基本信息
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Bio
My research in large-scale data mining and machine learning (ML) focuses on principled, interpretable, and scalable methods for discovering and summarizing the unknown unknowns in the world's data by leveraging the inherent connections within them. These connections are naturally modeled in networks or graphs, which in turn span every facet of our lives: email communication networks, knowledge graphs for web search, social networks, coauthorship graphs, brain networks, artificial neural networks, and more. My work harnesses the massive scale, heterogeneity, and complexity of these data by providing concise and interpretable network summaries as a way to: (a) speed up follow-up analysis and methods that only need to apply on smaller, representative data; (b) gain understanding into the underlying processes, and inform our decisions by removing the burden of manually sifting through mountains of data; and (c) provide insights into scientific data, generate new hypotheses, and lead to novel scientific discoveries.
Research Interests
Papers共 187 篇Author StatisticsCo-AuthorSimilar Experts
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ICLR 2024 (2024)
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arxiv(2024)
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arxiv(2024)
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arxiv(2024)
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Puja Trivedi,Ryan A Rossi,David Arbour, Tong Yu,Franck Dernoncourt, Sungchul Kim,Nedim Lipka,Namyong Park,Nesreen Ahmed,Danai Koutra
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arxiv(2024)
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ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)pp.6810-6814, (2024)
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