Zobrazeno 1 - 10
of 764
pro vyhledávání: '"Gerogiannis IS"'
We study the problem of Non-Stationary Reinforcement Learning (NS-RL) without prior knowledge about the system's non-stationarity. A state-of-the-art, black-box algorithm, known as MASTER, is considered, with a focus on identifying the conditions und
Externí odkaz:
http://arxiv.org/abs/2410.13772
Autor:
Ranawaka, Isuru, Hussain, Md Taufique, Block, Charles, Gerogiannis, Gerasimos, Torrellas, Josep, Azad, Ariful
We consider a sparse matrix-matrix multiplication (SpGEMM) setting where one matrix is square and the other is tall and skinny. This special variant, called TS-SpGEMM, has important applications in multi-source breadth-first search, influence maximiz
Externí odkaz:
http://arxiv.org/abs/2408.11988
State of the art methods for target tracking with sensor management (or controlled sensing) are model-based and are obtained through solutions to Partially Observable Markov Decision Process (POMDP) formulations. In this paper a Reinforcement Learnin
Externí odkaz:
http://arxiv.org/abs/2407.13995
Autor:
Gerogiannis, Dimitrios, Papantoniou, Foivos Paraperas, Potamias, Rolandos Alexandros, Lattas, Alexandros, Moschoglou, Stylianos, Ploumpis, Stylianos, Zafeiriou, Stefanos
The field of photorealistic 3D avatar reconstruction and generation has garnered significant attention in recent years; however, animating such avatars remains challenging. Recent advances in diffusion models have notably enhanced the capabilities of
Externí odkaz:
http://arxiv.org/abs/2403.17213
Autor:
Gerogiannis, Demetris, Arsenos, Anastasios, Kollias, Dimitrios, Nikitopoulos, Dimitris, Kollias, Stefanos
Computer-aided diagnosis (CAD) systems stand out as potent aids for physicians in identifying the novel Coronavirus Disease 2019 (COVID-19) through medical imaging modalities. In this paper, we showcase the integration and reliable and fast deploymen
Externí odkaz:
http://arxiv.org/abs/2403.06242
Autor:
Lenadora, Damitha, Sathia, Vimarsh, Gerogiannis, Gerasimos, Yesil, Serif, Torrellas, Josep, Mendis, Charith
Over the years, many frameworks and optimization techniques have been proposed to accelerate graph neural networks (GNNs). Compared to the optimizations explored in these systems, we observe that different matrix re-associations of GNN computations l
Externí odkaz:
http://arxiv.org/abs/2306.15155
Publikováno v:
In Telecommunications Policy March 2025 49(1)
Publikováno v:
IEEE Access, Vol 12, Pp 46470-46483 (2024)
Regulatory compliance in the pharmaceutical industry is challenging, requiring dedicated resources and meticulous control over production processes to ensure adherence to established regulatory guidelines, specifically ALCOA+ (Attributable, Legible,
Externí odkaz:
https://doaj.org/article/0efb5c18d6ef4c8b8fc2b778b34ac2cd
Autor:
Srinath Akuthota, Ravi Chander Janapati, K. Raj Kumar, Vassilis C. Gerogiannis, Andreas Kanavos, Biswaranjan Acharya, Foteini Grivokostopoulou, Usha Desai
Publikováno v:
Information, Vol 15, Iss 11, p 702 (2024)
This paper advances real-time cursor control for individuals with motor impairments through a novel brain–computer interface (BCI) system based solely on motor imagery. We introduce an enhanced deep neural network (DNN) classifier integrated with a
Externí odkaz:
https://doaj.org/article/8c4539d0d89546a898ba3bcad5531896
Publikováno v:
In Journal of Structural Geology August 2024 185