--- _id: '6354' abstract: - lang: eng text: Blood platelets are critical for hemostasis and thrombosis, but also play diverse roles during immune responses. We have recently reported that platelets migrate at sites of infection in vitro and in vivo. Importantly, platelets use their ability to migrate to collect and bundle fibrin (ogen)-bound bacteria accomplishing efficient intravascular bacterial trapping. Here, we describe a method that allows analyzing platelet migration in vitro, focusing on their ability to collect bacteria and trap bacteria under flow. acknowledgement: ' FöFoLe project 947 (F.G.), the Friedrich-Baur-Stiftung project 41/16 (F.G.)' article_number: e3018 author: - first_name: Shuxia full_name: Fan, Shuxia last_name: Fan - first_name: Michael full_name: Lorenz, Michael last_name: Lorenz - first_name: Steffen full_name: Massberg, Steffen last_name: Massberg - first_name: Florian R full_name: Gärtner, Florian R id: 397A88EE-F248-11E8-B48F-1D18A9856A87 last_name: Gärtner orcid: 0000-0001-6120-3723 citation: ama: Fan S, Lorenz M, Massberg S, Gärtner FR. Platelet migration and bacterial trapping assay under flow. Bio-Protocol. 2018;8(18). doi:10.21769/bioprotoc.3018 apa: Fan, S., Lorenz, M., Massberg, S., & Gärtner, F. R. (2018). Platelet migration and bacterial trapping assay under flow. Bio-Protocol. Bio-Protocol. https://doi.org/10.21769/bioprotoc.3018 chicago: Fan, Shuxia, Michael Lorenz, Steffen Massberg, and Florian R Gärtner. “Platelet Migration and Bacterial Trapping Assay under Flow.” Bio-Protocol. Bio-Protocol, 2018. https://doi.org/10.21769/bioprotoc.3018. ieee: S. Fan, M. Lorenz, S. Massberg, and F. R. Gärtner, “Platelet migration and bacterial trapping assay under flow,” Bio-Protocol, vol. 8, no. 18. Bio-Protocol, 2018. ista: Fan S, Lorenz M, Massberg S, Gärtner FR. 2018. Platelet migration and bacterial trapping assay under flow. Bio-Protocol. 8(18), e3018. mla: Fan, Shuxia, et al. “Platelet Migration and Bacterial Trapping Assay under Flow.” Bio-Protocol, vol. 8, no. 18, e3018, Bio-Protocol, 2018, doi:10.21769/bioprotoc.3018. short: S. Fan, M. Lorenz, S. Massberg, F.R. Gärtner, Bio-Protocol 8 (2018). date_created: 2019-04-29T09:40:33Z date_published: 2018-09-20T00:00:00Z date_updated: 2021-01-12T08:07:12Z day: '20' ddc: - '570' department: - _id: MiSi doi: 10.21769/bioprotoc.3018 ec_funded: 1 file: - access_level: open_access checksum: d4588377e789da7f360b553ae02c5119 content_type: application/pdf creator: dernst date_created: 2019-04-30T08:04:33Z date_updated: 2020-07-14T12:47:28Z file_id: '6360' file_name: 2018_BioProtocol_Fan.pdf file_size: 2928337 relation: main_file file_date_updated: 2020-07-14T12:47:28Z has_accepted_license: '1' intvolume: ' 8' issue: '18' keyword: - Platelets - Cell migration - Bacteria - Shear flow - Fibrinogen - E. coli language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '09' oa: 1 oa_version: Published Version project: - _id: 260AA4E2-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '747687' name: Mechanical Adaptation of Lamellipodial Actin Networks in Migrating Cells publication: Bio-Protocol publication_identifier: issn: - 2331-8325 publication_status: published publisher: Bio-Protocol quality_controlled: '1' status: public title: Platelet migration and bacterial trapping assay under flow tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 8 year: '2018' ... --- _id: '6459' author: - first_name: Barbara full_name: Petritsch, Barbara id: 406048EC-F248-11E8-B48F-1D18A9856A87 last_name: Petritsch orcid: 0000-0003-2724-4614 citation: ama: Petritsch B. Open Access at IST Austria 2009-2017. IST Austria; 2018. doi:10.5281/zenodo.1410279 apa: 'Petritsch, B. (2018). Open Access at IST Austria 2009-2017. Presented at the Open-Access-Tage, Graz, Austria: IST Austria. https://doi.org/10.5281/zenodo.1410279' chicago: Petritsch, Barbara. Open Access at IST Austria 2009-2017. IST Austria, 2018. https://doi.org/10.5281/zenodo.1410279. ieee: B. Petritsch, Open Access at IST Austria 2009-2017. IST Austria, 2018. ista: Petritsch B. 2018. Open Access at IST Austria 2009-2017, IST Austria,p. mla: Petritsch, Barbara. Open Access at IST Austria 2009-2017. IST Austria, 2018, doi:10.5281/zenodo.1410279. short: B. Petritsch, Open Access at IST Austria 2009-2017, IST Austria, 2018. conference: end_date: 2018-09-26 location: Graz, Austria name: Open-Access-Tage start_date: 2018-09-24 date_created: 2019-05-16T07:27:14Z date_published: 2018-09-24T00:00:00Z date_updated: 2020-07-14T23:06:21Z day: '24' ddc: - '020' department: - _id: E-Lib doi: 10.5281/zenodo.1410279 file: - access_level: open_access checksum: 9063ab4d10ea93353c3a03bbf53fbcf1 content_type: application/pdf