Search Keywords

Results Restricted To:

https://www.temple.edu

Total Results: 5,330

Johnson and Hardwick Halls - Student Affairs

https://studentaffairs.temple.edu/housing/residence-halls/johnson-hardwick-halls

Johnson Hall and Hardwick Hall are twin 11-story buildings with a communal style environment focused on the first-year student experience. Each building houses 465 students on floors 2 through 11. As a traditional hall, bathrooms are shared with all occupants assigned to live on each floor (gender specific) and are cleaned daily by Housing Facilities staff. Each bedroom is heated and has air ...

Faculty | Lewis Katz School of Medicine | Lewis Katz School of Medicine

https://medicine.temple.edu/departments-centers/basic-science-departments/cancer-cellular-biology/faculty

FCCC Faculty (DCCB adjuncts) Nuclear Dynamics and Cancer Research Program Alfonso Bellacosa Lu Chen Vladimir Kolenko Hayan Lee Yu (Sunny) Liu Zeng-jie Yang Amy Whitaker Cancer Signaling and Microenvironment Research Program Joan Font-Burgada Kerry Campbell Jonathan Chernoff Yash Chhabra Denise Connolly Edna (Eti) Cukierman Roland Dunbrack, Jr James Duncan Mitchell Fane Warren Kruger Alana O ...

FedHAN: A Cache-Based Semi-Asynchronous Federated Learning Framework ...

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 ...

phylotree.js - a JavaScript library for application development and ...

https://scholarshare.temple.edu/bitstreams/b1ecc345-7a7c-4776-a366-9b5585e714d6/download

The embedded, clickable “picture in Fig. 2 Interfacing with PV, the JavaScript protein viewer, to interactively view substitutions inferred by an evolutionary model. Both libraries are documented and provide useful abstractions, so that combining them into one interoperable application can be achieved with a few dozen lines of code

A Faculty Guide to A.I. - Center for the Advancement of Teaching

https://teaching.temple.edu/teaching-technologies/faculty-guide-ai

Source material used for training data, the design of a model’s algorithm, data labeling processes, product design decisions and policy decisions all contribute to the possible replication of biases and unfair stereotypes (Ferrara, 2). Content generated by AI tools can seem accurate but be entirely made up, a phenomenon known as AI ...

Temple University Hey Lab :: Software

https://ccgg.temple.edu/heylab/software

We distribute several software programs for population genetic analysis. These programs have been developed over the years to suit the needs of research in the Hey lab, as well as for others to use. Programs were written in C, C++, and/or Python, and the source code is available. The programs should compile under different compilers. A Win32 executable version (.exe file) is also available for ...

Electrical Engineering (ECE) | Temple University Bulletin

https://bulletin.temple.edu/undergraduate/courses/ece/

ECE 1112. Electrical Applications. 2 Credit Hours. This course introduces basic concepts in Electrical and Computer Engineering, and demonstrates them in the context of real applications. Course topics include basics of DC and AC circuits, transistor, diode and operational amplifier circuits, digital logic gates and power supply operation.

Learning Pixel-wise Alignment for Unsupervised Image Stitching

https://cis.temple.edu/~latecki/Papers/ACM_MM2023.pdf

ABSTRACT Image stitching aims to align a pair of images in the same view. Generating precise alignment with natural structures is challeng-ing for image stitching, as there is no wider field-of-view image as a reference, especially in non-coplanar practical scenarios. In this paper, we propose an unsupervised image stitching frame-work, breaking through the coplanar constraints in homography ...

Computational Learning Theory: PAC Learning - Temple University

https://cis.temple.edu/~giorgio/cis587/readings/pac.html

Going back to our problem of learning the concept medium-built people, we can assume that the concept is represented as a rectangle, with sides parallel to the axes height/weight, and with dimensions height_min, height_max, weight_min, weight_max. We assume that also the hypotheses will take the form of a rectangle with the sides parallel to the axes.

Microsoft Word - Participation Rubric.docx

https://teaching.temple.edu/sites/teaching/files/resource/pdf/Participation%20Rubric.pdf

Strong Always arrives fully prepared with all assignments completed; demonstrates engagement with course readings and instructional materials through making connections, personal reflections, probing questions, or providing appropriate additional resources Actively and respectfully listens to peers and instructor; Follow up questions or comments demonstrate consideration for and seek ...