Zobrazeno 1 - 10
of 6 362
pro vyhledávání: '"Bilgehan, A."'
In the realm of digital communication, understanding and mitigating the probability of error is crucial, particularly in Rayleigh fading channels where signal impairments are common. This paper presents a unified approach to derive the probability of
Externí odkaz:
http://arxiv.org/abs/2411.01977
Autor:
Azad, Fahim Tasneema, Anton, Javier Redondo, Mitra, Shubhodeep, Singh, Fateh, Behrens, Hans, Li, Mao-Lin, Arslan, Bilgehan, Candan, K. Selçuk, Sapino, Maria Luisa
Many socio-economical critical domains (such as sustainability, public health, and disasters) are characterized by highly complex and dynamic systems, requiring data and model-driven simulations to support decision-making. Due to a large number of un
Externí odkaz:
http://arxiv.org/abs/2407.14571
Autor:
Abdelbari, Amr, Bilgehan, Bülent
Understanding the probability of error is paramount in the design and analysis of digital communication systems, particularly in Rayleigh fading channels where signal impairments are prevalent. This article presents a unified approach for deriving th
Externí odkaz:
http://arxiv.org/abs/2406.16548
Publikováno v:
ICLR 2023
Meta-reinforcement learning has widely been used as a learning-to-learn framework to solve unseen tasks with limited experience. However, the aspect of constraint violations has not been adequately addressed in the existing works, making their applic
Externí odkaz:
http://arxiv.org/abs/2405.16601
In numerous reinforcement learning (RL) problems involving safety-critical systems, a key challenge lies in balancing multiple objectives while simultaneously meeting all stringent safety constraints. To tackle this issue, we propose a primal-based f
Externí odkaz:
http://arxiv.org/abs/2405.16390
Large Language Models (LLMs) have shown remarkable capabilities in tasks such as summarization, arithmetic reasoning, and question answering. However, they encounter significant challenges in the domain of moral reasoning and ethical decision-making,
Externí odkaz:
http://arxiv.org/abs/2405.12933
Ensuring the safety of Reinforcement Learning (RL) is crucial for its deployment in real-world applications. Nevertheless, managing the trade-off between reward and safety during exploration presents a significant challenge. Improving reward performa
Externí odkaz:
http://arxiv.org/abs/2405.01677
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-24 (2024)
Abstract Significant progress has been made recently with the contribution of technological advances in studies on brain cancer. Regarding this, identifying and correctly classifying tumors is a crucial task in the field of medical imaging. The disea
Externí odkaz:
https://doaj.org/article/84d9af284298442aa862ffea9725dec8
Autor:
Birol Ocak, Ahmet Bilgehan Sahin, Ismail Ertürk, Mustafa Korkmaz, Dilek Erdem, Umut Cakıroglu, Mustafa Karaca, Ahmet Dirican, Omer Fatih Olmez, Sabin Goktas Aydın, Ali Gökyer, Ahmet Kücükarda, Ahmet Gülmez, Perran Fulden Yumuk, Nazim Can Demircan, Abdilkerim Oyman, Teoman Sakalar, Fatih Karatas, Hacer Demir, Ayse Irem Yasin, Adem Deligonul, Bahar Dakiki, Mehmet Refik Goktug, Okan Avcı, Seher Yildiz Tacar, Nazım Serdar Turhal, Gülhan Ipek Deniz, Turgut Kacan, Erdem Cubukcu, Türkkan Evrensel
Publikováno v:
Current Oncology, Vol 31, Iss 9, Pp 5195-5205 (2024)
Background: This study aimed to investigate the effect of cytoreductive nephrectomy (CN) on the survival outcomes of nivolumab used as a subsequent therapy after the failure of at least one anti-vascular endothelial growth factor (VEGF) agent in pati
Externí odkaz:
https://doaj.org/article/e3b91b5047204acf948136cd657f8dec
Current literature, aiming to surpass the "Chain-of-Thought" approach, often resorts to external modi operandi involving halting, modifying, and then resuming the generation process to boost Large Language Models' (LLMs) reasoning capacities. Due to
Externí odkaz:
http://arxiv.org/abs/2308.10379