Zobrazeno 1 - 10
of 91 830
pro vyhledávání: '"A. Møller"'
Multiclass learnability is known to exhibit a properness barrier: there are learnable classes which cannot be learned by any proper learner. Binary classification faces no such barrier for learnability, but a similar one for optimal learning, which c
Externí odkaz:
http://arxiv.org/abs/2410.22749
Autor:
Kiefer, Sven, Bach-Møller, Nanna, Samra, Dominic, Lewis, David A., Schneider, Aaron D., Amadio, Flavia, Lecoq-Molinos, Helena, Carone, Ludmila, Decin, Leen, Jørgensen, Uffe G., Helling, Christiane
Warm Saturn type exoplanets orbiting M-dwarfs are particularly suitable for in-depth cloud characterisation through transmission spectroscopy due to their favourable stellar to planetary radius contrast. However, modelling cloud formation consistentl
Externí odkaz:
http://arxiv.org/abs/2410.17716
Autor:
Legrand, Nicolas, Weber, Lilian, Waade, Peter Thestrup, Daugaard, Anna Hedvig Møller, Khodadadi, Mojtaba, Mikuš, Nace, Mathys, Chris
Bayesian models of cognition have gained considerable traction in computational neuroscience and psychiatry. Their scopes are now expected to expand rapidly to artificial intelligence, providing general inference frameworks to support embodied, adapt
Externí odkaz:
http://arxiv.org/abs/2410.09206
In the context of Industry 4.0, the manufacturing sector is increasingly facing the challenge of data usability, which is becoming a widespread phenomenon and a new contemporary concern. In response, Data Governance (DG) emerges as a viable avenue to
Externí odkaz:
http://arxiv.org/abs/2409.15137
Autor:
Nielsen, Rasmus Svejstrup, Gunawan, Oki, Todorov, Teodor, Møller, Clara Brendstrup, Hansen, Ole, Vesborg, Peter Christian Kjærgaard
Selenium is an elemental semiconductor with a wide bandgap suitable for a range of optoelectronic and solar energy conversion technologies. However, developing such applications requires an in-depth understanding of the fundamental material propertie
Externí odkaz:
http://arxiv.org/abs/2409.12804
Room equalisation aims to increase the quality of loudspeaker reproduction in reverberant environments, compensating for colouration caused by imperfect room reflections and frequency dependant loudspeaker directivity. A common technique in the field
Externí odkaz:
http://arxiv.org/abs/2409.10131
Real or Robotic? Assessing Whether LLMs Accurately Simulate Qualities of Human Responses in Dialogue
Autor:
Ivey, Jonathan, Kumar, Shivani, Liu, Jiayu, Shen, Hua, Rakshit, Sushrita, Raju, Rohan, Zhang, Haotian, Ananthasubramaniam, Aparna, Kim, Junghwan, Yi, Bowen, Wright, Dustin, Israeli, Abraham, Møller, Anders Giovanni, Zhang, Lechen, Jurgens, David
Studying and building datasets for dialogue tasks is both expensive and time-consuming due to the need to recruit, train, and collect data from study participants. In response, much recent work has sought to use large language models (LLMs) to simula
Externí odkaz:
http://arxiv.org/abs/2409.08330
Autor:
Chiche, Simon, Moller, Nicolas, Bishop, Abby, de Kockere, Simon, de Vries, Krijn D., Latif, Uzair, Toscano, Simona
To detect ultra-high-energy neutrinos, experiments such as ARA and RNO-G target the radio emission these particles induce when cascading in the ice, using deep antennas in South Pole or in Greenland. One of the main backgrounds for such signals is th
Externí odkaz:
http://arxiv.org/abs/2409.02185
Boosting is an extremely successful idea, allowing one to combine multiple low accuracy classifiers into a much more accurate voting classifier. In this work, we present a new and surprisingly simple Boosting algorithm that obtains a provably optimal
Externí odkaz:
http://arxiv.org/abs/2408.17148
Recent works on the parallel complexity of Boosting have established strong lower bounds on the tradeoff between the number of training rounds $p$ and the total parallel work per round $t$. These works have also presented highly non-trivial parallel
Externí odkaz:
http://arxiv.org/abs/2408.16653