Academic literature on the topic 'Distribution Shift'
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Journal articles on the topic "Distribution Shift"
Lameris, Thomas K., Jeroen Hoekendijk, Geert Aarts, Aline Aarts, Andrew M. Allen, Louise Bienfait, Allert I. Bijleveld, et al. "Migratory vertebrates shift migration timing and distributions in a warming Arctic." Animal Migration 8, no. 1 (January 1, 2021): 110–31. http://dx.doi.org/10.1515/ami-2020-0112.
Full textKlopčič, Matija, Andrej Rozman, and Andrej Bončina. "Evidence of a Climate-Change-Induced Shift in European Beech Distribution: An Unequal Response in the Elevation, Temperature and Precipitation Gradients." Forests 13, no. 8 (August 17, 2022): 1311. http://dx.doi.org/10.3390/f13081311.
Full textTakesue, Hiroki, Toshimori Honjo, Kiyoshi Tamaki, and Yasuhiro Tokura. "Differential phase shift-quantum key distribution." IEEE Communications Magazine 47, no. 5 (May 2009): 102–6. http://dx.doi.org/10.1109/mcom.2009.4939284.
Full textYuki, Kazuhiro. "SECTORAL SHIFT, WEALTH DISTRIBUTION, AND DEVELOPMENT." Macroeconomic Dynamics 12, no. 4 (September 2008): 527–59. http://dx.doi.org/10.1017/s1365100508070296.
Full textLaine, Ilpo. "Zero distribution of some shift polynomials." Journal of Mathematical Analysis and Applications 469, no. 2 (January 2019): 808–26. http://dx.doi.org/10.1016/j.jmaa.2018.09.036.
Full textButt, Mehwish, Hafiza Farwa Amin, Javed Iqbal, Maqbool Hussain Sial, Najam-ul Hassan, and Mueen-ud-Din Azad. "Homogeneously Weighted Moving Average Control Chart for Rayleigh Distribution." Bulletin of Business and Economics (BBE) 12, no. 3 (November 24, 2023): 366–84. http://dx.doi.org/10.61506/01.00043.
Full textYu, Xu, Miao Yu, Li-xun Xu, Jing Yang, and Zhi-qiang Xie. "Training Classifiers under Covariate Shift by Constructing the Maximum Consistent Distribution Subset." Mathematical Problems in Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/302815.
Full textA Hassan, Mohamed, and Samia SA Hassan. "pp Coulomb Phase Shift for Different Proton Charge Distributions." Australian Journal of Physics 45, no. 5 (1992): 635. http://dx.doi.org/10.1071/ph920635.
Full textYe, Nanyang, Lin Zhu, Jia Wang, Zhaoyu Zeng, Jiayao Shao, Chensheng Peng, Bikang Pan, Kaican Li, and Jun Zhu. "Certifiable Out-of-Distribution Generalization." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 9 (June 26, 2023): 10927–35. http://dx.doi.org/10.1609/aaai.v37i9.26295.
Full textInoue, Kyo. "Differential Phase-Shift Quantum Key Distribution Systems." IEEE Journal of Selected Topics in Quantum Electronics 21, no. 3 (May 2015): 109–15. http://dx.doi.org/10.1109/jstqe.2014.2360362.
Full textDissertations / Theses on the topic "Distribution Shift"
Zennaro, Fabio. "Feature distribution learning for covariate shift adaptation using sparse filtering." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/feature-distribution-learning-for-covariate-shift-adaptation-using-sparse-filtering(67989db2-b8a0-4fac-8832-f611e9236ed5).html.
Full textIngram, Douglas Russell. "Starlight correlated with damped Lyman alpha absorbers /." Thesis, Connect to this title online; UW restricted, 1996. http://hdl.handle.net/1773/5435.
Full textNodet, Pierre. "Biquality learning : from weakly supervised learning to distribution shifts." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG030.