creator: dernst date_created: 2019-05-16T07:26:25Z date_updated: 2020-07-14T12:47:30Z file_id: '6460' file_name: Poster_Beitrag_125_Petritsch.pdf file_size: 1967778 relation: main_file file_date_updated: 2020-07-14T12:47:30Z has_accepted_license: '1' keyword: - Open Access - Publication Analysis language: - iso: eng month: '09' oa: 1 oa_version: Published Version publication_status: published publisher: IST Austria status: public title: Open Access at IST Austria 2009-2017 tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference_poster user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2018' ... --- _id: '690' abstract: - lang: eng text: We consider spectral properties and the edge universality of sparse random matrices, the class of random matrices that includes the adjacency matrices of the Erdős–Rényi graph model G(N, p). We prove a local law for the eigenvalue density up to the spectral edges. Under a suitable condition on the sparsity, we also prove that the rescaled extremal eigenvalues exhibit GOE Tracy–Widom fluctuations if a deterministic shift of the spectral edge due to the sparsity is included. For the adjacency matrix of the Erdős–Rényi graph this establishes the Tracy–Widom fluctuations of the second largest eigenvalue when p is much larger than N−2/3 with a deterministic shift of order (Np)−1. article_number: 543-616 author: - first_name: Jii full_name: Lee, Jii last_name: Lee - first_name: Kevin full_name: Schnelli, Kevin id: 434AD0AE-F248-11E8-B48F-1D18A9856A87 last_name: Schnelli orcid: 0000-0003-0954-3231 citation: ama: Lee J, Schnelli K. Local law and Tracy–Widom limit for sparse random matrices. Probability Theory and Related Fields. 2018;171(1-2). doi:10.1007/s00440-017-0787-8 apa: Lee, J., & Schnelli, K. (2018). Local law and Tracy–Widom limit for sparse random matrices. Probability Theory and Related Fields. Springer. https://doi.org/10.1007/s00440-017-0787-8 chicago: Lee, Jii, and Kevin Schnelli. “Local Law and Tracy–Widom Limit for Sparse Random Matrices.” Probability Theory and Related Fields. Springer, 2018. https://doi.org/10.1007/s00440-017-0787-8. ieee: J. Lee and K. Schnelli, “Local law and Tracy–Widom limit for sparse random matrices,” Probability Theory and Related Fields, vol. 171, no. 1–2. Springer, 2018. ista: Lee J, Schnelli K. 2018. Local law and Tracy–Widom limit for sparse random matrices. Probability Theory and Related Fields. 171(1–2), 543–616. mla: Lee, Jii, and Kevin Schnelli. “Local Law and Tracy–Widom Limit for Sparse Random Matrices.” Probability Theory and Related Fields, vol. 171, no. 1–2, 543–616, Springer, 2018, doi:10.1007/s00440-017-0787-8. short: J. Lee, K. Schnelli, Probability Theory and Related Fields 171 (2018). date_created: 2018-12-11T11:47:56Z date_published: 2018-06-14T00:00:00Z date_updated: 2021-01-12T08:09:33Z day: '14' department: - _id: LaEr doi: 10.1007/s00440-017-0787-8 ec_funded: 1 external_id: arxiv: - '1605.08767' intvolume: ' 171' issue: 1-2 language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1605.08767 month: '06' oa: 1 oa_version: Preprint project: - _id: 258DCDE6-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '338804' name: Random matrices, universality and disordered quantum systems publication: Probability Theory and Related Fields publication_status: published publisher: Springer publist_id: '7017' quality_controlled: '1' scopus_import: 1 status: public title: Local law and Tracy–Widom limit for sparse random matrices type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 171 year: '2018' ... --- _id: '703' abstract: - lang: eng text: We consider the NP-hard problem of MAP-inference for undirected discrete graphical models. We propose a polynomial time and practically efficient algorithm for finding a part of its optimal solution. Specifically, our algorithm marks some labels of the considered graphical model either as (i) optimal, meaning that they belong to all optimal solutions of the inference problem; (ii) non-optimal if they provably do not belong to any solution. With access to an exact solver of a linear programming relaxation to the MAP-inference problem, our algorithm marks the maximal possible (in a specified sense) number of labels. We also present a version of the algorithm, which has access to a suboptimal dual solver only and still can ensure the (non-)optimality for the marked labels, although the overall number of the marked labels may decrease. We propose an efficient implementation, which runs in time comparable to a single run of a suboptimal dual solver. Our method is well-scalable and shows state-of-the-art results on computational benchmarks from machine learning and computer vision. author: - first_name: Alexander full_name: Shekhovtsov, Alexander last_name: Shekhovtsov - first_name: Paul full_name: Swoboda, Paul id: 446560C6-F248-11E8-B48F-1D18A9856A87 last_name: Swoboda - first_name: Bogdan full_name: Savchynskyy, Bogdan last_name: Savchynskyy citation: ama: Shekhovtsov A, Swoboda P, Savchynskyy B. Maximum persistency via iterative relaxed inference with graphical models. