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In this work, we propose a new training procedure for multi-exit architectures based on the principle of knowledge distillation. The method encourage searly exits to mimic later, more accurate exits, by matching their output probabilities.\r\nExperiments on CIFAR100 and ImageNet show that distillation-based training significantly improves the accuracy of early exits while maintaining state-of-the-art accuracy for late ones. The method is particularly beneficial when training data is limited and it allows a straightforward extension to semi-supervised learning,i.e. making use of unlabeled data at training time. Moreover, it takes only afew lines to implement and incurs almost no computational overhead at training time, and none at all at test time.","lang":"eng"}],"type":"conference","language":[{"iso":"eng"}],"doi":"10.1109/ICCV.2019.00144","conference":{"start_date":"2019-10-27","location":"Seoul, Korea","end_date":"2019-11-02","name":"ICCV: International Conference on Computer Vision"},"project":[{"call_identifier":"FP7","name":"Lifelong Learning of Visual Scene Understanding","grant_number":"308036","_id":"2532554C-B435-11E9-9278-68D0E5697425"}],"isi":1,"quality_controlled":"1","oa":1,"external_id":{"isi":["000531438101047"]},"publication_identifier":{"isbn":["9781728148038"],"issn":["15505499"]},"month":"10","volume":"2019-October","date_updated":"2023-09-08T11:11:12Z","date_created":"2020-02-11T09:06:57Z","related_material":{"record":[{"id":"9418","relation":"dissertation_contains","status":"public"}]},"author":[{"id":"3EC6EE64-F248-11E8-B48F-1D18A9856A87","first_name":"Phuong","last_name":"Bui Thi Mai","full_name":"Bui Thi Mai, Phuong"},{"last_name":"Lampert","first_name":"Christoph","orcid":"0000-0001-8622-7887","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","full_name":"Lampert, Christoph"}],"department":[{"_id":"ChLa"}],"publisher":"IEEE","publication_status":"published","year":"2019","ec_funded":1,"file_date_updated":"2020-07-14T12:47:59Z"},{"publication_identifier":{"issn":["1049-5258"]},"month":"12","project":[{"_id":"268A44D6-B435-11E9-9278-68D0E5697425","grant_number":"805223","name":"Elastic Coordination for Scalable Machine Learning","call_identifier":"H2020"}],"isi":1,"quality_controlled":"1","external_id":{"arxiv":["1909.02253"],"isi":["000534424300084"]},"oa":1,"main_file_link":[{"url":"http://papers.nips.cc/paper/8379-powerset-convolutional-neural-networks","open_access":"1"}],"language":[{"iso":"eng"}],"conference":{"name":"NIPS: Conference on Neural Information Processing Systems","end_date":"2019-12-14","location":"Vancouver, Canada","start_date":"2019-12-08"},"ec_funded":1,"publisher":"Neural Information Processing Systems Foundation","department":[{"_id":"DaAl"}],"publication_status":"published","year":"2019","volume":32,"date_updated":"2023-09-08T11:13:52Z","date_created":"2020-02-28T10:03:24Z","author":[{"first_name":"Chris","last_name":"Wendler","full_name":"Wendler, Chris"},{"last_name":"Alistarh","first_name":"Dan-Adrian","orcid":"0000-0003-3650-940X","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87","full_name":"Alistarh, Dan-Adrian"},{"full_name":"Püschel, Markus","first_name":"Markus","last_name":"Püschel"}],"article_processing_charge":"No","day":"01","page":"927-938","citation":{"short":"C. Wendler, D.-A. Alistarh, M. Püschel, in:, Neural Information Processing Systems Foundation, 2019, pp. 927–938.","mla":"Wendler, Chris, et al. Powerset Convolutional Neural Networks. Vol. 32, Neural Information Processing Systems Foundation, 2019, pp. 927–38.","chicago":"Wendler, Chris, Dan-Adrian Alistarh, and Markus Püschel. “Powerset Convolutional Neural Networks,” 32:927–38. Neural Information Processing Systems Foundation, 2019.","ama":"Wendler C, Alistarh D-A, Püschel M. Powerset convolutional neural networks. In: Vol 32. Neural Information Processing Systems Foundation; 2019:927-938.","apa":"Wendler, C., Alistarh, D.