Decebal Constantin Mocanu
4 papers in the PaperMetrix corpus
Papers by this author
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Evolving Plasticity for Autonomous Learning under Changing Environmental Conditions
2019 · University of Twente Research Information
A fundamental aspect of learning in biological neural networks is the plasticity property which allows them to modify their configurations during their lifetime. Hebbian learning is a biologically plausible mechanism for modeling the plasticity property …
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The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training
2022 · TU/e Research Portal
Random pruning is arguably the most naive way to attain sparsity in neural networks, but has been deemed uncompetitive by either post-training pruning or sparse training. In this paper, we focus on sparse training and …
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Quick and Robust Feature Selection: the Strength of Energy-efficient\n Sparse Training for Autoencoders
2020 · arXiv (Cornell University)
Major complications arise from the recent increase in the amount of\nhigh-dimensional data, including high computational costs and memory\nrequirements. Feature selection, which identifies the most relevant and\ninformative attributes of a dataset, has been introduced as a …
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Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity
2025 · arXiv (Cornell University)
Federated learning (FL) enables collaborative model training across decentralized clients while preserving data privacy, leveraging aggregated updates to build robust global models. However, this training paradigm faces significant challenges due to data heterogeneity and limited …