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2018;40(7):1668-1682. doi:10.1109/TPAMI.2017.2730884 apa: Shekhovtsov, A., Swoboda, P., & Savchynskyy, B. (2018). Maximum persistency via iterative relaxed inference with graphical models. IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE. https://doi.org/10.1109/TPAMI.2017.2730884 chicago: Shekhovtsov, Alexander, Paul Swoboda, and Bogdan Savchynskyy. “Maximum Persistency via Iterative Relaxed Inference with Graphical Models.” IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE, 2018. https://doi.org/10.1109/TPAMI.2017.2730884. ieee: A. Shekhovtsov, P. Swoboda, and B. Savchynskyy, “Maximum persistency via iterative relaxed inference with graphical models,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 7. IEEE, pp. 1668–1682, 2018. ista: Shekhovtsov A, Swoboda P, Savchynskyy B. 2018. Maximum persistency via iterative relaxed inference with graphical models. IEEE Transactions on Pattern Analysis and Machine Intelligence. 40(7), 1668–1682. mla: Shekhovtsov, Alexander, et al. “Maximum Persistency via Iterative Relaxed Inference with Graphical Models.” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 7, IEEE, 2018, pp. 1668–82, doi:10.1109/TPAMI.2017.2730884. short: A. Shekhovtsov, P. Swoboda, B. Savchynskyy, IEEE Transactions on Pattern Analysis and Machine Intelligence 40 (2018) 1668–1682. date_created: 2018-12-11T11:48:01Z date_published: 2018-07-01T00:00:00Z date_updated: 2021-01-12T08:11:32Z day: '01' department: - _id: VlKo doi: 10.1109/TPAMI.2017.2730884 external_id: arxiv: - '1508.07902' intvolume: ' 40' issue: '7' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1508.07902 month: '07' oa: 1 oa_version: Preprint page: 1668-1682 publication: IEEE Transactions on Pattern Analysis and Machine Intelligence publication_identifier: issn: - '01628828' publication_status: published publisher: IEEE publist_id: '6992' quality_controlled: '1' scopus_import: 1 status: public title: Maximum persistency via iterative relaxed inference with graphical models type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 40 year: '2018' ... --- _id: '7116' abstract: - lang: eng text: 'Training deep learning models has received tremendous research interest recently. In particular, there has been intensive research on reducing the communication cost of training when using multiple computational devices, through reducing the precision of the underlying data representation. Naturally, such methods induce system trade-offs—lowering communication precision could de-crease communication overheads and improve scalability; but, on the other hand, it can also reduce the accuracy of training. In this paper, we study this trade-off space, and ask:Can low-precision communication consistently improve the end-to-end performance of training modern neural networks, with no accuracy loss?From the performance point of view, the answer to this question may appear deceptively easy: compressing communication through low precision should help when the ratio between communication and computation is high. However, this answer is less straightforward when we try to generalize this principle across various neural network architectures (e.g., AlexNet vs. ResNet),number of GPUs (e.g., 2 vs. 8 GPUs), machine configurations(e.g., EC2 instances vs. NVIDIA DGX-1), communication primitives (e.g., MPI vs. NCCL), and even different GPU architectures(e.g., Kepler vs. Pascal). Currently, it is not clear how a realistic realization of all these factors maps to the speed up provided by low-precision communication. In this paper, we conduct an empirical study to answer this question and report the insights.' article_processing_charge: No author: - first_name: Demjan full_name: Grubic, Demjan last_name: Grubic - first_name: Leo full_name: Tam, Leo last_name: Tam - first_name: Dan-Adrian full_name: Alistarh, Dan-Adrian id: 4A899BFC-F248-11E8-B48F-1D18A9856A87 last_name: Alistarh orcid: 0000-0003-3650-940X - first_name: Ce full_name: Zhang, Ce last_name: Zhang citation: ama: 'Grubic D, Tam L, Alistarh D-A, Zhang C. Synchronous multi-GPU training for deep learning with low-precision communications: An empirical study. In: Proceedings of the 21st International Conference on Extending Database Technology. OpenProceedings; 2018:145-156. doi:10.5441/002/EDBT.2018.14' apa: 'Grubic, D., Tam, L., Alistarh, D.