Search Results for author: Jaewon Yang

Found 8 papers, 0 papers with code

Defining and Evaluating Network Communities based on Ground-truth

no code implementations28 May 2012 Jaewon Yang, Jure Leskovec

Identifying such communities of nodes has proven to be a challenging task mainly due to a plethora of definitions of a community, intractability of algorithms, issues with evaluation and the lack of a reliable gold-standard ground-truth.

Social and Information Networks Physics and Society

Attenuation correction for brain PET imaging using deep neural network based on dixon and ZTE MR images

no code implementations17 Dec 2017 Kuang Gong, Jaewon Yang, Kyungsang Kim, Georges El Fakhri, Youngho Seo, Quanzheng Li

With only Dixon MR images as the network input, the existing U-net structure was adopted and analysis using forty patient data sets shows it is superior than other Dixon based methods.

Image Reconstruction

Joint Correction of Attenuation and Scatter Using Deep Convolutional Neural Networks (DCNN) for Time-of-Flight PET

no code implementations28 Nov 2018 Jaewon Yang, Dookun Park, Jae Ho Sohn, Zhen Jane Wang, Grant T. Gullberg, Youngho Seo

Deep convolutional neural networks (DCNN) have demonstrated its capability to convert MR image to pseudo CT for PET attenuation correction in PET/MRI.

Salience and Market-aware Skill Extraction for Job Targeting

no code implementations27 May 2020 Baoxu Shi, Jaewon Yang, Feng Guo, Qi He

Based on the above promising results, we deployed the \model ~online to extract job targeting skills for all $20$M job postings served at LinkedIn.

Let AI Entertain You: Increasing User Engagement with Generative AI and Rejection Sampling

no code implementations16 Dec 2023 Jingying Zeng, Jaewon Yang, Waleed Malik, Xiao Yan, Richard Huang, Qi He

Second, there is a concern with the quality of the content generative AI produces, which often lacks the distinctiveness and authenticity that human-created content possesses.

FairSample: Training Fair and Accurate Graph Convolutional Neural Networks Efficiently

no code implementations26 Jan 2024 Zicun Cong, Shi Baoxu, Shan Li, Jaewon Yang, Qi He, Jian Pei

To address the bias in node features and model parameters, FairSample is complemented by a regularization objective to optimize fairness.

Attribute Fairness

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