statistical machine learning and deep learning algorithms
My research deals with developing and analyzing efficient and effective machine learning and deep learning algorithms and applying these algorithms to a large variety of applications such as computer vision, signal processing, medical image processing, speech processing, and natural language processing.
Recent Deep Learning Publications:
- Calibration of medical imaging classification systems with weight scaling, Lior Frenkel and Jacob Goldberger, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022.
- Long context question answering via supervised contrastive learning, Avi Caciularu, Ido Dagan, Jacob Goldberger and Arman Cohan, The Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2022.
- A proposition-level clustering approach for multi-document summarization, Ori Ernst, Avi Caciularu, Ori Shapira, Ramakanth Pasunuru, Mohit Bansal, Jacob Goldberger and Ido Dagan, The Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL) , 2022.
- Class-based attention mechanism for chest radiograph multi-label categorization, David Sriker, Hayit Greenspan and Jacob Goldberger, IEEE International Symposium on Biomedical Imaging (ISBI), 2022.
- Adaptation of a multisite network to a new clinical site via batch-normalization similarity, Shira Kasten-Serlin, Jacob Goldberger and Hayit Greenspan, IEEE International Symposium on Biomedical Imaging (ISBI), 2022.
- Network calibration by temperature scaling based on the predicted confidence, Lior Frenkel and Jacob Goldberger, The European Signal Processing Conference (EUSIPCO), 2022.
I'm a member of the Bar-Ilan Data Science Institute.
My Erdös Number is 2.