-A., & Zhang, C. (2018). Synchronous multi-GPU training for deep learning with low-precision communications: An empirical study. In Proceedings of the 21st International Conference on Extending Database Technology (pp. 145–156). Vienna, Austria: OpenProceedings. https://doi.org/10.5441/002/EDBT.2018.14' chicago: 'Grubic, Demjan, Leo Tam, Dan-Adrian Alistarh, and Ce Zhang. “Synchronous Multi-GPU Training for Deep Learning with Low-Precision Communications: An Empirical Study.” In Proceedings of the 21st International Conference on Extending Database Technology, 145–56. OpenProceedings, 2018. https://doi.org/10.5441/002/EDBT.2018.14.' ieee: 'D. Grubic, L. Tam, D.-A. Alistarh, and C. Zhang, “Synchronous multi-GPU training for deep learning with low-precision communications: An empirical study,” in Proceedings of the 21st International Conference on Extending Database Technology, Vienna, Austria, 2018, pp. 145–156.' ista: 'Grubic D, Tam L, Alistarh D-A, Zhang C. 2018. Synchronous multi-GPU training for deep learning with low-precision communications: An empirical study. Proceedings of the 21st International Conference on Extending Database Technology. EDBT: Conference on Extending Database Technology, 145–156.' mla: 'Grubic, Demjan, et al. “Synchronous Multi-GPU Training for Deep Learning with Low-Precision Communications: An Empirical Study.” Proceedings of the 21st International Conference on Extending Database Technology, OpenProceedings, 2018, pp. 145–56, doi:10.5441/002/EDBT.2018.14.' short: D. Grubic, L. Tam, D.-A. Alistarh, C. Zhang, in:, Proceedings of the 21st International Conference on Extending Database Technology, OpenProceedings, 2018, pp. 145–156. conference: end_date: 2018-03-29 location: Vienna, Austria name: 'EDBT: Conference on Extending Database Technology' start_date: 2018-03-26 date_created: 2019-11-26T14:19:11Z date_published: 2018-03-26T00:00:00Z date_updated: 2023-02-23T12:59:17Z day: '26' ddc: - '000' department: - _id: DaAl doi: 10.5441/002/EDBT.2018.14 file: - access_level: open_access checksum: ec979b56abc71016d6e6adfdadbb4afe content_type: application/pdf creator: dernst date_created: 2019-11-26T14:23:04Z date_updated: 2020-07-14T12:47:49Z file_id: '7118' file_name: 2018_OpenProceedings_Grubic.pdf file_size: 1603204 relation: main_file file_date_updated: 2020-07-14T12:47:49Z has_accepted_license: '1' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ month: '03' oa: 1 oa_version: Published Version page: 145-156 publication: Proceedings of the 21st International Conference on Extending Database Technology publication_identifier: isbn: - '9783893180783' issn: - 2367-2005 publication_status: published publisher: OpenProceedings quality_controlled: '1' scopus_import: 1 status: public title: 'Synchronous multi-GPU training for deep learning with low-precision communications: An empirical study' tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2018' ... --- _id: '7407' abstract: - lang: eng text: 'Proofs of space (PoS) [Dziembowski et al., CRYPTO''15] are proof systems where a prover can convince a verifier that he "wastes" disk space. PoS were introduced as a more ecological and economical replacement for proofs of work which are currently used to secure blockchains like Bitcoin. In this work we investigate extensions of PoS which allow the prover to embed useful data into the dedicated space, which later can be recovered. Our first contribution is a security proof for the original PoS from CRYPTO''15 in the random oracle model (the original proof only applied to a restricted class of adversaries which can store a subset of the data an honest prover would store). When this PoS is instantiated with recent constructions of maximally depth robust graphs, our proof implies basically optimal security. As a second contribution we show three different extensions of this PoS where useful data can be embedded into the space required by the prover. Our security proof for the PoS extends (non-trivially) to these constructions. We discuss how some of these variants can be used as proofs of catalytic space (PoCS), a notion we put forward in this work, and which basically is a PoS where most of the space required by the prover can be used to backup useful data. Finally we discuss how one of the extensions is a candidate construction for a proof of replication (PoR), a proof system recently suggested in the Filecoin whitepaper. ' alternative_title: - LIPIcs article_processing_charge: No author: - first_name: Krzysztof Z full_name: Pietrzak, Krzysztof Z id: 3E04A7AA-F248-11E8-B48F-1D18A9856A87 last_name: Pietrzak orcid: 0000-0002-9139-1654 citation: ama: 'Pietrzak KZ. Proofs of catalytic space. In: 10th Innovations in Theoretical Computer Science  Conference (ITCS 2019). Vol 124. