Zobrazeno 1 - 10
of 5 247
pro vyhledávání: '"Sayın, A."'
We present a novel approach to reconstruction of 3D cardiac motion from sparse intraoperative data. While existing methods can accurately reconstruct 3D organ geometries from full 3D volumetric imaging, they cannot be used during surgical interventio
Externí odkaz:
http://arxiv.org/abs/2412.02589
Autor:
Donmez, Ahmed Said, Sayin, Muhammed O.
This paper addresses the challenge of limited observations in non-cooperative multi-agent systems where agents can have partial access to other agents' actions. We present the generalized individual Q-learning dynamics that combine belief-based and p
Externí odkaz:
http://arxiv.org/abs/2409.02663
Autor:
Sayin, Irem, Gursoy, Rana, Cicek, Buse, Mert, Yunus Emre, Ozturk, Fatih, Pamukcu, Taha Emre, Sevimli, Ceylin Deniz, Uvet, Huseyin
This study develops a Convolutional Neural Network (CNN) model for detecting myocardial infarction (MI) from Electrocardiogram (ECG) images. The model, built using the InceptionV3 architecture and optimized through transfer learning, was trained usin
Externí odkaz:
http://arxiv.org/abs/2408.16800
We explore the potential of Large Language Models (LLMs) to assist and potentially correct physicians in medical decision-making tasks. We evaluate several LLMs, including Meditron, Llama2, and Mistral, to analyze the ability of these models to inter
Externí odkaz:
http://arxiv.org/abs/2403.20288
There is increasing interest in developing AIs for assisting human decision-making in high-stakes tasks, such as medical diagnosis, for the purpose of improving decision quality and reducing cognitive strain. Mainstream approaches team up an expert w
Externí odkaz:
http://arxiv.org/abs/2403.16501
Publikováno v:
IEEE Control Systems Letters 8 (2024) 1733-1738
In this paper, we explore the susceptibility of the independent Q-learning algorithms (a classical and widely used multi-agent reinforcement learning method) to strategic manipulation of sophisticated opponents in normal-form games played repeatedly.
Externí odkaz:
http://arxiv.org/abs/2403.08906
Multi-team games, prevalent in robotics and resource management, involve team members striving for a joint best response against other teams. Team-Nash equilibrium (TNE) predicts the outcomes of such coordinated interactions. However, can teams of se
Externí odkaz:
http://arxiv.org/abs/2402.02147
Multimodal optimization is often encountered in engineering problems, especially when different and alternative solutions are sought. Evolutionary algorithms can efficiently tackle multimodal optimization thanks to their features such as the concept
Externí odkaz:
http://arxiv.org/abs/2401.06153
This paper presents new families of algorithms for the repeated play of two-agent (near) zero-sum games and two-agent zero-sum stochastic games. For example, the family includes fictitious play and its variants as members. Commonly, the algorithms in
Externí odkaz:
http://arxiv.org/abs/2311.00778
Autor:
Sayin, Muhammed O.
This paper proposes a finite-horizon approximation scheme and introduces episodic equilibrium as a solution concept for stochastic games (SGs), where agents strategize based on the current state and episode stage. The paper also establishes an upper
Externí odkaz:
http://arxiv.org/abs/2310.07256