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pro vyhledávání: '"Kirsch A"'
Autor:
Okanovic, Patrik, Kirsch, Andreas, Kasper, Jannes, Hoefler, Torsten, Krause, Andreas, Gürel, Nezihe Merve
With the multitude of pretrained models available thanks to the advancements in large-scale supervised and self-supervised learning, choosing the right model is becoming increasingly pivotal in the machine learning lifecycle. However, much like the t
Externí odkaz:
http://arxiv.org/abs/2410.13609
A De Bruijn cycle is a cyclic sequence in which every word of length $n$ over an alphabet $\mathcal{A}$ appears exactly once. De Bruijn tori are a two-dimensional analogue. Motivated by recent progress on universal partial cycles and words, which sho
Externí odkaz:
http://arxiv.org/abs/2409.12417
Autor:
Kirsch, Andreas
Epistemic uncertainty is crucial for safety-critical applications and out-of-distribution detection tasks. Yet, we uncover a paradoxical phenomenon in deep learning models: an epistemic uncertainty collapse as model complexity increases, challenging
Externí odkaz:
http://arxiv.org/abs/2409.02628
Large Language Models (LLMs) generate text by sampling the next token from a probability distribution over the vocabulary at each decoding step. However, popular sampling methods like top-p (nucleus sampling) often struggle to balance quality and div
Externí odkaz:
http://arxiv.org/abs/2407.01082
Autor:
Park, Jihun, Horn, Jarryd A., Kirsch, Dylan J., Pant, Rohit K., Yoon, Hyeok, Baek, Sungha, Sarker, Suchismita, Mehta, Apurva, Zhang, Xiaohang, Lee, Seunghun, Greene, Richard, Paglione, Johnpierre, Takeuchi, Ichiro
The Bi${-}$Ni binary system has been of interest due to possible unconventional superconductivity aroused therein, such as time-reversal symmetry breaking in Bi/Ni bilayers or the coexistence of superconductivity and ferromagnetism in Bi$_3$Ni crysta
Externí odkaz:
http://arxiv.org/abs/2406.18704
Recently, transductive learning methods, which leverage holdout sets during training, have gained popularity for their potential to improve speed, accuracy, and fairness in machine learning models. Despite this, the composition of the holdout set its
Externí odkaz:
http://arxiv.org/abs/2406.12011
Autor:
Brandfonbrener, David, Zhang, Hanlin, Kirsch, Andreas, Schwarz, Jonathan Richard, Kakade, Sham
Selecting high-quality data for pre-training is crucial in shaping the downstream task performance of language models. A major challenge lies in identifying this optimal subset, a problem generally considered intractable, thus necessitating scalable
Externí odkaz:
http://arxiv.org/abs/2406.10670
We provide a mathematical analysis of the Dynamical Mean-Field Theory, a celebrated representative of a class of approximations in quantum mechanics known as embedding methods. We start by a pedagogical and self-contained mathematical formulation of
Externí odkaz:
http://arxiv.org/abs/2406.03384
Temporal credit assignment in reinforcement learning is challenging due to delayed and stochastic outcomes. Monte Carlo targets can bridge long delays between action and consequence but lead to high-variance targets due to stochasticity. Temporal dif
Externí odkaz:
http://arxiv.org/abs/2405.03878
Publikováno v:
Pediatric Health, Medicine and Therapeutics, Vol Volume 10, Pp 75-81 (2019)
Angela M Arlen,1 Cayce Nawaf,1 Andrew J Kirsch21Yale University School of Medicine, Department of Urology, New Haven, CT 06520, USA; 2Emory University, Children’s Healthcare of Atlanta, Atlanta, GA 30328, USAAbstract: Prune belly syndrome (PBS) is
Externí odkaz:
https://doaj.org/article/dc9600cbe0824962b254bc7170784b9c