Zobrazeno 1 - 10
of 3 981
pro vyhledávání: '"Lin, Shao"'
Deep learning has made profound impacts in the domains of data mining and AI, distinguished by the groundbreaking achievements in numerous real-world applications and the innovative algorithm design philosophy. However, it suffers from the inconsiste
Externí odkaz:
http://arxiv.org/abs/2409.14174
Autor:
Lin, Shao-Bo
Parameter selection without communicating local data is quite challenging in distributed learning, exhibing an inconsistency between theoretical analysis and practical application of it in tackling distributively stored data. Motivated by the recentl
Externí odkaz:
http://arxiv.org/abs/2409.05070
We construct a hydrodynamic theory of active smectics A in two-dimensional space, including the creation/annihilation and motility of dislocations with Burgers' number $\pm1$. We derive analytical criteria on the set of parameters that lead to flows.
Externí odkaz:
http://arxiv.org/abs/2405.18250
Autor:
de la Rosa, Ezequiel, Reyes, Mauricio, Liew, Sook-Lei, Hutton, Alexandre, Wiest, Roland, Kaesmacher, Johannes, Hanning, Uta, Hakim, Arsany, Zubal, Richard, Valenzuela, Waldo, Robben, David, Sima, Diana M., Anania, Vincenzo, Brys, Arne, Meakin, James A., Mickan, Anne, Broocks, Gabriel, Heitkamp, Christian, Gao, Shengbo, Liang, Kongming, Zhang, Ziji, Siddiquee, Md Mahfuzur Rahman, Myronenko, Andriy, Ashtari, Pooya, Van Huffel, Sabine, Jeong, Hyun-su, Yoon, Chi-ho, Kim, Chulhong, Huo, Jiayu, Ourselin, Sebastien, Sparks, Rachel, Clèrigues, Albert, Oliver, Arnau, Lladó, Xavier, Chalcroft, Liam, Pappas, Ioannis, Bertels, Jeroen, Heylen, Ewout, Moreau, Juliette, Hatami, Nima, Frindel, Carole, Qayyum, Abdul, Mazher, Moona, Puig, Domenec, Lin, Shao-Chieh, Juan, Chun-Jung, Hu, Tianxi, Boone, Lyndon, Goubran, Maged, Liu, Yi-Jui, Wegener, Susanne, Kofler, Florian, Ezhov, Ivan, Shit, Suprosanna, Petzsche, Moritz R. Hernandez, Menze, Bjoern, Kirschke, Jan S., Wiestler, Benedikt
Diffusion-weighted MRI (DWI) is essential for stroke diagnosis, treatment decisions, and prognosis. However, image and disease variability hinder the development of generalizable AI algorithms with clinical value. We address this gap by presenting a
Externí odkaz:
http://arxiv.org/abs/2403.19425
Autor:
Lin, Shao-Bo
This paper focuses on scattered data fitting problems on spheres. We study the approximation performance of a class of weighted spectral filter algorithms, including Tikhonov regularization, Landaweber iteration, spectral cut-off, and iterated Tikhon
Externí odkaz:
http://arxiv.org/abs/2401.15294
Graph Neural Networks (GNNs) excel in delineating graph structures in diverse domains, including community analysis and recommendation systems. As the interpretation of GNNs becomes increasingly important, the demand for robust baselines and expansiv
Externí odkaz:
http://arxiv.org/abs/2401.04133
Autor:
Lin, Shao-Bo
This paper focuses on parameter selection issues of kernel ridge regression (KRR). Due to special spectral properties of KRR, we find that delicate subdivision of the parameter interval shrinks the difference between two successive KRR estimates. Bas
Externí odkaz:
http://arxiv.org/abs/2312.05885
With the help of massive data and rich computational resources, deep Q-learning has been widely used in operations research and management science and has contributed to great success in numerous applications, including recommender systems, supply ch
Externí odkaz:
http://arxiv.org/abs/2310.17915
For radial basis function (RBF) kernel interpolation of scattered data, Schaback in 1995 proved that the attainable approximation error and the condition number of the underlying interpolation matrix cannot be made small simultaneously. He referred t
Externí odkaz:
http://arxiv.org/abs/2310.16384
Data silos, mainly caused by privacy and interoperability, significantly constrain collaborations among different organizations with similar data for the same purpose. Distributed learning based on divide-and-conquer provides a promising way to settl
Externí odkaz:
http://arxiv.org/abs/2309.04236