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2018:59:1-59:25. doi:10.4230/LIPICS.ITCS.2019.59' apa: 'Pietrzak, K. Z. (2018). Proofs of catalytic space. In 10th Innovations in Theoretical Computer Science  Conference (ITCS 2019) (Vol. 124, p. 59:1-59:25). San Diego, CA, United States: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPICS.ITCS.2019.59' chicago: Pietrzak, Krzysztof Z. “Proofs of Catalytic Space.” In 10th Innovations in Theoretical Computer Science  Conference (ITCS 2019), 124:59:1-59:25. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2018. https://doi.org/10.4230/LIPICS.ITCS.2019.59. ieee: K. Z. Pietrzak, “Proofs of catalytic space,” in 10th Innovations in Theoretical Computer Science  Conference (ITCS 2019), San Diego, CA, United States, 2018, vol. 124, p. 59:1-59:25. ista: 'Pietrzak KZ. 2018. Proofs of catalytic space. 10th Innovations in Theoretical Computer Science  Conference (ITCS 2019). ITCS: Innovations in theoretical Computer Science Conference, LIPIcs, vol. 124, 59:1-59:25.' mla: Pietrzak, Krzysztof Z. “Proofs of Catalytic Space.” 10th Innovations in Theoretical Computer Science  Conference (ITCS 2019), vol. 124, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2018, p. 59:1-59:25, doi:10.4230/LIPICS.ITCS.2019.59. short: K.Z. Pietrzak, in:, 10th Innovations in Theoretical Computer Science  Conference (ITCS 2019), Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2018, p. 59:1-59:25. conference: end_date: 2019-01-12 location: San Diego, CA, United States name: 'ITCS: Innovations in theoretical Computer Science Conference' start_date: 2019-01-10 date_created: 2020-01-30T09:16:05Z date_published: 2018-12-31T00:00:00Z date_updated: 2021-01-12T08:13:26Z day: '31' ddc: - '000' department: - _id: KrPi doi: 10.4230/LIPICS.ITCS.2019.59 ec_funded: 1 file: - access_level: open_access checksum: 5cebb7f7849a3beda898f697d755dd96 content_type: application/pdf creator: dernst date_created: 2020-02-04T08:17:52Z date_updated: 2020-07-14T12:47:57Z file_id: '7443' file_name: 2018_LIPIcs_Pietrzak.pdf file_size: 822884 relation: main_file file_date_updated: 2020-07-14T12:47:57Z has_accepted_license: '1' intvolume: ' 124' language: - iso: eng main_file_link: - open_access: '1' url: https://eprint.iacr.org/2018/194 month: '12' oa: 1 oa_version: Published Version page: 59:1-59:25 project: - _id: 258AA5B2-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '682815' name: Teaching Old Crypto New Tricks publication: 10th Innovations in Theoretical Computer Science Conference (ITCS 2019) publication_identifier: isbn: - 978-3-95977-095-8 issn: - 1868-8969 publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' scopus_import: 1 status: public title: Proofs of catalytic space tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 124 year: '2018' ... --- _id: '7812' abstract: - lang: eng text: Deep neural networks (DNNs) continue to make significant advances, solving tasks from image classification to translation or reinforcement learning. One aspect of the field receiving considerable attention is efficiently executing deep models in resource-constrained environments, such as mobile or embedded devices. This paper focuses on this problem, and proposes two new compression methods, which jointly leverage weight quantization and distillation of larger teacher networks into smaller student networks. The first method we propose is called quantized distillation and leverages distillation during the training process, by incorporating distillation loss, expressed with respect to the teacher, into the training of a student network whose weights are quantized to a limited set of levels. The second method, differentiable quantization, optimizes the location of quantization points through stochastic gradient descent, to better fit the behavior of the teacher model. We validate both methods through experiments on convolutional and recurrent architectures. We show that quantized shallow students can reach similar accuracy levels to full-precision teacher models, while providing order of magnitude compression, and inference speedup that is linear in the depth reduction. In sum, our results enable DNNs for resource-constrained environments to leverage architecture and accuracy advances developed on more powerful devices. article_processing_charge: No author: - first_name: Antonio full_name: Polino, Antonio last_name: Polino - first_name: Razvan full_name: Pascanu, Razvan last_name: Pascanu - first_name: Dan-Adrian full_name: Alistarh, Dan-Adrian id: 4A899BFC-F248-11E8-B48F-1D18A9856A87 last_name: Alistarh orcid: 0000-0003-3650-940X citation: ama: 'Polino A, Pascanu R, Alistarh D-A. Model compression via distillation and quantization. In: 6th International Conference on Learning Representations. ; 2018.' apa: Polino, A., Pascanu, R., & Alistarh, D.