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pro vyhledávání: '"P MOUDGIL"'
Autor:
Knyazev, Boris, Moudgil, Abhinav, Lajoie, Guillaume, Belilovsky, Eugene, Lacoste-Julien, Simon
Neural network training can be accelerated when a learnable update rule is used in lieu of classic adaptive optimizers (e.g. Adam). However, learnable update rules can be costly and unstable to train and use. A simpler recently proposed approach to a
Externí odkaz:
http://arxiv.org/abs/2409.04434
Publikováno v:
Indian Journal of Animal Sciences, Vol 91, Iss 6 (2021)
Classical swine fever (CSF) is a highly contagious viral disease of pigs and is responsible for significant economic losses due to high morbidity and mortality. Pigs from nine different piggery units in Haryana were investigated for CSF suspected out
Externí odkaz:
https://doaj.org/article/9cc4cf615ab141f1a5fd301bce9b5483
Autor:
Joseph, Charles-Étienne, Thérien, Benjamin, Moudgil, Abhinav, Knyazev, Boris, Belilovsky, Eugene
Communication-efficient variants of SGD, specifically local SGD, have received a great deal of interest in recent years. These approaches compute multiple gradient steps locally, that is on each worker, before averaging model parameters, helping reli
Externí odkaz:
http://arxiv.org/abs/2312.02204
Publikováno v:
Alexandria Engineering Journal, Vol 103, Iss , Pp 169-179 (2024)
Efficient character recognition in ancient handwritten Devanagari documents is crucial for societal advancements. Challenges such as overlapping characters, missing headlines, and over-inked stains further complicate the recognition process. In respo
Externí odkaz:
https://doaj.org/article/6e6c318ba89641d3b1d656f4d80f6b05
Autor:
Amgad Mentias, Milind Y. Desai, Ambarish Pandey, Issam Motairek, Rohit Moudgil, Chonyang Albert, Salil V. Deo, Robert D. Brook, Venu Menon, Sanjay Rajagopalan, Sadeer Al‐Kindi
Publikováno v:
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, Vol 13, Iss 15 (2024)
Background Exposure to fine particulate matter (
Externí odkaz:
https://doaj.org/article/4b6a5432f067476ab8ea6ff49447162a
Autor:
Ernoult, Maxence, Normandin, Fabrice, Moudgil, Abhinav, Spinney, Sean, Belilovsky, Eugene, Rish, Irina, Richards, Blake, Bengio, Yoshua
The development of biologically-plausible learning algorithms is important for understanding learning in the brain, but most of them fail to scale-up to real-world tasks, limiting their potential as explanations for learning by real brains. As such,
Externí odkaz:
http://arxiv.org/abs/2201.13415
Natural language instructions for visual navigation often use scene descriptions (e.g., "bedroom") and object references (e.g., "green chairs") to provide a breadcrumb trail to a goal location. This work presents a transformer-based vision-and-langua
Externí odkaz:
http://arxiv.org/abs/2110.14143
Recent Visual Question Answering (VQA) models have shown impressive performance on the VQA benchmark but remain sensitive to small linguistic variations in input questions. Existing approaches address this by augmenting the dataset with question para
Externí odkaz:
http://arxiv.org/abs/2010.06087
Recent works have proposed several long term tracking benchmarks and highlight the importance of moving towards long-duration tracking to bridge the gap with application requirements. The current evaluation methodologies, however, do not focus on sev
Externí odkaz:
http://arxiv.org/abs/1910.12273
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