Decebal Constantin Mocanu

dr.ir.

  • Source: Scopus
  • Calculated based on number of publications stored in Pure and citations from Scopus
20132022

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  • 2021

    Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training

    Liu, S., Yin, L., Mocanu, D. C. & Pechenizkiy, M., 18 Jul 2021, The Thirty-eighth International Conference on Machine Learning, ICML 2021.

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

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  • Forecasting

    Mocanu, E., Mocanu, D. C., Paterakis, N. G. & Gibescu, M., 9 Jul 2021, Local Electricity Markets. Pinto, T., Vale, Z. & Widergren, S. (eds.). 1 ed. Elsevier

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

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  • Selfish Sparse RNN Training

    Liu, S., Mocanu, D. C., Pei, Y. & Pechenizkiy, M., 18 Jul 2021, The Thirty-eighth International Conference on Machine Learning, ICML 2021. (PMLR, Proceedings of Machine Learning Research; vol. 139).

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

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  • Sparse Training Theory for Scalable and Efficient Agents

    Mocanu, D. C., Mocanu, E., Pinto, T., Curci, S., Nguyen, P. H., Gibescu, M., Ernst, D. & Vale, Z., 3 May 2021, AAMAS '21: Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems. p. 34-38

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

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    18 Downloads (Pure)
  • Sparse Training via Boosting Pruning Plasticity with Neuroregeneration

    Liu, S., Chen, T., Chen, X., Atashgahi, Z., Yin, L., Kou, H., Shen, L., Pechenizkiy, M., Wang, Z. & Mocanu, D. C., 19 Jun 2021, Advances in Neural Information Processing Systems. 25 p.

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

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