-A. (2018). Model compression via distillation and quantization. In 6th International Conference on Learning Representations. Vancouver, Canada. chicago: Polino, Antonio, Razvan Pascanu, and Dan-Adrian Alistarh. “Model Compression via Distillation and Quantization.” In 6th International Conference on Learning Representations, 2018. ieee: A. Polino, R. Pascanu, and D.-A. Alistarh, “Model compression via distillation and quantization,” in 6th International Conference on Learning Representations, Vancouver, Canada, 2018. ista: 'Polino A, Pascanu R, Alistarh D-A. 2018. Model compression via distillation and quantization. 6th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.' mla: Polino, Antonio, et al. “Model Compression via Distillation and Quantization.” 6th International Conference on Learning Representations, 2018. short: A. Polino, R. Pascanu, D.-A. Alistarh, in:, 6th International Conference on Learning Representations, 2018. conference: end_date: 2018-05-03 location: Vancouver, Canada name: 'ICLR: International Conference on Learning Representations' start_date: 2018-04-30 date_created: 2020-05-10T22:00:51Z date_published: 2018-05-01T00:00:00Z date_updated: 2023-02-23T13:18:41Z day: '01' ddc: - '000' department: - _id: DaAl external_id: arxiv: - '1802.05668' file: - access_level: open_access checksum: a4336c167978e81891970e4e4517a8c3 content_type: application/pdf creator: dernst date_created: 2020-05-26T13:02:00Z date_updated: 2020-07-14T12:48:03Z file_id: '7894' file_name: 2018_ICLR_Polino.pdf file_size: 308339 relation: main_file file_date_updated: 2020-07-14T12:48:03Z has_accepted_license: '1' language: - iso: eng month: '05' oa: 1 oa_version: Published Version publication: 6th International Conference on Learning Representations publication_status: published quality_controlled: '1' scopus_import: 1 status: public title: Model compression via distillation and quantization type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2018' ... --- _id: '8547' abstract: - lang: eng text: The cerebral cortex contains multiple hierarchically organized areas with distinctive cytoarchitectonical patterns, but the cellular mechanisms underlying the emergence of this diversity remain unclear. Here, we have quantitatively investigated the neuronal output of individual progenitor cells in the ventricular zone of the developing mouse neocortex using a combination of methods that together circumvent the biases and limitations of individual approaches. We found that individual cortical progenitor cells show a high degree of stochasticity and generate pyramidal cell lineages that adopt a wide range of laminar configurations. Mathematical modelling these lineage data suggests that a small number of progenitor cell populations, each generating pyramidal cells following different stochastic developmental programs, suffice to generate the heterogenous complement of pyramidal cell lineages that collectively build the complex cytoarchitecture of the neocortex. acknowledgement: We thank I. Andrew and S.E. Bae for excellent technical assistance, F. Gage for plasmids, and K. Nave (Nex-Cre) for mouse colonies. We thank members of the Marín and Rico laboratories for stimulating discussions and ideas. Our research on this topic is supported by grants from the European Research Council (ERC-2017-AdG 787355 to O.M and ERC2016-CoG 725780 to S.H.) and Wellcome Trust (103714MA) to O.M. L.L. was the recipient of an EMBO long-term postdoctoral fellowship, R.B. received support from FWF Lise-Meitner program (M 2416) and F.K.W. was supported by an EMBO postdoctoral fellowship and is currently a Marie Skłodowska-Curie Fellow from the European Commission under the H2020 Programme. article_processing_charge: No author: - first_name: Alfredo full_name: Llorca, Alfredo last_name: Llorca - first_name: Gabriele full_name: Ciceri, Gabriele last_name: Ciceri - first_name: Robert J full_name: Beattie, Robert J id: 2E26DF60-F248-11E8-B48F-1D18A9856A87 last_name: Beattie orcid: 0000-0002-8483-8753 - first_name: Fong K. full_name: Wong, Fong K. last_name: Wong - first_name: Giovanni full_name: Diana, Giovanni last_name: Diana - first_name: Eleni full_name: Serafeimidou, Eleni last_name: Serafeimidou - first_name: Marian full_name: Fernández-Otero, Marian last_name: Fernández-Otero - first_name: Carmen full_name: Streicher, Carmen id: 36BCB99C-F248-11E8-B48F-1D18A9856A87 