Zobrazeno 1 - 10
of 18 461
pro vyhledávání: '"P, Egan"'
An $n\times n$ complex matrix $M$ with entries in the $k^{\textrm{th}}$ roots of unity which satisfies $MM^{\ast} = nI_{n}$ is called a Butson Hadamard matrix. While a matrix with entries in the $k^{\textrm{th}}$ roots typically does not have an eige
Externí odkaz:
http://arxiv.org/abs/2412.16579
A Beginner's Guide to Power and Energy Measurement and Estimation for Computing and Machine Learning
Autor:
Jagannadharao, Akshaya, Beckage, Nicole, Biswas, Sovan, Egan, Hilary, Gafur, Jamil, Metsch, Thijs, Nafus, Dawn, Raffa, Giuseppe, Tripp, Charles
Concerns about the environmental footprint of machine learning are increasing. While studies of energy use and emissions of ML models are a growing subfield, most ML researchers and developers still do not incorporate energy measurement as part of th
Externí odkaz:
http://arxiv.org/abs/2412.17830
Autor:
Berger, Sabrina, Lasinski, Arianna, Egan, Eamon, Wulf, Dallas, Chokshi, Aman, Sievers, Jonathan
We present results from the first application of the Global Navigation Satellite System (GNSS; GPS is one example of a collection of satellites in GNSS) for radio beam calibration using a commercial GNSS receiver with the Deep Dish Development Array
Externí odkaz:
http://arxiv.org/abs/2411.06144
Centraliser algebras of monomial representations of finite groups may be constructed and studied using methods similar to those employed in the study of permutation groups. Guided by results of D. G. Higman and others, we give an explicit constructio
Externí odkaz:
http://arxiv.org/abs/2409.14352
Low-dose positron emission tomography (PET) image reconstruction methods have potential to significantly improve PET as an imaging modality. Deep learning provides a promising means of incorporating prior information into the image reconstruction pro
Externí odkaz:
http://arxiv.org/abs/2409.06198
Implicit Neural Representations (INRs) have recently advanced the field of deep learning due to their ability to learn continuous representations of signals without the need for large training datasets. Although INR methods have been studied for medi
Externí odkaz:
http://arxiv.org/abs/2409.01013
Local interactions of uncoordinated individuals produce the collective behaviors of many biological systems, inspiring much of the current research in programmable matter. A striking example is the spontaneous assembly of fire ants into "bridges" com
Externí odkaz:
http://arxiv.org/abs/2408.10830
Autor:
Hassanali, Ali, Egan, Colin K.
The solvent-induced interactions (SII) between flexible solutes can be separated into two distinct components: the solvation-induced conformational effect, and the joint solvation interaction (JSI). The JSI quantifies the thermodynamic effect of the
Externí odkaz:
http://arxiv.org/abs/2408.08419
Grant Free Random Access (GFRA) is a popular protocol in the Internet of Things (IoT) to reduce the control signaling. GFRA is a framed protocol where each frame is split into two parts: device identification; and data transmission part which can be
Externí odkaz:
http://arxiv.org/abs/2407.18809
Publikováno v:
IEEE Transactions on Vehicular Technology, 2024
Grant-free random access (GFRA) is now a popular protocol for large-scale wireless multiple access systems in order to reduce control signaling. Resource allocation in GFRA can be viewed as a form of frame slotted ALOHA, where a ubiquitous design ass
Externí odkaz:
http://arxiv.org/abs/2407.18806