-A., & Püschel, M. (2019). Powerset convolutional neural networks (Vol. 32, pp. 927–938). Presented at the NIPS: Conference on Neural Information Processing Systems, Vancouver, Canada: Neural Information Processing Systems Foundation.","ieee":"C. Wendler, D.-A. Alistarh, and M. Püschel, “Powerset convolutional neural networks,” presented at the NIPS: Conference on Neural Information Processing Systems, Vancouver, Canada, 2019, vol. 32, pp. 927–938.","ista":"Wendler C, Alistarh D-A, Püschel M. 2019. Powerset convolutional neural networks. NIPS: Conference on Neural Information Processing Systems vol. 32, 927–938."},"date_published":"2019-12-01T00:00:00Z","type":"conference","abstract":[{"lang":"eng","text":"We present a novel class of convolutional neural networks (CNNs) for set functions,i.e., data indexed with the powerset of a finite set. The convolutions are derivedas linear, shift-equivariant functions for various notions of shifts on set functions.The framework is fundamentally different from graph convolutions based on theLaplacian, as it provides not one but several basic shifts, one for each element inthe ground set. Prototypical experiments with several set function classificationtasks on synthetic datasets and on datasets derived from real-world hypergraphsdemonstrate the potential of our new powerset CNNs."}],"intvolume":" 32","status":"public","title":"Powerset convolutional neural networks","_id":"7542","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","oa_version":"Published Version"},{"date_created":"2020-02-23T23:00:36Z","date_updated":"2023-09-08T11:12:04Z","oa_version":"None","author":[{"last_name":"Cremer","first_name":"Sylvia","orcid":"0000-0002-2193-3868","id":"2F64EC8C-F248-11E8-B48F-1D18A9856A87","full_name":"Cremer, Sylvia"},{"full_name":"Kutzer, Megan","first_name":"Megan","last_name":"Kutzer","id":"29D0B332-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8696-6978"}],"edition":"2","title":"Social immunity","status":"public","publication_status":"published","editor":[{"full_name":"Choe, Jae","last_name":"Choe","first_name":"Jae"}],"department":[{"_id":"SyCr"}],"publisher":"Elsevier","year":"2019","_id":"7513","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","abstract":[{"lang":"eng","text":"Social insects (i.e., ants, termites and the social bees and wasps) protect their colonies from disease using a combination of individual immunity and collectively performed defenses, termed social immunity. The first line of social immune defense is sanitary care, which is performed by colony members to protect their pathogen-exposed nestmates from developing an infection. If sanitary care fails and an infection becomes established, a second line of social immune defense is deployed to stop disease transmission within the colony and to protect the valuable queens, which together with the males are the reproductive individuals of the colony. Insect colonies are separated into these reproductive individuals and the sterile worker force, forming a superorganismal reproductive unit reminiscent of the differentiated germline and soma in a multicellular organism. Ultimately, the social immune response preserves the germline of the superorganism insect colony and increases overall fitness of the colony in case of disease. 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Choe (Ed.), Encyclopedia of Animal Behavior, 2nd ed., Elsevier, 2019, pp. 747–755.","mla":"Cremer, Sylvia, and Megan Kutzer. “Social Immunity.” Encyclopedia of Animal Behavior, edited by Jae Choe, 2nd ed., Elsevier, 2019, pp. 747–55, doi:10.1016/B978-0-12-809633-8.90721-0.","chicago":"Cremer, Sylvia, and Megan Kutzer. “Social Immunity.” In Encyclopedia of Animal Behavior, edited by Jae Choe, 2nd ed., 747–55. Elsevier, 2019. https://doi.org/10.1016/B978-0-12-809633-8.90721-0."},"external_id":{"isi":["000248989500026"]},"day":"06","month":"02","article_processing_charge":"No","publication_identifier":{"eisbn":["9780128132524"],"isbn":["9780128132517"]},"scopus_import":"1"},{"external_id":{"isi":["000563497600059"]},"citation":{"ama":"Laccone F, Malomo L, Perez Rodriguez J, et al. FlexMaps Pavilion: A twisted arc made of mesostructured flat flexible panels. 