last_name: Streicher - first_name: Sebastian J. full_name: Arnold, Sebastian J. last_name: Arnold - first_name: Martin full_name: Meyer, Martin last_name: Meyer - first_name: Simon full_name: Hippenmeyer, Simon id: 37B36620-F248-11E8-B48F-1D18A9856A87 last_name: Hippenmeyer orcid: 0000-0003-2279-1061 - first_name: Miguel full_name: Maravall, Miguel last_name: Maravall - first_name: Oscar full_name: Marín, Oscar last_name: Marín citation: ama: Llorca A, Ciceri G, Beattie RJ, et al. Heterogeneous progenitor cell behaviors underlie the assembly of neocortical cytoarchitecture. bioRxiv. doi:10.1101/494088 apa: Llorca, A., Ciceri, G., Beattie, R. J., Wong, F. K., Diana, G., Serafeimidou, E., … Marín, O. (n.d.). Heterogeneous progenitor cell behaviors underlie the assembly of neocortical cytoarchitecture. bioRxiv. Cold Spring Harbor Laboratory. https://doi.org/10.1101/494088 chicago: Llorca, Alfredo, Gabriele Ciceri, Robert J Beattie, Fong K. Wong, Giovanni Diana, Eleni Serafeimidou, Marian Fernández-Otero, et al. “Heterogeneous Progenitor Cell Behaviors Underlie the Assembly of Neocortical Cytoarchitecture.” BioRxiv. Cold Spring Harbor Laboratory, n.d. https://doi.org/10.1101/494088. ieee: A. Llorca et al., “Heterogeneous progenitor cell behaviors underlie the assembly of neocortical cytoarchitecture,” bioRxiv. Cold Spring Harbor Laboratory. ista: Llorca A, Ciceri G, Beattie RJ, Wong FK, Diana G, Serafeimidou E, Fernández-Otero M, Streicher C, Arnold SJ, Meyer M, Hippenmeyer S, Maravall M, Marín O. Heterogeneous progenitor cell behaviors underlie the assembly of neocortical cytoarchitecture. bioRxiv, 10.1101/494088. mla: Llorca, Alfredo, et al. “Heterogeneous Progenitor Cell Behaviors Underlie the Assembly of Neocortical Cytoarchitecture.” BioRxiv, Cold Spring Harbor Laboratory, doi:10.1101/494088. short: A. Llorca, G. Ciceri, R.J. Beattie, F.K. Wong, G. Diana, E. Serafeimidou, M. Fernández-Otero, C. Streicher, S.J. Arnold, M. Meyer, S. Hippenmeyer, M. Maravall, O. Marín, BioRxiv (n.d.). date_created: 2020-09-21T12:01:50Z date_published: 2018-12-13T00:00:00Z date_updated: 2021-01-12T08:20:00Z day: '13' department: - _id: SiHi doi: 10.1101/494088 ec_funded: 1 language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1101/494088 month: '12' oa: 1 oa_version: Preprint project: - _id: 260018B0-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '725780' name: Principles of Neural Stem Cell Lineage Progression in Cerebral Cortex Development - _id: 264E56E2-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: M02416 name: Molecular Mechanisms Regulating Gliogenesis in the Cerebral Cortex publication: bioRxiv publication_status: submitted publisher: Cold Spring Harbor Laboratory status: public title: Heterogeneous progenitor cell behaviors underlie the assembly of neocortical cytoarchitecture type: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2018' ... --- _id: '86' abstract: - lang: eng text: Responsiveness—the requirement that every request to a system be eventually handled—is one of the fundamental liveness properties of a reactive system. Average response time is a quantitative measure for the responsiveness requirement used commonly in performance evaluation. We show how average response time can be computed on state-transition graphs, on Markov chains, and on game graphs. In all three cases, we give polynomial-time algorithms. acknowledgement: 'This research was supported in part by the Austrian Science Fund (FWF) under grants S11402-N23, S11407-N23 (RiSE/SHiNE) and Z211-N23 (Wittgenstein Award), ERC Start grant (279307: Graph Games), Vienna Science and Technology Fund (WWTF) through project ICT15-003 and by the National Science Centre (NCN), Poland under grant 2014/15/D/ST6/04543.' alternative_title: - LNCS author: - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000−0002−2985−7724 - first_name: Jan full_name: Otop, Jan id: 2FC5DA74-F248-11E8-B48F-1D18A9856A87 last_name: Otop citation: ama: 'Chatterjee K, Henzinger TA, Otop J. Computing average response time. In: Lohstroh M, Derler P, Sirjani M, eds. Principles of Modeling. Vol 10760. Springer; 2018:143-161. doi:10.1007/978-3-319-95246-8_9' apa: Chatterjee, K., Henzinger, T. A., & Otop, J. (2018). Computing average response time. In M. Lohstroh, P. Derler, & M. Sirjani (Eds.), Principles of Modeling (Vol. 10760, pp. 143–161). Springer. https://doi.org/10.1007/978-3-319-95246-8_9 chicago: Chatterjee, Krishnendu, Thomas A Henzinger, and Jan Otop. “Computing Average Response Time.” In Principles of Modeling, edited by Marten Lohstroh, Patricia Derler, and Marjan Sirjani, 10760:143–61. Springer, 2018. https://doi.org/10.1007/978-3-319-95246-8_9. ieee: