Zobrazeno 1 - 10
of 10 420
pro vyhledávání: '"A Hijazi"'
This study develops a deep learning-based approach to automate inbound load plan adjustments for a large transportation and logistics company. It addresses a critical challenge for the efficient and resilient planning of E-commerce operations in pres
Externí odkaz:
http://arxiv.org/abs/2411.17502
We present a neural network-enhanced column generation (CG) approach for a parallel machine scheduling problem. The proposed approach utilizes an encoder-decoder attention model, namely the transformer and pointer architectures, to develop job sequen
Externí odkaz:
http://arxiv.org/abs/2410.15601
The paper studies a large-scale order fulfillment problem for a leading e-commerce company in the United States. The challenge involves selecting fulfillment centers and shipping carriers with observational data only to efficiently process orders fro
Externí odkaz:
http://arxiv.org/abs/2409.06918
Autor:
Hijazi, Faris, AlHarbi, Somayah, AlHussein, Abdulaziz, Shairah, Harethah Abu, AlZahrani, Reem, AlShamlan, Hebah, Knio, Omar, Turkiyyah, George
The rapid advancements in Large Language Models (LLMs) have led to significant improvements in various natural language processing tasks. However, the evaluation of LLMs' legal knowledge, particularly in non-English languages such as Arabic, remains
Externí odkaz:
http://arxiv.org/abs/2408.07983
Solid-State Reactions at Niobium-Germanium Interfaces in Hybrid Superconductor-Semiconductor Devices
Autor:
Langa Jr., Bernardo, Sapkota, Deepak, Lainez, Ivan, Haight, Richard, Srijanto, Bernadeta, Feldman, Leonard, Hijazi, Hussein, Zhu, Xiangyu, Hu, Lifang, Kim, Moon, Sardashti, Kasra
Hybrid Superconductor-Semiconductor (S-Sm) materials systems are promising candidates for quantum computing applications. Their integration into superconducting electronics has enabled on-demand voltage tunability at millikelvin temperatures. Ge quan
Externí odkaz:
http://arxiv.org/abs/2405.20517
Autor:
Hijazi, Maeshal, Dehghanian, Payman
Maintaining the privacy of power system data is essential for protecting sensitive information and ensuring the operation security of critical infrastructure. Therefore, the adoption of centralized deep learning (DL) transient stability assessment (T
Externí odkaz:
http://arxiv.org/abs/2403.03126
As more speech technologies rely on a supervised deep learning approach with clean speech as the ground truth, a methodology to onboard said speech at scale is needed. However, this approach needs to minimize the dependency on human listening and ann
Externí odkaz:
http://arxiv.org/abs/2402.12482
Publikováno v:
Addressing Anti-Asian Racism with Social Work Advocacy and Action, 2024.
Externí odkaz:
https://doi.org/10.1093/oso/9780197672242.003.0010
Autor:
Wang, Runhui, Kong, Luyang, Tao, Yefan, Borthwick, Andrew, Golac, Davor, Johnson, Henrik, Hijazi, Shadie, Deng, Dong, Zhang, Yongfeng
Locality-sensitive hashing (LSH) is a fundamental algorithmic technique widely employed in large-scale data processing applications, such as nearest-neighbor search, entity resolution, and clustering. However, its applicability in some real-world sce
Externí odkaz:
http://arxiv.org/abs/2401.18064
Autor:
Zhao, Haoruo, Hijazi, Hassan, Jones, Haydn, Moore, Juston, Tanneau, Mathieu, Van Hentenryck, Pascal
Neural network verification aims at providing formal guarantees on the output of trained neural networks, to ensure their robustness against adversarial examples and enable their deployment in safety-critical applications. This paper introduces a new
Externí odkaz:
http://arxiv.org/abs/2401.05280