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pro vyhledávání: '"Nikolakakis A"'
Autor:
Nikolakakis, Emmanouil, Ching, Joann, Karystinaios, Emmanouil, Sipin, Gabrielle, Widmer, Gerhard, Marinescu, Razvan
Music therapy has been shown in recent years to provide multiple health benefits related to emotional wellness. In turn, maintaining a healthy emotional state has proven to be effective for patients undergoing treatment, such as Parkinson's patients
Externí odkaz:
http://arxiv.org/abs/2411.09080
Autor:
Promponas, Panagiotis, Valls, Víctor, Nikolakakis, Konstantinos, Kalogerias, Dionysis, Tassiulas, Leandros
We study the problem of designing scheduling policies for communication networks. This problem is often addressed with max-weight-type approaches since they are throughput-optimal. However, max-weight policies make scheduling decisions based on the n
Externí odkaz:
http://arxiv.org/abs/2409.09198
We present AFEN (Audio Feature Ensemble Learning), a model that leverages Convolutional Neural Networks (CNN) and XGBoost in an ensemble learning fashion to perform state-of-the-art audio classification for a range of respiratory diseases. We use a m
Externí odkaz:
http://arxiv.org/abs/2405.05467
Reconstructing digital brain phantoms in the form of voxel-based, multi-channeled tissue probability maps for individual subjects is essential for capturing brain anatomical variability, understanding neurological diseases, as well as for testing ima
Externí odkaz:
http://arxiv.org/abs/2404.14739
The NOSTR is a communication protocol for the social web, based on the w3c websockets standard. Although it is still in its infancy, it is well known as a social media protocol, thousands of trusted users and multiple user interfaces, offering a uniq
Externí odkaz:
http://arxiv.org/abs/2404.15834
We present GaSpCT, a novel view synthesis and 3D scene representation method used to generate novel projection views for Computer Tomography (CT) scans. We adapt the Gaussian Splatting framework to enable novel view synthesis in CT based on limited s
Externí odkaz:
http://arxiv.org/abs/2404.03126
Federated Learning (FL) is a decentralized machine learning framework that enables collaborative model training while respecting data privacy. In various applications, non-uniform availability or participation of users is unavoidable due to an advers
Externí odkaz:
http://arxiv.org/abs/2309.14176
Autor:
Okanovic, Patrik, Waleffe, Roger, Mageirakos, Vasilis, Nikolakakis, Konstantinos E., Karbasi, Amin, Kalogerias, Dionysis, Gürel, Nezihe Merve, Rekatsinas, Theodoros
Methods for carefully selecting or generating a small set of training data to learn from, i.e., data pruning, coreset selection, and data distillation, have been shown to be effective in reducing the ever-increasing cost of training neural networks.
Externí odkaz:
http://arxiv.org/abs/2305.18424
We establish matching upper and lower generalization error bounds for mini-batch Gradient Descent (GD) training with either deterministic or stochastic, data-independent, but otherwise arbitrary batch selection rules. We consider smooth Lipschitz-con
Externí odkaz:
http://arxiv.org/abs/2305.02247
Autor:
Nikolaos Nikolakakis
Publikováno v:
Filosofia Unisinos, Vol 25, Iss 3 (2024)
This study offers an in-depth exploration of Jean-Jacques Rousseau’s philosophy of international relations, an under-researched but crucial aspect of his political thought. We strongly argue that Rousseau understood the transformation of individual
Externí odkaz:
https://doaj.org/article/6c2897d4cd024b0d9783f7872ddfd8ce
