M. Zyarah
Fatima Tuz Zohora
J. Aimone
...
Emre Neftci
M. Mattina
Vincenzo Lomonaco
Clare D. Thiem
Benjamin Epstein
309
26
0
05 Oct 2023
RedMule: A Mixed-Precision Matrix-Matrix Operation Engine for Flexible
  and Energy-Efficient On-Chip Linear Algebra and TinyML Training Acceleration
RedMule: A Mixed-Precision Matrix-Matrix Operation Engine for Flexible and Energy-Efficient On-Chip Linear Algebra and TinyML Training AccelerationFuture generations computer systems (FGCS), 2023
Yvan Tortorella
L. Bertaccini
Luca Benini
D. Rossi
Francesco Conti
214
29
0
10 Jan 2023
Architect, Regularize and Replay (ARR): a Flexible Hybrid Approach for
  Continual Learning
Architect, Regularize and Replay (ARR): a Flexible Hybrid Approach for Continual Learning
Vincenzo Lomonaco
Lorenzo Pellegrini
G. Graffieti
Davide Maltoni
331
2
0
06 Jan 2023
A TinyML Platform for On-Device Continual Learning with Quantized Latent
  Replays
A TinyML Platform for On-Device Continual Learning with Quantized Latent ReplaysIEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS), 2021
Leonardo Ravaglia
Manuele Rusci
D. Nadalini
Alessandro Capotondi
Francesco Conti
Luca Benini
BDL
320
88
0
20 Oct 2021
1
Page 1 of 1