{"type":"conference","doi":"10.1109/ICCVW.2019.00097","author":[{"last_name":"Rannen-Triki","first_name":"Amal","full_name":"Rannen-Triki, Amal"},{"full_name":"Berman, Maxim","last_name":"Berman","first_name":"Maxim"},{"id":"3D50B0BA-F248-11E8-B48F-1D18A9856A87","full_name":"Kolmogorov, Vladimir","last_name":"Kolmogorov","first_name":"Vladimir"},{"last_name":"Blaschko","first_name":"Matthew B.","full_name":"Blaschko, Matthew B."}],"day":"01","publication":"Proceedings of the 2019 International Conference on Computer Vision Workshop","external_id":{"isi":["000554591600090"]},"month":"10","article_processing_charge":"No","publication_identifier":{"isbn":["9781728150239"]},"date_updated":"2023-09-08T11:19:12Z","date_published":"2019-10-01T00:00:00Z","conference":{"location":"Seoul, South Korea","end_date":"2019-10-28","name":"ICCVW: International Conference on Computer Vision Workshop","start_date":"2019-10-27"},"publication_status":"published","citation":{"apa":"Rannen-Triki, A., Berman, M., Kolmogorov, V., &#38; Blaschko, M. B. (2019). Function norms for neural networks. In <i>Proceedings of the 2019 International Conference on Computer Vision Workshop</i>. Seoul, South Korea: IEEE. <a href=\"https://doi.org/10.1109/ICCVW.2019.00097\">https://doi.org/10.1109/ICCVW.2019.00097</a>","ista":"Rannen-Triki A, Berman M, Kolmogorov V, Blaschko MB. 2019. Function norms for neural networks. Proceedings of the 2019 International Conference on Computer Vision Workshop. ICCVW: International Conference on Computer Vision Workshop, 748–752.","chicago":"Rannen-Triki, Amal, Maxim Berman, Vladimir Kolmogorov, and Matthew B. Blaschko. “Function Norms for Neural Networks.” In <i>Proceedings of the 2019 International Conference on Computer Vision Workshop</i>. IEEE, 2019. <a href=\"https://doi.org/10.1109/ICCVW.2019.00097\">https://doi.org/10.1109/ICCVW.2019.00097</a>.","ama":"Rannen-Triki A, Berman M, Kolmogorov V, Blaschko MB. Function norms for neural networks. In: <i>Proceedings of the 2019 International Conference on Computer Vision Workshop</i>. IEEE; 2019. doi:<a href=\"https://doi.org/10.1109/ICCVW.2019.00097\">10.1109/ICCVW.2019.00097</a>","short":"A. Rannen-Triki, M. Berman, V. Kolmogorov, M.B. Blaschko, in:, Proceedings of the 2019 International Conference on Computer Vision Workshop, IEEE, 2019.","mla":"Rannen-Triki, Amal, et al. “Function Norms for Neural Networks.” <i>Proceedings of the 2019 International Conference on Computer Vision Workshop</i>, 748–752, IEEE, 2019, doi:<a href=\"https://doi.org/10.1109/ICCVW.2019.00097\">10.1109/ICCVW.2019.00097</a>.","ieee":"A. Rannen-Triki, M. Berman, V. Kolmogorov, and M. B. Blaschko, “Function norms for neural networks,” in <i>Proceedings of the 2019 International Conference on Computer Vision Workshop</i>, Seoul, South Korea, 2019."},"department":[{"_id":"VlKo"}],"language":[{"iso":"eng"}],"article_number":"748-752","_id":"7639","abstract":[{"lang":"eng","text":"Deep neural networks (DNNs) have become increasingly important due to their excellent empirical performance on a wide range of problems. However, regularization is generally achieved by indirect means, largely due to the complex set of functions defined by a network and the difficulty in measuring function complexity. There exists no method in the literature for additive regularization based on a norm of the function, as is classically considered in statistical learning theory. In this work, we study the tractability of function norms for deep neural networks with ReLU activations. We provide, to the best of our knowledge, the first proof in the literature of the NP-hardness of computing function norms of DNNs of 3 or more layers. We also highlight a fundamental difference between shallow and deep networks. In the light on these results, we propose a new regularization strategy based on approximate function norms, and show its efficiency on a segmentation task with a DNN."}],"oa_version":"None","date_created":"2020-04-05T22:00:50Z","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publisher":"IEEE","year":"2019","scopus_import":"1","title":"Function norms for neural networks","quality_controlled":"1","status":"public","isi":1}