[{"publication_status":"published","publication_identifier":{"isbn":["978-3-95977-095-8"],"issn":["1868-8969"]},"language":[{"iso":"eng"}],"file":[{"creator":"dernst","date_updated":"2020-07-14T12:47:57Z","file_size":822884,"date_created":"2020-02-04T08:17:52Z","file_name":"2018_LIPIcs_Pietrzak.pdf","access_level":"open_access","relation":"main_file","content_type":"application/pdf","checksum":"5cebb7f7849a3beda898f697d755dd96","file_id":"7443"}],"ec_funded":1,"license":"https://creativecommons.org/licenses/by/4.0/","volume":124,"abstract":[{"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. ","lang":"eng"}],"oa_version":"Published Version","main_file_link":[{"url":"https://eprint.iacr.org/2018/194","open_access":"1"}],"scopus_import":1,"alternative_title":["LIPIcs"],"intvolume":" 124","month":"12","date_updated":"2021-01-12T08:13:26Z","ddc":["000"],"file_date_updated":"2020-07-14T12:47:57Z","department":[{"_id":"KrPi"}],"_id":"7407","conference":{"end_date":"2019-01-12","location":"San Diego, CA, United States","start_date":"2019-01-10","name":"ITCS: Innovations in theoretical Computer Science Conference"},"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"type":"conference","status":"public","year":"2018","has_accepted_license":"1","publication":"10th Innovations in Theoretical Computer Science Conference (ITCS 2019)","day":"31","page":"59:1-59:25","date_created":"2020-01-30T09:16:05Z","date_published":"2018-12-31T00:00:00Z","doi":"10.4230/LIPICS.ITCS.2019.59","oa":1,"publisher":"Schloss Dagstuhl - Leibniz-Zentrum für Informatik","quality_controlled":"1","citation":{"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.","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.","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.","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.","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","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."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","author":[{"orcid":"0000-0002-9139-1654","full_name":"Pietrzak, Krzysztof Z","last_name":"Pietrzak","first_name":"Krzysztof Z","id":"3E04A7AA-F248-11E8-B48F-1D18A9856A87"}],"title":"Proofs of catalytic space","project":[{"grant_number":"682815","name":"Teaching Old Crypto New Tricks","_id":"258AA5B2-B435-11E9-9278-68D0E5697425","call_identifier":"H2020"}]},{"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."}],"oa_version":"Published Version","scopus_import":1,"quality_controlled":"1","oa":1,"month":"05","has_accepted_license":"1","publication_status":"published","year":"2018","day":"01","file":[{"content_type":"application/pdf","access_level":"open_access","relation":"main_file","checksum":"a4336c167978e81891970e4e4517a8c3","file_id":"7894","date_updated":"2020-07-14T12:48:03Z","file_size":308339,"creator":"dernst","date_created":"2020-05-26T13:02:00Z","file_name":"2018_ICLR_Polino.pdf"}],"publication":"6th International Conference on Learning Representations","language":[{"iso":"eng"}],"date_published":"2018-05-01T00:00:00Z","date_created":"2020-05-10T22:00:51Z","_id":"7812","type":"conference","conference":{"location":"Vancouver, Canada","end_date":"2018-05-03","start_date":"2018-04-30","name":"ICLR: International Conference on Learning Representations"},"status":"public","citation":{"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.","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.","short":"A. Polino, R. Pascanu, D.-A. Alistarh, 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.","ama":"Polino A, Pascanu R, Alistarh D-A. Model compression via distillation and quantization. In: 6th International Conference on Learning Representations. ; 2018.","mla":"Polino, Antonio, et al. “Model Compression via Distillation and Quantization.” 6th International Conference on Learning Representations, 2018."