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Laccone et al., “FlexMaps Pavilion: A twisted arc made of mesostructured flat flexible panels,” in IASS Symposium 2019 - 60th Anniversary Symposium of the International Association for Shell and Spatial Structures; Structural Membranes 2019 - 9th International Conference on Textile Composites and Inflatable Structures, FORM and FORCE, Barcelona, Spain, 2019, pp. 509–515.","apa":"Laccone, F., Malomo, L., Perez Rodriguez, J., Pietroni, N., Ponchio, F., Bickel, B., & Cignoni, P. (2019). FlexMaps Pavilion: A twisted arc made of mesostructured flat flexible panels. In IASS Symposium 2019 - 60th Anniversary Symposium of the International Association for Shell and Spatial Structures; Structural Membranes 2019 - 9th International Conference on Textile Composites and Inflatable Structures, FORM and FORCE (pp. 509–515). Barcelona, Spain: International Center for Numerical Methods in Engineering.","mla":"Laccone, Francesco, et al. “FlexMaps Pavilion: A Twisted Arc Made of Mesostructured Flat Flexible Panels.” IASS Symposium 2019 - 60th Anniversary Symposium of the International Association for Shell and Spatial Structures; Structural Membranes 2019 - 9th International Conference on Textile Composites and Inflatable Structures, FORM and FORCE, International Center for Numerical Methods in Engineering, 2019, pp. 509–15.","short":"F. Laccone, L. Malomo, J. Perez Rodriguez, N. Pietroni, F. Ponchio, B. Bickel, P. Cignoni, in:, IASS Symposium 2019 - 60th Anniversary Symposium of the International Association for Shell and Spatial Structures; Structural Membranes 2019 - 9th International Conference on Textile Composites and Inflatable Structures, FORM and FORCE, International Center for Numerical Methods in Engineering, 2019, pp. 509–515.","chicago":"Laccone, Francesco, Luigi Malomo, Jesus Perez Rodriguez, Nico Pietroni, Federico Ponchio, Bernd Bickel, and Paolo Cignoni. “FlexMaps Pavilion: A Twisted Arc Made of Mesostructured Flat Flexible Panels.” In IASS Symposium 2019 - 60th Anniversary Symposium of the International Association for Shell and Spatial Structures; Structural Membranes 2019 - 9th International Conference on Textile Composites and Inflatable Structures, FORM and FORCE, 509–15. International Center for Numerical Methods in Engineering, 2019."},"publication":"IASS Symposium 2019 - 60th Anniversary Symposium of the International Association for Shell and Spatial Structures; Structural Membranes 2019 - 9th International Conference on Textile Composites and Inflatable Structures, FORM and FORCE","page":"509-515","isi":1,"quality_controlled":"1","date_published":"2019-10-10T00:00:00Z","conference":{"name":"IASS: International Association for Shell and Spatial Structures","start_date":"2019-10-07","location":"Barcelona, Spain","end_date":"2019-10-10"},"language":[{"iso":"eng"}],"scopus_import":"1","publication_identifier":{"isbn":["9788412110104"],"issn":["2518-6582"]},"article_processing_charge":"No","day":"10","month":"10","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"9261","year":"2019","publisher":"International Center for Numerical Methods in Engineering","department":[{"_id":"BeBi"}],"publication_status":"published","status":"public","title":"FlexMaps Pavilion: A twisted arc made of mesostructured flat flexible panels","author":[{"full_name":"Laccone, Francesco","last_name":"Laccone","first_name":"Francesco"},{"full_name":"Malomo, Luigi","first_name":"Luigi","last_name":"Malomo"},{"id":"2DC83906-F248-11E8-B48F-1D18A9856A87","last_name":"Perez Rodriguez","first_name":"Jesus","full_name":"Perez Rodriguez, Jesus"},{"full_name":"Pietroni, Nico","last_name":"Pietroni","first_name":"Nico"},{"first_name":"Federico","last_name":"Ponchio","full_name":"Ponchio, Federico"},{"full_name":"Bickel, Bernd","first_name":"Bernd","last_name":"Bickel","id":"49876194-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6511-9385"},{"last_name":"Cignoni","first_name":"Paolo","full_name":"Cignoni, Paolo"}],"oa_version":"None","date_updated":"2023-09-08T11:21:54Z","date_created":"2021-03-21T23:01:21Z","type":"conference","abstract":[{"text":"Bending-active