基本信息
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职业迁徙
个人简介
Current Research:
Large Scale Unsupervised Learning - Algorithms with theoretical guarantees for estimating mixtures of Gaussians in the presence of outliers.
Large Scale Supervised/Semi-Supervised Learning - Incremental methods for learning models from millions of observatiosn with thousands of classes.
Online Learning - Updating sufficient statistics in an online fashion to be able to extract models of different complexities at any time.
Robust Learning - Learning models that know when the data is outside the training distribution.
Feature Selection with Annealing - A generic method for feature selection and model learning that outperforms boosting and methods based on sparsity inducing penalties such as L1, SCAD, and MCP.
Large Scale Unsupervised Learning - Algorithms with theoretical guarantees for estimating mixtures of Gaussians in the presence of outliers.
Large Scale Supervised/Semi-Supervised Learning - Incremental methods for learning models from millions of observatiosn with thousands of classes.
Online Learning - Updating sufficient statistics in an online fashion to be able to extract models of different complexities at any time.
Robust Learning - Learning models that know when the data is outside the training distribution.
Feature Selection with Annealing - A generic method for feature selection and model learning that outperforms boosting and methods based on sparsity inducing penalties such as L1, SCAD, and MCP.
研究兴趣
论文共 150 篇作者统计合作学者相似作者
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arxiv(2023)
CoRRno. 9 (2023): 5936-5955
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arxiv(2023)
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arxiv(2023)
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CoRRno. 8 (2023): 4072-4072
Boshi Wang,Adrian Barbu
Electronicsno. 20 (2022): 3323
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D-Core
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