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pro vyhledávání: '"Ketenci, Mert"'
Shapley values have emerged as a foundational tool in machine learning (ML) for elucidating model decision-making processes. Despite their widespread adoption and unique ability to satisfy essential explainability axioms, computational challenges per
Externí odkaz:
http://arxiv.org/abs/2402.04211
Survival analysis is a widely-used technique for analyzing time-to-event data in the presence of censoring. In recent years, numerous survival analysis methods have emerged which scale to large datasets and relax traditional assumptions such as propo
Externí odkaz:
http://arxiv.org/abs/2311.01660
We present a novel stochastic variational Gaussian process ($\mathcal{GP}$) inference method, based on a posterior over a learnable set of weighted pseudo input-output points (coresets). Instead of a free-form variational family, the proposed coreset
Externí odkaz:
http://arxiv.org/abs/2311.01409
Summarization of clinical narratives is a long-standing research problem. Here, we introduce the task of hospital-course summarization. Given the documentation authored throughout a patient's hospitalization, generate a paragraph that tells the story
Externí odkaz:
http://arxiv.org/abs/2105.00816
We introduce Latent Meaning Cells, a deep latent variable model which learns contextualized representations of words by combining local lexical context and metadata. Metadata can refer to granular context, such as section type, or to more global cont
Externí odkaz:
http://arxiv.org/abs/2010.02010
Akademický článek
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Autor:
Adams G; Columbia University, New York, NY., Alsentzer E; Harvard-MIT's Health Science and Technology, Cambridge, MA., Ketenci M; Columbia University, New York, NY., Zucker J; Columbia University, New York, NY., Elhadad N; Columbia University, New York, NY.
Publikováno v:
Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting [Proc Conf] 2021 Jun; Vol. 2021, pp. 4794-4811.
Autor:
Adams G; Columbia University, New York, NY, US., Ketenci M; Columbia University, New York, NY, US., Bhave S; Columbia University, New York, NY, US., Perotte A; Columbia University, New York, NY, US., Elhadad N; Columbia University, New York, NY, US.
Publikováno v:
Proceedings of machine learning research [Proc Mach Learn Res] 2020 Dec; Vol. 136, pp. 12-40.