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pro vyhledávání: '"Matson, A. T."'
Ever-increasing ubiquity of data and computational resources in the last decade have propelled a notable transition in the machine learning paradigm towards more distributed approaches. Such a transition seeks to not only tackle the scalability and r
Externí odkaz:
http://arxiv.org/abs/2401.10839
The rapid growth of wearable sensor technologies holds substantial promise for the field of personalized and context-aware Human Activity Recognition. Given the inherently decentralized nature of data sources within this domain, the utilization of mu
Externí odkaz:
http://arxiv.org/abs/2311.04236
Algorithm selection and hyperparameter tuning are critical steps in both academic and applied machine learning. On the other hand, these steps are becoming ever increasingly delicate due to the extensive rise in the number, diversity, and distributed
Externí odkaz:
http://arxiv.org/abs/2309.06604
Hyper-parameter optimization is one of the most tedious yet crucial steps in training machine learning models. There are numerous methods for this vital model-building stage, ranging from domain-specific manual tuning guidelines suggested by the orac
Externí odkaz:
http://arxiv.org/abs/2303.03394
Hierarchical Multi-Agent Systems provide convenient and relevant ways to analyze, model, and simulate complex systems composed of a large number of entities that interact at different levels of abstraction. In this paper, we introduce HAMLET (Hierarc
Externí odkaz:
http://arxiv.org/abs/2010.04894
In this paper, we present a directional antenna-based leader-follower robotic relay system capable of building end-to-end communication in complicated and dynamically changing environments. The proposed system consists of multiple networked robots -
Externí odkaz:
http://arxiv.org/abs/1711.08007
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Akademický článek
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Autor:
Luo, Shaocheng, Kim, Jonghoek, Parasuraman, Ramviyas, Bae, Jun Han, Matson, Eric T., Min, Byung-Cheol
Publikováno v:
In Ad Hoc Networks 1 April 2019 86:131-143
A 15-Category Audio Dataset for Drones and an Audio-Based UAV Classification Using Machine Learning.
Publikováno v:
International Journal of Semantic Computing; Jun2024, Vol. 18 Issue 2, p257-272, 16p