Zobrazeno 1 - 10
of 38 925
pro vyhledávání: '"A, Koç"'
Traditional machine learning approaches assume that data comes from a single generating mechanism, which may not hold for most real life data. In these cases, the single mechanism assumption can result in suboptimal performance. We introduce a cluste
Externí odkaz:
http://arxiv.org/abs/2411.06572
Autor:
Vasu, Pavan Kumar Anasosalu, Faghri, Fartash, Li, Chun-Liang, Koc, Cem, True, Nate, Antony, Albert, Santhanam, Gokul, Gabriel, James, Grasch, Peter, Tuzel, Oncel, Pouransari, Hadi
Scaling the input image resolution is essential for enhancing the performance of Vision Language Models (VLMs), particularly in text-rich image understanding tasks. However, popular visual encoders such as ViTs become inefficient at high resolutions
Externí odkaz:
http://arxiv.org/abs/2412.13303
Autor:
Yiğit, Uğur, Koç, Suat
Let $R\ $be an integral domain and $R^{\#}$ the set of all nonzero nonunits of $R.\ $For every elements $a,b\in R^{\#},$ we define $a\sim b$ if and only if $aR=bR,$ that is, $a$ and $b$ are associated elements. Suppose that $EC(R^{\#})$ is the set of
Externí odkaz:
http://arxiv.org/abs/2409.10577
In this paper, we associate a new topology to a nonzero unital module $M$ over a commutative $R$, which is called Golomb topology of the $R$-module $M$. Let $M\ $be an\ $R$-module and $B_{M}$ be the family of coprime cosets $\{m+N\}$ where $m\in M$ a
Externí odkaz:
http://arxiv.org/abs/2409.09807
Autor:
Çakmak, Hikmet, Yontan, Talar, Bilir, Selçk, Banks, Timothy S., Michel, Raúl., Soydugan, Esin, Koç, Seliz, Erçay, Hülya
This study outlines a detailed investigation using CCD {\it UBV} and {\it Gaia} DR3 data sets of the two open clusters Ruprecht 1 (Rup-1) and Ruprecht 171 (Rup-171). Fundamental astrophysical parameters such as color excesses, photometric metalliciti
Externí odkaz:
http://arxiv.org/abs/2409.02298
This study explores the use of large language models (LLMs) to predict emotion intensity in Polish political texts, a resource-poor language context. The research compares the performance of several LLMs against a supervised model trained on an annot
Externí odkaz:
http://arxiv.org/abs/2407.12141
Autor:
Koç, Robin, Vural, Fatoş T. Yarman
In this study, we attempt to model intuition and incorporate this formalism to improve the performance of the Convolutional Neural Networks. Despite decades of research, ambiguities persist on principles of intuition. Experimental psychology reveals
Externí odkaz:
http://arxiv.org/abs/2407.09236
Autor:
Çiloğlu, Berk, Koç, Görkem Berkay, Shamsabadi, Afsoon Alidadi, Ozturk, Metin, Yanikomeroglu, Halim
Generative-AI (GenAI), a novel technology capable of producing various types of outputs, including text, images, and videos, offers significant potential for wireless communications. This article introduces the concept of strategic demand-planning th
Externí odkaz:
http://arxiv.org/abs/2407.02292
Autor:
Pouransari, Hadi, Li, Chun-Liang, Chang, Jen-Hao Rick, Vasu, Pavan Kumar Anasosalu, Koc, Cem, Shankar, Vaishaal, Tuzel, Oncel
Large language models (LLMs) are commonly trained on datasets consisting of fixed-length token sequences. These datasets are created by randomly concatenating documents of various lengths and then chunking them into sequences of a predetermined targe
Externí odkaz:
http://arxiv.org/abs/2405.13226
This study aims to introduce the cell load estimation problem of cell switching approaches in cellular networks specially-presented in a high-altitude platform station (HAPS)-assisted network. The problem arises from the fact that the traffic loads o
Externí odkaz:
http://arxiv.org/abs/2405.00387