structures are able to efficiently produce complex curved shapes starting from flat panels. The desired deformation of the panels derives from the proper selection of their elastic properties. Optimized panels, called FlexMaps, are designed such that, once they are bent and assembled, the resulting static equilibrium configuration matches a desired input 3D shape. The FlexMaps elastic properties are controlled by locally varying spiraling geometric mesostructures, which are optimized in size and shape to match the global curvature (i.e., bending requests) of the target shape. The design pipeline starts from a quad mesh representing the input 3D shape, which defines the edge size and the total amount of spirals: every quad will embed one spiral. Then, an optimization algorithm tunes the geometry of the spirals by using a simplified pre-computed rod model. This rod model is derived from a non-linear regression algorithm which approximates the non-linear behavior of solid FEM spiral models subject to hundreds of load combinations. This innovative pipeline has been applied to the project of a lightweight plywood pavilion named FlexMaps Pavilion, which is a single-layer piecewise twisted arc that fits a bounding box of 3.90x3.96x3.25 meters.","lang":"eng"}]},{"date_created":"2020-04-05T22:00:51Z","date_updated":"2023-09-08T11:18:37Z","author":[{"full_name":"Kolesnikov, Alexander","id":"2D157DB6-F248-11E8-B48F-1D18A9856A87","first_name":"Alexander","last_name":"Kolesnikov"},{"last_name":"Kuznetsova","first_name":"Alina","full_name":"Kuznetsova, Alina"},{"first_name":"Christoph","last_name":"Lampert","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8622-7887","full_name":"Lampert, Christoph"},{"first_name":"Vittorio","last_name":"Ferrari","full_name":"Ferrari, Vittorio"}],"publication_status":"published","department":[{"_id":"ChLa"}],"publisher":"IEEE","year":"2019","ec_funded":1,"article_number":"1749-1753","language":[{"iso":"eng"}],"conference":{"name":"ICCVW: International Conference on Computer Vision Workshop","location":"Seoul, South Korea","start_date":"2019-10-27","end_date":"2019-10-28"},"doi":"10.1109/ICCVW.2019.00217","isi":1,"quality_controlled":"1","project":[{"grant_number":"308036","_id":"2532554C-B435-11E9-9278-68D0E5697425","name":"Lifelong Learning of Visual Scene Understanding","call_identifier":"FP7"}],"external_id":{"arxiv":["1807.02136"],"isi":["000554591601098"]},"oa":1,"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1807.02136"}],"month":"10","publication_identifier":{"isbn":["9781728150239"]},"oa_version":"Preprint","status":"public","title":"Detecting visual relationships using box attention","_id":"7640","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","abstract":[{"text":"We propose a new model for detecting visual relationships, such as \"person riding motorcycle\" or \"bottle on table\". This task is an important step towards comprehensive structured mage understanding, going beyond detecting individual objects. Our main novelty is a Box Attention mechanism that allows to model pairwise interactions between objects using standard object detection pipelines. The resulting model is conceptually clean, expressive and relies on well-justified training and prediction procedures. Moreover, unlike previously proposed approaches, our model does not introduce any additional complex components or hyperparameters on top of those already required by the underlying detection model. We conduct an experimental evaluation on two datasets, V-COCO and Open Images, demonstrating strong quantitative and qualitative results.","lang":"eng"}],"type":"conference","date_published":"2019-10-01T00:00:00Z","publication":"Proceedings of the 2019 International Conference on Computer Vision Workshop","citation":{"ama":"Kolesnikov A, Kuznetsova A, Lampert C, Ferrari V. Detecting visual relationships using box attention. In: Proceedings of the 2019 International Conference on Computer Vision Workshop. IEEE; 2019. doi:10.1109/ICCVW.2019.00217","ieee":"A. Kolesnikov, A. Kuznetsova, C. Lampert, and