Zobrazeno 1 - 10
of 6 424
pro vyhledávání: '"Karray"'
Publikováno v:
Research and Reports in Urology, Vol Volume 14, Pp 351-358 (2022)
Naim Yarak, Skander Zouari, Omar Karray, Walid Sleiman, Alaa Abdelwahab, Stéphane Bart, Maher Abdessater Urology Department, Centre Hospitalier Régional René DUBOS, Pontoise, 95300, FranceCorrespondence: Maher Abdessater, Email maher.abdessater@gm
Externí odkaz:
https://doaj.org/article/4ebb0254a8de4249b6f2e27d3694822f
Autor:
Zhang, Weizhi, Bei, Yuanchen, Yang, Liangwei, Zou, Henry Peng, Zhou, Peilin, Liu, Aiwei, Li, Yinghui, Chen, Hao, Wang, Jianling, Wang, Yu, Huang, Feiran, Zhou, Sheng, Bu, Jiajun, Lin, Allen, Caverlee, James, Karray, Fakhri, King, Irwin, Yu, Philip S.
Cold-start problem is one of the long-standing challenges in recommender systems, focusing on accurately modeling new or interaction-limited users or items to provide better recommendations. Due to the diversification of internet platforms and the ex
Externí odkaz:
http://arxiv.org/abs/2501.01945
Autor:
Li, Ziwen, Huang, Jiaxin, Chen, Runnan, Che, Yunlong, Guo, Yandong, Liu, Tongliang, Karray, Fakhri, Gong, Mingming
Reconstructing dynamic urban scenes presents significant challenges due to their intrinsic geometric structures and spatiotemporal dynamics. Existing methods that attempt to model dynamic urban scenes without leveraging priors on potentially moving r
Externí odkaz:
http://arxiv.org/abs/2412.03473
Autor:
Song, Kun, Solozabal, Ruben, hao, Li, Ren, Lu, Abdar, Moloud, Li, Qing, Karray, Fakhri, Takac, Martin
Hyperbolic representation learning is well known for its ability to capture hierarchical information. However, the distance between samples from different levels of hierarchical classes can be required large. We reveal that the hyperbolic discriminan
Externí odkaz:
http://arxiv.org/abs/2410.22026
Reinforcement Learning (RL) algorithms suffer from the dependency on accurately engineered reward functions to properly guide the learning agents to do the required tasks. Preference-based reinforcement learning (PbRL) addresses that by utilizing hum
Externí odkaz:
http://arxiv.org/abs/2408.11943
Large vision-language models (LVLMs) have made significant progress in recent years. While LVLMs exhibit excellent ability in language understanding, question answering, and conversations of visual inputs, they are prone to producing hallucinations.
Externí odkaz:
http://arxiv.org/abs/2408.05767
The prevalence of AI-generated imagery has raised concerns about the authenticity of astronomical images, especially with advanced text-to-image models like Stable Diffusion producing highly realistic synthetic samples. Existing detection methods, pr
Externí odkaz:
http://arxiv.org/abs/2407.06817
Existing vision-text contrastive learning models enhance representation transferability and support zero-shot prediction by matching paired image and caption embeddings while pushing unrelated pairs apart. However, astronomical image-label datasets a
Externí odkaz:
http://arxiv.org/abs/2407.07315
The intersection of Astronomy and AI encounters significant challenges related to issues such as noisy backgrounds, lower resolution (LR), and the intricate process of filtering and archiving images from advanced telescopes like the James Webb. Given
Externí odkaz:
http://arxiv.org/abs/2405.13267
Autor:
Huang, Feiran, Bei, Yuanchen, Yang, Zhenghang, Jiang, Junyi, Chen, Hao, Shen, Qijie, Wang, Senzhang, Karray, Fakhri, Yu, Philip S.
Recommending cold items remains a significant challenge in billion-scale online recommendation systems. While warm items benefit from historical user behaviors, cold items rely solely on content features, limiting their recommendation performance and
Externí odkaz:
http://arxiv.org/abs/2402.09176