},"date_updated":"2023-02-23T13:18:41Z","ddc":["000"],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"full_name":"Polino, Antonio","last_name":"Polino","first_name":"Antonio"},{"first_name":"Razvan","full_name":"Pascanu, Razvan","last_name":"Pascanu"},{"last_name":"Alistarh","orcid":"0000-0003-3650-940X","full_name":"Alistarh, Dan-Adrian","first_name":"Dan-Adrian","id":"4A899BFC-F248-11E8-B48F-1D18A9856A87"}],"article_processing_charge":"No","external_id":{"arxiv":["1802.05668"]},"department":[{"_id":"DaAl"}],"file_date_updated":"2020-07-14T12:48:03Z","title":"Model compression via distillation and quantization"},{"date_updated":"2021-01-12T08:20:00Z","citation":{"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.","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.","ieee":"A. Llorca et al., “Heterogeneous progenitor cell behaviors underlie the assembly of neocortical cytoarchitecture,” bioRxiv. Cold Spring Harbor Laboratory.","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.).","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","ama":"Llorca A, Ciceri G, Beattie RJ, et al. Heterogeneous progenitor cell behaviors underlie the assembly of neocortical cytoarchitecture. bioRxiv. doi:10.1101/494088"},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","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"},{"id":"2E26DF60-F248-11E8-B48F-1D18A9856A87","first_name":"Robert J","orcid":"0000-0002-8483-8753","full_name":"Beattie, Robert J","last_name":"Beattie"},{"first_name":"Fong K.","full_name":"Wong, Fong K.","last_name":"Wong"},{"first_name":"Giovanni","last_name":"Diana","full_name":"Diana, Giovanni"},{"last_name":"Serafeimidou","full_name":"Serafeimidou, Eleni","first_name":"Eleni"},{"first_name":"Marian","last_name":"Fernández-Otero","full_name":"Fernández-Otero, Marian"},{"last_name":"Streicher","full_name":"Streicher, Carmen","first_name":"Carmen","id":"36BCB99C-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Arnold","full_name":"Arnold, Sebastian J.","first_name":"Sebastian J."},{"first_name":"Martin","full_name":"Meyer, Martin","last_name":"Meyer"},{"last_name":"Hippenmeyer","orcid":"0000-0003-2279-1061","full_name":"Hippenmeyer, Simon","first_name":"Simon","id":"37B36620-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Maravall, Miguel","last_name":"Maravall","first_name":"Miguel"},{"last_name":"Marín","full_name":"Marín, Oscar","first_name":"Oscar"}],"title":"Heterogeneous progenitor cell behaviors underlie the assembly of neocortical cytoarchitecture","department":[{"_id":"SiHi"}],"_id":"8547","type":"preprint","status":"public","project":[{"call_identifier":"H2020","_id":"260018B0-B435-11E9-9278-68D0E5697425","name":"Principles of Neural Stem Cell Lineage Progression in Cerebral Cortex Development","grant_number":"725780"},{"call_identifier":"FWF","_id":"264E56E2-B435-11E9-9278-68D0E5697425","name":"Molecular Mechanisms Regulating Gliogenesis in the Cerebral Cortex","grant_number":"M02416"}],"year":"2018","publication_status":"submitted","publication":"bioRxiv","language":[{"iso":"eng"}],"day":"13","ec_funded":1,"date_created":"2020-09-21T12:01:50Z","doi":"10.1101/494088","date_published":"2018-12-13T00:00:00Z","abstract":[{"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.","lang":"eng"}],"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.","oa_version":"Preprint","main_file_link":[{"url":"https://doi.org/10.1101/494088","open_access":"1"}],"oa":1,"publisher":"Cold Spring Harbor Laboratory","month":"12"},{"editor":[{"first_name":"Marten","full_name":"Lohstroh, Marten","last_name":"Lohstroh"},{"first_name":"Patricia","last_name":"Derler","full_name":"Derler, Patricia"},{"full_name":"Sirjani, Marjan","last_name":"Sirjani","first_name":"Marjan"}],"title":"Computing average response time","author":[{"last_name":"Chatterjee","orcid":"0000-0002-4561-241X","full_name":"Chatterjee, Krishnendu","first_name":"Krishnendu","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000−0002−2985−7724","full_name":"Henzinger, Thomas A","last_name":"Henzinger","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","first_name":"Thomas A"},{"full_name":"Otop, Jan","last_name":"Otop","first_name":"Jan","id":"2FC5DA74-F248-11E8-B48F-1D18A9856A87"}],"publist_id":"7968","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"ista":"Chatterjee K, Henzinger TA, Otop J. 2018.Computing average response time. In: Principles of Modeling. LNCS, vol. 10760, 143–161.","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.","short":"K. Chatterjee, T.A. Henzinger, J. Otop, in:, M. Lohstroh, P. Derler, M. Sirjani (Eds.), Principles of Modeling, Springer, 2018, pp. 143–161.","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.","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","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","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."