V. Ferrari, “Detecting visual relationships using box attention,” in Proceedings of the 2019 International Conference on Computer Vision Workshop, Seoul, South Korea, 2019.","apa":"Kolesnikov, A., Kuznetsova, A., Lampert, C., & Ferrari, V. (2019). Detecting visual relationships using box attention. In Proceedings of the 2019 International Conference on Computer Vision Workshop. Seoul, South Korea: IEEE. https://doi.org/10.1109/ICCVW.2019.00217","ista":"Kolesnikov A, Kuznetsova A, Lampert C, Ferrari V. 2019. Detecting visual relationships using box attention. Proceedings of the 2019 International Conference on Computer Vision Workshop. ICCVW: International Conference on Computer Vision Workshop, 1749–1753.","short":"A. Kolesnikov, A. Kuznetsova, C. Lampert, V. Ferrari, in:, Proceedings of the 2019 International Conference on Computer Vision Workshop, IEEE, 2019.","mla":"Kolesnikov, Alexander, et al. “Detecting Visual Relationships Using Box Attention.” Proceedings of the 2019 International Conference on Computer Vision Workshop, 1749–1753, IEEE, 2019, doi:10.1109/ICCVW.2019.00217.","chicago":"Kolesnikov, Alexander, Alina Kuznetsova, Christoph Lampert, and Vittorio Ferrari. “Detecting Visual Relationships Using Box Attention.” In Proceedings of the 2019 International Conference on Computer Vision Workshop. IEEE, 2019. https://doi.org/10.1109/ICCVW.2019.00217."},"day":"01","article_processing_charge":"No","scopus_import":"1"},{"quality_controlled":"1","isi":1,"publication":"Proceedings of the 2019 International Conference on Computer Vision Workshop","external_id":{"isi":["000554591600090"]},"citation":{"ama":"Rannen-Triki A, Berman M, Kolmogorov V, Blaschko MB. Function norms for neural networks. In: Proceedings of the 2019 International Conference on Computer Vision Workshop. IEEE; 2019. doi:10.1109/ICCVW.2019.00097","apa":"Rannen-Triki, A., Berman, M., Kolmogorov, V., & Blaschko, M. B. (2019). Function norms for neural networks. In Proceedings of the 2019 International Conference on Computer Vision Workshop. Seoul, South Korea: IEEE. https://doi.org/10.1109/ICCVW.2019.00097","ieee":"A. Rannen-Triki, M. Berman, V. Kolmogorov, and M. B. Blaschko, “Function norms for neural networks,” in Proceedings of the 2019 International Conference on Computer Vision Workshop, Seoul, South Korea, 2019.","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.","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.” Proceedings of the 2019 International Conference on Computer Vision Workshop, 748–752, IEEE, 2019, doi:10.1109/ICCVW.2019.00097.","chicago":"Rannen-Triki, Amal, Maxim Berman, Vladimir Kolmogorov, and Matthew B. Blaschko. “Function Norms for Neural Networks.” In Proceedings of the 2019 International Conference on Computer Vision Workshop. IEEE, 2019. https://doi.org/10.1109/ICCVW.2019.00097."},"language":[{"iso":"eng"}],"conference":{"location":"Seoul, South Korea","start_date":"2019-10-27","end_date":"2019-10-28","name":"ICCVW: International Conference on Computer Vision Workshop"},"doi":"10.1109/ICCVW.2019.00097","date_published":"2019-10-01T00:00:00Z","scopus_import":"1","day":"01","month":"10","article_processing_charge":"No","publication_identifier":{"isbn":["9781728150239"]},"title":"Function norms for neural networks","publication_status":"published","status":"public","department":[{"_id":"VlKo"}],"publisher":"IEEE","_id":"7639","year":"2019","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","date_updated":"2023-09-08T11:19:12Z","date_created":"2020-04-05T22:00:50Z","oa_version":"None","author":[{"last_name":"Rannen-Triki","first_name":"Amal","full_name":"Rannen-Triki, Amal"},{"last_name":"Berman","first_name":"Maxim","full_name":"Berman, Maxim"},{"full_name":"Kolmogorov, Vladimir","first_name":"Vladimir","last_name":"Kolmogorov","id":"3D50B0BA-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Blaschko","first_name":"Matthew B.","full_name":"Blaschko, Matthew B."}],"article_number":"748-752","type":"conference","abstract":[{"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.","lang":"eng"}]}]