K. Chatterjee, T. A. Henzinger, and J. Otop, “Computing average response time,” in Principles of Modeling, vol. 10760, M. Lohstroh, P. Derler, and M. Sirjani, Eds. Springer, 2018, pp. 143–161. ista: 'Chatterjee K, Henzinger TA, Otop J. 2018.Computing average response time. In: Principles of Modeling. LNCS, vol. 10760, 143–161.' mla: Chatterjee, Krishnendu, et al. “Computing Average Response Time.” Principles of Modeling, edited by Marten Lohstroh et al., vol. 10760, Springer, 2018, pp. 143–61, doi:10.1007/978-3-319-95246-8_9. short: K. Chatterjee, T.A. Henzinger, J. Otop, in:, M. Lohstroh, P. Derler, M. Sirjani (Eds.), Principles of Modeling, Springer, 2018, pp. 143–161. date_created: 2018-12-11T11:44:33Z date_published: 2018-07-20T00:00:00Z date_updated: 2021-01-12T08:20:14Z day: '20' ddc: - '000' department: - _id: KrCh - _id: ToHe doi: 10.1007/978-3-319-95246-8_9 ec_funded: 1 editor: - first_name: Marten full_name: Lohstroh, Marten last_name: Lohstroh - first_name: Patricia full_name: Derler, Patricia last_name: Derler - first_name: Marjan full_name: Sirjani, Marjan last_name: Sirjani file: - access_level: open_access checksum: 9995c6ce6957333baf616fc4f20be597 content_type: application/pdf creator: dernst date_created: 2019-11-19T08:22:18Z date_updated: 2020-07-14T12:48:14Z file_id: '7053' file_name: 2018_PrinciplesModeling_Chatterjee.pdf file_size: 516307 relation: main_file file_date_updated: 2020-07-14T12:48:14Z has_accepted_license: '1' intvolume: ' 10760' language: - iso: eng month: '07' oa: 1 oa_version: Submitted Version page: 143 - 161 project: - _id: 25832EC2-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S 11407_N23 name: Rigorous Systems Engineering - _id: 25863FF4-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S11407 name: Game Theory - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize - _id: 2581B60A-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '279307' name: 'Quantitative Graph Games: Theory and Applications' - _id: 25892FC0-B435-11E9-9278-68D0E5697425 grant_number: ICT15-003 name: Efficient Algorithms for Computer Aided Verification publication: Principles of Modeling publication_status: published publisher: Springer publist_id: '7968' quality_controlled: '1' scopus_import: 1 status: public title: Computing average response time type: book_chapter user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 10760 year: '2018' ... --- _id: '9229' alternative_title: - Molecular and cellular neuroscience article_processing_charge: No article_type: letter_note author: - first_name: Johann G full_name: Danzl, Johann G id: 42EFD3B6-F248-11E8-B48F-1D18A9856A87 last_name: Danzl orcid: 0000-0001-8559-3973 citation: ama: Danzl JG. Diffraction-unlimited optical imaging for synaptic physiology. Opera Medica et Physiologica. 2018;4(S1):11. doi:10.20388/omp2018.00s1.001 apa: Danzl, J. G. (2018). Diffraction-unlimited optical imaging for synaptic physiology. Opera Medica et Physiologica. Lobachevsky State University of Nizhny Novgorod. https://doi.org/10.20388/omp2018.00s1.001 chicago: Danzl, Johann G. “Diffraction-Unlimited Optical Imaging for Synaptic Physiology.” Opera Medica et Physiologica. Lobachevsky State University of Nizhny Novgorod, 2018. https://doi.org/10.20388/omp2018.00s1.001. ieee: J. G. Danzl, “Diffraction-unlimited optical imaging for synaptic physiology,” Opera Medica et Physiologica, vol. 4, no. S1. Lobachevsky State University of Nizhny Novgorod, p. 11, 2018. ista: Danzl JG. 2018. Diffraction-unlimited optical imaging for synaptic physiology. Opera Medica et Physiologica. 4(S1), 11. mla: Danzl, Johann G. “Diffraction-Unlimited Optical Imaging for Synaptic Physiology.” Opera Medica et Physiologica, vol. 4, no. S1, Lobachevsky State University of Nizhny Novgorod, 2018, p. 11, doi:10.20388/omp2018.00s1.001. short: J.G. Danzl, Opera Medica et Physiologica 4 (2018) 11. date_created: 2021-03-07T23:01:25Z date_published: 2018-06-30T00:00:00Z date_updated: 2021-12-03T07:31:05Z day: '30' department: - _id: JoDa doi: 10.20388/omp2018.00s1.001 intvolume: ' 4' issue: S1 language: - iso: eng main_file_link: - open_access: '1' url: http://operamedphys.org/content/molecular-and-cellular-neuroscience month: '06' oa: 1 oa_version: Published Version page: '11' publication: Opera Medica et Physiologica publication_identifier: eissn: - 2500-2295 issn: - 2500-2287 publication_status: published publisher: Lobachevsky State University of Nizhny Novgorod quality_controlled: '1' scopus_import: '1' status: public title: Diffraction-unlimited optical imaging for synaptic physiology type: journal_article user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 volume: 4 year: '2018' ...