},"project":[{"grant_number":"S 11407_N23","name":"Rigorous Systems Engineering","call_identifier":"FWF","_id":"25832EC2-B435-11E9-9278-68D0E5697425"},{"grant_number":"S11407","name":"Game Theory","_id":"25863FF4-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"},{"_id":"25F42A32-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"The Wittgenstein Prize","grant_number":"Z211"},{"call_identifier":"FP7","_id":"2581B60A-B435-11E9-9278-68D0E5697425","name":"Quantitative Graph Games: Theory and Applications","grant_number":"279307"},{"_id":"25892FC0-B435-11E9-9278-68D0E5697425","name":"Efficient Algorithms for Computer Aided Verification","grant_number":"ICT15-003"}],"date_published":"2018-07-20T00:00:00Z","doi":"10.1007/978-3-319-95246-8_9","date_created":"2018-12-11T11:44:33Z","page":"143 - 161","day":"20","publication":"Principles of Modeling","has_accepted_license":"1","year":"2018","quality_controlled":"1","publisher":"Springer","oa":1,"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.","file_date_updated":"2020-07-14T12:48:14Z","department":[{"_id":"KrCh"},{"_id":"ToHe"}],"ddc":["000"],"date_updated":"2021-01-12T08:20:14Z","status":"public","type":"book_chapter","_id":"86","volume":10760,"ec_funded":1,"file":[{"date_updated":"2020-07-14T12:48:14Z","file_size":516307,"creator":"dernst","date_created":"2019-11-19T08:22:18Z","file_name":"2018_PrinciplesModeling_Chatterjee.pdf","content_type":"application/pdf","access_level":"open_access","relation":"main_file","file_id":"7053","checksum":"9995c6ce6957333baf616fc4f20be597"}],"language":[{"iso":"eng"}],"publication_status":"published","month":"07","intvolume":" 10760","alternative_title":["LNCS"],"scopus_import":1,"oa_version":"Submitted Version","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."}]},{"date_updated":"2021-12-03T07:31:05Z","department":[{"_id":"JoDa"}],"_id":"9229","type":"journal_article","article_type":"letter_note","status":"public","publication_identifier":{"eissn":["2500-2295"],"issn":["2500-2287"]},"publication_status":"published","language":[{"iso":"eng"}],"issue":"S1","volume":4,"oa_version":"Published Version","alternative_title":["Molecular and cellular neuroscience"],"scopus_import":"1","main_file_link":[{"url":"http://operamedphys.org/content/molecular-and-cellular-neuroscience","open_access":"1"}],"month":"06","intvolume":" 4","citation":{"ista":"Danzl JG. 2018. Diffraction-unlimited optical imaging for synaptic physiology. Opera Medica et Physiologica. 4(S1), 11.","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.","short":"J.G. Danzl, Opera Medica et Physiologica 4 (2018) 11.","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","ama":"Danzl JG. Diffraction-unlimited optical imaging for synaptic physiology. Opera Medica et Physiologica. 2018;4(S1):11. doi:10.20388/omp2018.00s1.001","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."},"user_id":"8b945eb4-e2f2-11eb-945a-df72226e66a9","author":[{"last_name":"Danzl","full_name":"Danzl, Johann G","orcid":"0000-0001-8559-3973","id":"42EFD3B6-F248-11E8-B48F-1D18A9856A87","first_name":"Johann G"}],"article_processing_charge":"No","title":"Diffraction-unlimited optical imaging for synaptic physiology","year":"2018","day":"30","publication":"Opera Medica et Physiologica","page":"11","date_published":"2018-06-30T00:00:00Z","doi":"10.20388/omp2018.00s1.001","date_created":"2021-03-07T23:01:25Z","quality_controlled":"1","publisher":"Lobachevsky State University of Nizhny Novgorod","oa":1}]