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QGen: On the Ability to Generalize in Quantization Aware Training

Autor: AskariHemmat, MohammadHossein, Jeddi, Ahmadreza, Hemmat, Reyhane Askari, Lazarevich, Ivan, Hoffman, Alexander, Sah, Sudhakar, Saboori, Ehsan, Savaria, Yvon, David, Jean-Pierre

Quantization lowers memory usage, computational requirements, and latency by utilizing fewer bits to represent model weights and activations. In this work, we investigate the generalization properties of quantized neural networks, a characteristic th

Externí odkaz: http://arxiv.org/abs/2404.11769

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Supermind Ideator: Exploring generative AI to support creative problem-solving

Autor: Rick, Steven R., Giacomelli, Gianni, Wen, Haoran, Laubacher, Robert J., Taubenslag, Nancy, Heyman, Jennifer L., Knicker, Max Sina, Jeddi, Younes, Maier, Hendrik, Dwyer, Stephen, Ragupathy, Pranav, Malone, Thomas W.

Previous efforts to support creative problem-solving have included (a) techniques (such as brainstorming and design thinking) to stimulate creative ideas, and (b) software tools to record and share these ideas. Now, generative AI technologies can sug

Externí odkaz: http://arxiv.org/abs/2311.01937

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Akademický článek

Investigation of Circular Woven Composite Preforms for Composite Pipes

Autor: Amid Hooman, Jeddi Ali Asghar Asgharian, Salehi Manouchehr, Dabiryan Hadi, Pejman Reza

Publikováno v: AUTEX Research Journal, Vol 16, Iss 2, Pp 100-108 (2016)

The main traditional technique for commercial manufacturing of composite pipes is filament winding in which the winding angle and the discontinuity of the structure (caused by starting and ending points of the winding process) are two important matte

Externí odkaz: https://doaj.org/article/3d70db581adc4d0f9e4b8e145aeacbca

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Using evolutionary machine learning to characterize and optimize co-pyrolysis of biomass feedstocks and polymeric wastes

Autor: Shahbeik, Hossein, Shafizadeh, Alireza, Nadian, Mohammad Hossein, Jeddi, Dorsa, Mirjalili, Seyedali, Yang, Yadong, Lam, Su Shiung, Pan, Junting, Tabatabaei, Meisam, Aghbashlo, Mortaza

Publikováno v: Journal of Cleaner Production, Volume 387, 10 February 2023, 135881

Co-pyrolysis of biomass feedstocks with polymeric wastes is a promising strategy for improving the quantity and quality parameters of the resulting liquid fuel. Numerous experimental measurements are typically conducted to find the optimal operating

Externí odkaz: http://arxiv.org/abs/2305.16350

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