Research output per year
Research output per year
Personal profile
About Me
Research:
- Machine Learning
- Deep Learning and Applications
- Feature Extraction and Selection
- Learning from Biomedical Data
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
הנדסת חשמל
Oct 2012 → Jul 2017
הנדסת חשמל
Oct 2010 → Oct 2012
הנדסת חשמל; פיזיקה, Bachelor
Mar 2006 → Mar 2010
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Multi-modal Differentiable Unsupervised Feature Selection
Yang, J., Lindenbaum, O., Kluger, Y. & Jaffe, A., 2023, In: Proceedings of Machine Learning Research. 216, p. 2400-2410 11 p.Research output: Contribution to journal › Conference article › peer-review
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Neuronal Cell Type Classification Using Locally Sparse Networks
Ophir, O., Shefi, O. & Lindenbaum, O., 2023, ICASSPW 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, Proceedings. Institute of Electrical and Electronics Engineers Inc., (ICASSPW 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, Proceedings).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Support recovery with Projected Stochastic Gates: Theory and application for linear models
Jana, S., Li, H., Yamada, Y. & Lindenbaum, O., Dec 2023, In: Signal Processing. 213, 109193.Research output: Contribution to journal › Article › peer-review
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Deep unsupervised feature selection by discarding nuisance and correlated features
Shaham, U., Lindenbaum, O., Svirsky, J. & Kluger, Y., Aug 2022, In: Neural Networks. 152, p. 34-43 10 p.Research output: Contribution to journal › Article › peer-review
4 Scopus citations -
Histopathologic and Machine Deep Learning Criteria to Predict Lymphoma Transformation in Bone Marrow Biopsies
Irshaid, L., Bleiberg, J., Weinberger, E., Garritano, J., Shallis, R. M., Patsenker, J., Lindenbaum, O., Kluger, Y., Katz, S. G. & Xu, M. L., Feb 2022, In: Archives of Pathology and Laboratory Medicine. 146, 2, p. 182-193 12 p.Research output: Contribution to journal › Article › peer-review
Open Access9 Scopus citations