Zobrazeno 1 - 10
of 40 904
pro vyhledávání: '"A. A. Sima"'
Autor:
Fortulan, Raphael, Li, Suwei, Reece, Michael John, Serhiienko, Illia, Mori, Takao, Yamini, Sima Aminorroya
There is evidence that magnetism can potentially increase the thermopower of materials, most likely due to magnon scattering, suggesting the incorporation of intrinsic magnetic semiconductors in non-magnetic thermoelectric materials. Here, samples of
Externí odkaz:
http://arxiv.org/abs/2408.15704
Reward shaping is effective in addressing the sparse-reward challenge in reinforcement learning by providing immediate feedback through auxiliary informative rewards. Based on the reward shaping strategy, we propose a novel multi-task reinforcement l
Externí odkaz:
http://arxiv.org/abs/2408.10858
Reward shaping addresses the challenge of sparse rewards in reinforcement learning by constructing denser and more informative reward signals. To achieve self-adaptive and highly efficient reward shaping, we propose a novel method that incorporates s
Externí odkaz:
http://arxiv.org/abs/2408.03029
Fully supervised training of semantic segmentation models is costly and challenging because each pixel within an image needs to be labeled. Therefore, the sparse pixel-level annotation methods have been introduced to train models with a subset of pix
Externí odkaz:
http://arxiv.org/abs/2408.01694
Due to the expected disparity in quantum vs. classical clock speeds, quantum advantage for branch and bound algorithms is more likely achievable in settings involving large search trees and low operator evaluation costs. Therefore, in this paper, we
Externí odkaz:
http://arxiv.org/abs/2407.20185
With recent advancements in AI and computation tools, intelligent paradigms emerged to empower different fields such as healthcare robots with new capabilities. Advanced AI robotic algorithms (e.g., reinforcement learning) can be trained and develope
Externí odkaz:
http://arxiv.org/abs/2407.17464
Autor:
Wang, Xiaoqi, He, Wenbin, Xuan, Xiwei, Sebastian, Clint, Ono, Jorge Piazentin, Li, Xin, Behpour, Sima, Doan, Thang, Gou, Liang, Shen, Han Wei, Ren, Liu
The open-vocabulary image segmentation task involves partitioning images into semantically meaningful segments and classifying them with flexible text-defined categories. The recent vision-based foundation models such as the Segment Anything Model (S
Externí odkaz:
http://arxiv.org/abs/2406.05271
Auto-Multilift: Distributed Learning and Control for Cooperative Load Transportation With Quadrotors
Designing motion control and planning algorithms for multilift systems remains challenging due to the complexities of dynamics, collision avoidance, actuator limits, and scalability. Existing methods that use optimization and distributed techniques e
Externí odkaz:
http://arxiv.org/abs/2406.04858
Autor:
Aghdam, Sima Taefi, Javadi, Atefeh, Hashemi, Seyedazim, Abdollahi, Mahdi, van Loon, Jacco, Khosroshahi, Habib, Golshan, Roya Hamedani, Saremi, Elham, Saberi, Maryam
NGC 5128 (Cen A) is the nearest giant elliptical galaxy and one of the brightest extragalactic radio sources in the sky, boasting a prominent dust lane and jets emanating from its nuclear supermassive black hole. In this paper, we construct the star
Externí odkaz:
http://arxiv.org/abs/2406.00517
Large language models (LLMs) have attracted considerable attention as they are capable of showcasing impressive capabilities generating comparable high-quality responses to human inputs. LLMs, can not only compose textual scripts such as emails and e
Externí odkaz:
http://arxiv.org/abs/2405.19578