Search Results - Yu, Yaoliang

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  1. 1
    DeepAntigen: a novel method for neoantigen prioritization via 3D genome and deep sparse learning

    DeepAntigen: a novel method for neoantigen prioritization via 3D genome and deep sparse learning by Shi, Yi, Guo, Zehua, Su, Xianbin, Meng, Luming, Zhang, Mingxuan, Sun, Jing, Wu, Chao, Zheng, Minhua, Shang, Xueyin, Zou, Xin, Cheng, Wangqiu, Yu, Yaoliang, Cai, Yujia, Zhang, Chaoyi, Cai, Weidong, Da, Lin-Tai, He, Guang, Han, Ze-Guang

    Published in Bioinformatics
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  2. 2
    Distance metric learning by minimal distance maximization

    Distance metric learning by minimal distance maximization by Yu, Yaoliang, Jiang, Jiayan, Zhang, Liming

    Published in Pattern recognition
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  3. 3
    Petuum: A New Platform for Distributed Machine Learning on Big Data

    Petuum: A New Platform for Distributed Machine Learning on Big Data by Xing, Eric P., Qirong Ho, Wei Dai, Jin Kyu Kim, Jinliang Wei, Seunghak Lee, Xun Zheng, Pengtao Xie, Kumar, Abhimanu, Yaoliang Yu

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  4. 4
    A novel neoantigen discovery approach based on chromatin high order conformation

    A novel neoantigen discovery approach based on chromatin high order conformation by Shi, Yi, Zhang, Mingxuan, Meng, Luming, Su, Xianbin, Shang, Xueying, Guo, Zehua, Li, Qingjiao, Lin, Mengna, Zou, Xin, Luo, Qing, Yu, Yaoliang, Wu, Yanting, Da, Lintai, Cai, Tom Weidong, He, Guang, Han, Ze-Guang

    Published in BMC medical genomics
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  5. 5
    Federated Learning Meets Multi-Objective Optimization

    Federated Learning Meets Multi-Objective Optimization by Hu, Zeou, Shaloudegi, Kiarash, Zhang, Guojun, Yu, Yaoliang

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  6. 6
    MT-MAG: Accurate and interpretable machine learning for complete or partial taxonomic assignments of metagenomeassembled genomes

    MT-MAG: Accurate and interpretable machine learning for complete or partial taxonomic assignments of metagenomeassembled genomes by Li, Wanxin, Kari, Lila, Yu, Yaoliang, Hug, Laura A

    Published in PloS one
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  7. 7
    Problems and Opportunities in Training Deep Learning Software Systems: An Analysis of Variance

    Problems and Opportunities in Training Deep Learning Software Systems: An Analysis of Variance by Pham, Hung Viet, Qian, Shangshu, Wang, Jiannan, Lutellier, Thibaud, Rosenthal, Jonathan, Tan, Lin, Yu, Yaoliang, Nagappan, Nachiappan

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  8. 8
    DEVIATE: A Deep Learning Variance Testing Framework

    DEVIATE: A Deep Learning Variance Testing Framework by Pham, Hung Viet, Kim, Mijung, Tan, Lin, Yu, Yaoliang, Nagappan, Nachiappan

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  9. 9
    A PENALIZED REGRESSION MODEL FOR THE JOINT ESTIMATION OF EQTL ASSOCIATIONS AND GENE NETWORK STRUCTURE

    A PENALIZED REGRESSION MODEL FOR THE JOINT ESTIMATION OF EQTL ASSOCIATIONS AND GENE NETWORK STRUCTURE by Marchetti-Bowick, Micol, Yu, Yaoliang, Wu, Wei, Xing, Eric P.

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  10. 10
    A Novel Facial Feature Point Localization Method on 3D Faces

    A Novel Facial Feature Point Localization Method on 3D Faces by Peng Guan, Yaoliang Yu, Liming Zhang

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  11. 11
    One Sample Fits All: Approximating All Probabilistic Values Simultaneously and Efficiently

    One Sample Fits All: Approximating All Probabilistic Values Simultaneously and Efficiently by Li, Weida, Yu, Yaoliang

    Published in arXiv.org
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  12. 12
    Unlocking The Potential of Adaptive Attacks on Diffusion-Based Purification

    Unlocking The Potential of Adaptive Attacks on Diffusion-Based Purification by Kassis, Andre, Hengartner, Urs, Yu, Yaoliang

    Published in arXiv.org
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  13. 13
    Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning

    Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning by Saber Malekmohammadi, Yu, Yaoliang, Cao, Yang

    Published in arXiv.org
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  14. 14
    Last-iterate Convergence in Regularized Graphon Mean Field Game

    Last-iterate Convergence in Regularized Graphon Mean Field Game by Dong, Jing, Wang, Baoxiang, Yu, Yaoliang

    Published in arXiv.org
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  15. 15
    Uncoupled and Convergent Learning in Monotone Games under Bandit Feedback

    Uncoupled and Convergent Learning in Monotone Games under Bandit Feedback by Dong, Jing, Wang, Baoxiang, Yu, Yaoliang

    Published in arXiv.org
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  16. 16
    Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games

    Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games by Dong, Jing, Wang, Baoxiang, Yu, Yaoliang

    Published in arXiv.org
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  17. 17
    Structure Preserving Diffusion Models

    Structure Preserving Diffusion Models by Lu, Haoye, Szabados, Spencer, Yu, Yaoliang

    Published in arXiv.org
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  18. 18
    Indiscriminate Data Poisoning Attacks on Neural Networks

    Indiscriminate Data Poisoning Attacks on Neural Networks by Lu, Yiwei, Kamath, Gautam, Yu, Yaoliang

    Published in arXiv.org
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  19. 19
    Exploring the Limits of Model-Targeted Indiscriminate Data Poisoning Attacks

    Exploring the Limits of Model-Targeted Indiscriminate Data Poisoning Attacks by Lu, Yiwei, Kamath, Gautam, Yu, Yaoliang

    Published in arXiv.org
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  20. 20
    Convergence of Gradient Methods on Bilinear Zero-Sum Games

    Convergence of Gradient Methods on Bilinear Zero-Sum Games by Zhang, Guojun, Yu, Yaoliang

    Published in arXiv.org
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