https://scholarshare.temple.edu/server/api/core/bitstreams/5f8a9579-d279-412d-88f3-744d54fdbdad/content
The ef ciency of the proviral DNA excision by CRISPR-Cas9 in fi the spleens of two infected humanized mice from the CRISPR-Cas9 and LASER ART group (animals where no rebound was observed) was determined by ddPCR.
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://ibit.temple.edu/wp-content/uploads/2014/04/IBITSportsanalytics.pdf
Foreword Sports enthusiasts are likely familiar with the growing importance of analytics in sports franchise operations. Sports teams use analytics in a wide range of activities, including game management, player development, marketing, and finance. As a result, sports are becoming a proving ground for tomorrow’s business analytics technologies. This IBIT Report provides a history and the ...
https://sites.temple.edu/pdames/files/2016/07/DamesTokekarKumarISRR2015.pdf
Abstract Target tracking is a fundamental problem in robotics research and has been the subject of detailed studies over the years. In this paper, we introduce a new formulation, based on the mathematical concept of random finite sets, that allows for tracking an unknown and dynamic number of mobile targets with a team of robots. We show how to employ the Probability Hypothesis Density filter ...
https://cis.temple.edu/~latecki/Courses/CIS2166-Fall16/Lectures/MatrixAlg1.pdf
A matrix is a rectangular array of numbers or other mathematical objects, for which operations such as addition and multiplication are defined. Most of this article focuses on real matrices, i.e., matrices whose elements are real numbers. For instance, this is a real matrix: The numbers, symbols or expressions in the matrix are called its entries or its elements. The horizontal and vertical ...
https://cis.temple.edu/~latecki/Courses/CIS2033-Spring12/ElementaryProbabilityforApplications/ch3.pdf
5/36 5 The same result holds if B = “The first die is k” and 2 ≤ k ≤ 6. Carrying this reasoning further, we see that given the outcome lies in A, all five possibilities have the same probability. This should not be surprising. The original probabil-ity is uniform over the 36 possibilities, so when we condition on the occurrence of A, its five outcomes are equally likely.
https://sites.temple.edu/xifanwu/files/2020/10/Identification-of-a-functional-point-defect-in-SrTiO3.pdf
Point defects are universally present in every material, and significantly affect the physical properties and functions of materials [1–4]. In complex oxides, point defects have played a critical role in determining structural, electronic, optical, and electrochemical properties, especially via modifying the charge, spin, and orbital states of cations (e.g., transition metal ions). Recent ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/Paper%206190%20Camera%20Ready%20Version.pdf
a major challenge for federated learning in diverse settings. Personalized Federated Learning (PFL), [Tan et al., 2022a] addresses these issues by allowing client-specific models that leverage global insights to enhance local outcomes. The main challenge in PFL lies in balancing global knowledge sharing with preserving client-specific information, making the trade- off an important research ...
https://foxonline.temple.edu/guides/canvas/color-coding-of-gradebook/
What do the Colors in Gradebook Mean? Gradebook includes a default set of colors that indicate different assignment statuses.
https://cis.temple.edu/~jiewu/research/publications/Publication_files/Paper%206750%20Camera%20Ready%20Version.pdf
1 Introduction Federated learning (FL) [Koneˇcn ́y et al., 2017], a widely-used framework for distributed machine learning, is a signif-icant research focus. Most FL algorithms, such as the clas-sic FedAvg, fall into Synchronous Federated Learning (SFL). They require the server to wait for all selected clients’ lo-cal training and uploads before aggregating updates, and as-sume uniform ...