Zobrazeno 1 - 10
of 229
pro vyhledávání: '"Jaeger, Stefan"'
Autor:
Jaeger, Stefan
Contemporary machine learning methods will try to approach the Bayes error, as it is the lowest possible error any model can achieve. This paper postulates that any decision is composed of not one but two Bayesian decisions and that decision-making i
Externí odkaz:
http://arxiv.org/abs/2410.12984
Publikováno v:
2024 IEEE International Conference on Image Processing (ICIP)
Predominant methods for image-based drone detection frequently rely on employing generic object detection algorithms like YOLOv5. While proficient in identifying drones against homogeneous backgrounds, these algorithms often struggle in complex, high
Externí odkaz:
http://arxiv.org/abs/2406.11641
Autor:
Jaeger, Stefan
Minimizing cross-entropy is a widely used method for training artificial neural networks. Many training procedures based on backpropagation use cross-entropy directly as their loss function. Instead, this theoretical essay investigates a dual process
Externí odkaz:
http://arxiv.org/abs/2104.13277
Autor:
Jaeger, Stefan
Gradient descent has been a central training principle for artificial neural networks from the early beginnings to today's deep learning networks. The most common implementation is the backpropagation algorithm for training feed-forward neural networ
Externí odkaz:
http://arxiv.org/abs/2006.04751
Akademický článek
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Autor:
Yanik, Sean, Hang Yu, Chaiyawong, Nattawat, Adewale-Fasoro, Opeoluwa, Dinis, Luciana Ribeiro, Narayanasamy, Ravi Kumar, Lee, Elizabeth C., Lubonja, Ariel, Bowen Li, Jaeger, Stefan, Srinivasan, Prakash
Publikováno v:
American Journal of Tropical Medicine & Hygiene; Nov2024, Vol. 111 Issue 5, p967-976, 10p
Akademický článek
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Autor:
Jaeger, Stefan
This paper presents a new representation of natural numbers and discusses its consequences for computability and computational complexity. The paper argues that the introduction of the first Peano axiom in the traditional definition of natural number
Externí odkaz:
http://arxiv.org/abs/1104.2538
Autor:
Jaeger, Stefan
Heisenberg's uncertainty principle states that it is not possible to compute both the position and momentum of an electron with absolute certainty. However, this computational limitation, which is central to quantum mechanics, has no counterpart in t
Externí odkaz:
http://arxiv.org/abs/0811.0463