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Kujifunza Kidogo cha Mtandaoni

Kujifunza Kidogo cha Mtandaoni huunganisha kanuni ya sasisho la mtiririko wa kujifunza mtandaoni na lengo la ufanisi wa data la kujifunza kidogo, ikiwezesha modeli kubadilika kila wakati kwa kazi au madarasa mapya kutoka kwa mifano michache tu iliyo na lebo wakati data inapoingia mfululizo — bila ufikiaji wa seti kamili ya data ya kihistoria.

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Vyanzo

  1. Finn, C., Rajeswaran, A., Kakade, S., & Levine, S. (2019). Online Meta-Learning. Proceedings of the 36th International Conference on Machine Learning (ICML), PMLR 97, 1920–1930. link
  2. Javed, K., & White, M. (2019). Meta-Learning Representations for Continual Learning. Advances in Neural Information Processing Systems (NeurIPS), 32. link

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Online Few-shot Learning (Streaming Meta-Learning from Scarce Labels). ScholarGate. https://scholargate.app/sw/machine-learning/online-few-shot-learning

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Linganisha bega kwa bega
ScholarGateOnline Few-shot Learning (Online Few-shot Learning (Streaming Meta-Learning from Scarce Labels)). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/machine-learning/online-few-shot-learning · Seti ya data: https://doi.org/10.5281/zenodo.20539026