https://community.mis.temple.edu/mis3537beaver2016/files/2016/01/Article-Managing-Supply-Chain-Inventory-Pitfalls-and-Opportunities.pdf
Managing Supply Chain Inventory: Pitfalls and Opportunities Hau L. Lee Corey Billington YOU CONSIDER DISTRIBUTION AND INVENTORY COSTS WHEN YOU DESIGN L/ PRODUCTS? CAN YOU KEEP YOUR CUSTOMERS INFORMED OF WHEN THEIR orders will arrive? Do you know what kind of inventory control systems your dealers use? If not, you've succumbed to the pitfalls of inventory management. You're not alone ...
https://www.fox.temple.edu/directory/detmar-william-straub-tug28766
Biography Since 2015, Detmar has been a Research Professor and IBIT Fellow at Temple University’s Fox School. A Regents Professor Emeritus of the University System of Georgia and formerly holding a distinguished professorship in the CIS Dept. of the Robinson School of Business at Georgia State University, Detmar has conducted research in the areas of cybersecurity, digital transformation, e ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/FedCPD.pdf
Both challenges pertain to optimizing personalized feder-ated learning, yet their solutions don’t cross-apply. Parame-ter decoupling protects local knowledge to prevent forgetting but falls short on sharing global insights, thus struggling with generalization. On the other hand, prototype learning curbs overfitting and boosts generalization by sharing class proto-types, yet it misses ...
https://medicine.temple.edu/education/biomedical-sciences-graduate-program/admissions
The application deadline is February 15. An application will be considered complete once the required application materials have been received and verified. Note that there is no deadline extension for incomplete applications. All applicants to the MS program must apply through BioMedical’s Centralized Application Service (BioMedCAS). Applicants should check their application’s status on ...
https://community.mis.temple.edu/mis5203sec001spring2021/files/2021/02/5203_04_Requirements.pdf
Explain the advantages and pitfalls of observing workers and analyzing business documents to determine system requirements. Explain how computing can provide support for requirements determination.
https://cis.temple.edu/~jiewu/research/publications/Publication_files/m48122-zhao%20final.pdf
ArrayPipe: Introducing Job-Array Pipeline Parallelism for High Throughput Model Exploration Hairui Zhao1, Hongliang Li1,2,∗, Qi Tian1, Jie Wu3, Meng Zhang1, Xiang Li1, Haixiao Xu4
https://cis.temple.edu/~jiewu/research/publications/Publication_files/INFOCOM2024_PSFL%20Parallel-Sequential%20Federated%20Learning%20with%20Convergence%20Guarantees.pdf
Abstract—Federated Learning (FL) is a novel distributed learning paradigm which can coordinate multiple clients to jointly train a machine learning model by using their local data samples. Existing FL works can be roughly divided into two categories according to the modes of model training: Parallel FL (PFL) and Sequential FL (SFL). PFL can speed up each round of model training time through ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/Privacy-Preserving_Federated_Neural_Architecture_Search_With_Enhanced_Robustness_for_Edge_Computing.pdf
Abstract—With the development of large-scale artificial intelli-gence services, edge devices are becoming essential providers of data and computing power. However, these edge devices are not immune to malicious attacks. Federated learning (FL), while pro-tecting privacy of decentralized data through secure aggregation, struggles to trace adversaries and lacks optimization for hetero-geneity ...
https://cis.temple.edu/~wu/research/publications/Publication_files/Joint%20Dynamic%20Grouping%20and%20Gradient%20Coding%20for%20Time-critical%20Distributed%20Machine%20Learning%20in%20Heterogeneous%20Edge%20Networks-FINAL-VERSION.pdf
Abstract—In edge networks, distributed computing resources have been widely utilized to collaboratively perform a machine learning task by multiple nodes. However, the model training time in heterogeneous edge networks is becoming longer because of excessive computation and delay caused by slow nodes, namely stragglers. The parameter server even abandons stragglers which fail to return ...
https://cis.temple.edu/~yu/research/PPGSpotter-info24.pdf
Abstract—Free weight training (FWT) is of utmost importance for physical well-being. However, the success of FWT depends heavily on choosing the suitable workload, as improper selections can lead to suboptimal outcomes or injury. Current workload estimation approaches rely on manual recording and special-ized equipment with limited feedback. Therefore, we introduce PPGSpotter, a novel PPG ...