https://cis.temple.edu/~latecki/Papers/Quan_DRBANET_ICIP_2022.pdf
ABSTRACT Due to the powerful ability to encode image details and semantics, many lightweight dual-resolution networks have been proposed in recent years. However, most of them ignore the benefit of boundary information. This paper introduces a lightweight dual-resolution network, called DRBANet, aim-ing to refine semantic segmentation results with the aid of boundary information. DRBANet also ...
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/~lakaemper/courses/cis350_2004/etc/moeller_triangle.pdf
1 Introduction Most collision detection algorithms, such as OBBTree [Gottschalk96], sphere hier-archies [Hubbard96] and BV-trees [Klosowski97], try to minimize the number of primitive-primitive intersections that have to be computed. Still, a fast and reliable method for computing the primitive-primitive intersection is desired. Since render-ing hardware is often targeted for triangles, the ...
https://cis.temple.edu/~pwang/Publication/OpenNARS.pdf
NARS utilises the Non-Axiomatic Logic (NAL) [9] for inference and the Nars-ese language for representing statements. The language and the logic are outside the scope of this document. The aim of this paper is to describe the current implementation of NARS in detail. The following aspects of the implementa-tion are focused on: memory management with concept centric processing, non-deterministic ...
https://cis.temple.edu/~latecki/Courses/AI-Fall10/Lectures/SVDEig08.ppt
If A is a symmetric and positive definite then SVD = Eigen decomposition EIG( i) = SVD( i2) Here AAT has an eigenvalue-eigenvector pair ( i2,ui) Alternatively, the vi are the eigenvectors of ATA with the same non zero eigenvalue i2 Example for SVD Let A be a symmetric, positive definite matrix U can be computed as V can be computed as Example ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/ICPP_2021_Duan.pdf
ABSTRACT Reducing the inference time of Deep Neural Networks (DNNs) is critical when running time sensitive applications on mobile devices. Existing research has shown that partitioning a DNN and ofloading a part of its computation to cloud servers can reduce the inference time. The single DNN partition problem has been extensively in-vestigated recently. However, in real-world applications, a ...
https://www.fox.temple.edu/sites/fox/files/documents/Cummins%20Conference%202022/RILA_Moenig_JRI_final.pdf
Registered index-linked annuities (RILAs) are increasingly popular equity-based re-tirement savings products o ered by U.S. life insurance companies. They combine features of xed-index annuities and traditional variable annuities (TVAs), o ering in-vestors equity exposure with downside protection in a tax-deferred setting. This article introduces RILAs to the academic literature by describing ...
https://sites.temple.edu/emilyksnell/files/2017/08/Wasik-Hindman-Snell-2016.pdf
ulary that is not often found in everyday conversations (Mol, Bus, deJong, & Smeets, 2008), and book reading is a common practice in early childhood settings as a means of introducing and teach-ing vocabulary words. With the increased emphasis on developing language and vocabulary in young children, especially children in poverty, it is important to examine what we know from the research on ...
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