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pro vyhledávání: '"Ali, Saheb"'
In regularization Self-Supervised Learning (SSL) methods for graphs, computational complexity increases with the number of nodes in graphs and embedding dimensions. To mitigate the scalability of non-contrastive graph SSL, we propose a novel approach
Externí odkaz:
http://arxiv.org/abs/2402.09603
WERank: Towards Rank Degradation Prevention for Self-Supervised Learning Using Weight Regularization
A common phenomena confining the representation quality in Self-Supervised Learning (SSL) is dimensional collapse (also known as rank degeneration), where the learned representations are mapped to a low dimensional subspace of the representation spac
Externí odkaz:
http://arxiv.org/abs/2402.09586
Autor:
Taghanaki, Saeid Asgari, Khani, Aliasghar, Pasand, Ali Saheb, Khasahmadi, Amir, Sanghi, Aditya, Willis, Karl D. D., Mahdavi-Amiri, Ali
Interpreting the learned features of vision models has posed a longstanding challenge in the field of machine learning. To address this issue, we propose a novel method that leverages the capabilities of language models to interpret the learned featu
Externí odkaz:
http://arxiv.org/abs/2309.00733
Autor:
Natrayan L., Ameen Fuad, Chinta Neelima Devi, Teja Nalla Bhanu, Muthu G., Kaliappan S., Ali Saheb, Vadiveloo Ashiwin
Publikováno v:
Green Processing and Synthesis, Vol 13, Iss 1, Pp 1-15 (2024)
This article explores the impact of nano-silica on the properties of woven flax fibre/epoxy composites. Using compression moulding, epoxy/flax/silica hybrid nanocomposites were produced. The nano-silica was dispersed in the epoxy matrix via ultrasoni
Externí odkaz:
https://doaj.org/article/900bcc154a76424287fef7440992cb58
Autor:
Murugan, Ramadurai, Raj Gunasekar, Kiren, Ali, Saheb, Sivalingam, Chitra, Subramanian, Raghunandhakumar, Venkatesan, Kumar, Selvaraj, Manickam, Malakondaiah, Suresh
Publikováno v:
In Journal of Industrial and Engineering Chemistry 25 September 2024 137:448-454
Autor:
Rezagholizadeh, Mehdi, Jafari, Aref, Salad, Puneeth, Sharma, Pranav, Pasand, Ali Saheb, Ghodsi, Ali
With ever growing scale of neural models, knowledge distillation (KD) attracts more attention as a prominent tool for neural model compression. However, there are counter intuitive observations in the literature showing some challenging limitations o
Externí odkaz:
http://arxiv.org/abs/2110.08532
Autor:
Ramya, J. Ramana, Ali, Saheb, K, Thanigai Arul, Vijayalakshmi, R., Gajendiran, J., Gnanam, S., Ramachandran, K.
Publikováno v:
In Microbial Pathogenesis August 2024 193
Autor:
Murugan, Ramadurai, Tamil Selvan, Silambarasan, Subramanian, Raghunandhakumar, S, Chitra, Ali, Saheb
Publikováno v:
In Journal of Photochemistry & Photobiology, A: Chemistry 1 August 2024 453
Publikováno v:
In International Journal of Biological Macromolecules March 2024 262 Part 2
Akademický článek
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