Full textThe field of Learning with weak supervision is called Weakly Supervised Learning and aggregates a variety of situations where the collected ground truth is imperfect. The collected labels may suffer from bad quality, non-adaptability, or insufficient quantity. In this report, we propose a novel taxonomy of Weakly Supervised Learning as a continuous cube called the Weak Supervision Cube that encompasses all of the weaknesses of supervision. To design algorithms capable of handling any weak supervisions, we suppose the availability of a small trusted dataset, without bias and corruption, in addition to the potentially corrupted dataset. The trusted dataset allows the definition of a generic learning framework named Biquality Learning. We review the state-of-the-art of these algorithms that assumed the availability of a small trusted dataset. Under this framework, we propose an algorithm based on Importance Reweighting for Biquality Learning (IRBL). This classifier-agnostic approach is based on the empirical estimation of the Radon-Nikodym derivative (RND), to build a risk-consistent estimator on reweighted untrusted data. Then we extend the proposed framework to dataset shifts. Dataset shifts happen when the data distribution observed at training time is different from what is expected from the data distribution at testing time. So we propose an improved version of IRBL named IRBL2, capable of handling such dataset shifts. Additionally, we propose another algorithm named KPDR based on the same theory but focused on covariate shift instead of the label noise formulation. To diffuse and democratize the Biquality Learning Framework, we release an open-source Python library à la Scikit-Learn for Biquality Learning named biquality-learn
Chen, Xiaojun. "Multiple Scattering from Bubble Clouds." Scholarly Repository, 2010. http://scholarlyrepository.miami.edu/oa_theses/36.
Full textHo, Yo-Bin. "Modeling the distribution and shift of Chinese Americans in the United States : an analysis by trend surface expansion /." The Ohio State University, 1995. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487861796820923.
Full textBrodén, Daniel. "Analysis of Demand Response Solutions for Congestion Management in Distribution Networks." Thesis, KTH, Industriella informations- och styrsystem, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-138575.
Full textFigueiredo, Cláudia Cerqueira de Souza Machado Vieira. "Repartição funcional do rendimento no Brasil : uma abordagem setorial." Master's thesis, Instituto Superior de Economia e Gestão, 2019. http://hdl.handle.net/10400.5/19042.
Full textNeste trabalho faz-se uma análise da evolução da repartição funcional do rendimento no período contemporâneo Brasileiro, entre 2000 e 2016. A alteração da parte do trabalho no rendimento gerado na economia (VAB ou PIB), o chamado labour share, resulta da combinação de duas tendências importantes, a saber, a evolução da produtividade do trabalho e a do salário médio. Por sua vez, a alteração global (ou média) destas variáveis resulta das tendências verificadas em cada setor da economia em causa, cada um com as suas peculiaridades. Depois de um breve enquadramento teórico e revisão da literatura relevante, para a análise empírica da evolução do caso brasileiro será dada atenção à imputação do rendimento misto a "salários" e "lucros". Com isto pretende-se observar as relações existentes entre a evolução da participação do trabalho na economia e as transformações registadas na estrutura produtiva. Faz-se ainda a aplicação de uma análise shift-share, através da qual é possível distinguir/quantificar o chamado efeito "intra-sectorial" ou "within" (evolução do labour share de cada setor) do efeito "inter-setorial" ou "between" (ou de mudança estrutural, i.e., alterações no peso relativo de cada setor).
This paper analyzes the evolution of the functional distribution of income in the contemporary Brazilian period between 2000 and 2016. The change in the share of labor in the income generated in the economy (GVA or GDP), the so-called labor share, results from the combination of two important trends, namely the evolution of labor productivity and that of the average wage. In turn, the overall (or average) change in these variables results from trends in each sector of the economy concerned, each with its own peculiarities. After a brief theoretical framework and review of the relevant literature, for the empirical analysis of the evolution of the Brazilian case, attention will be given to the imputation of mixed income to "wages" and "profits". With this it is intended to observe the existing relations between the evolution of the participation of the work in the economy and the transformations registered in the productive structure. A shift-share analysis is also applied, whereby it is possible to distinguish / quantify the so-called "intra-sectoral" or "within" effect (evolution of each sector's labor share) from the "inter-sectoral" or "inter-sectoral" effect. "Between" (or structural change, ie, changes in the relative weight of each sector).
info:eu-repo/semantics/publishedVersion
Ryckebusch, Gaëlle. "Analysis of Demand-Response Participation Strategies for Congestion Management in an Island Distribution Network." Thesis, KTH, Industriella informations- och styrsystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-169220.
Full textSlove, Davidson Jessica. "The plasticity and geography of host use and the diversification of butterflies." Doctoral thesis, Stockholms universitet, Zoologiska institutionen, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-69573.
Full textAt the time of the doctoral defence,the following papers were unpublished and had a status as follows: Paper 3: Submitted; Papers 4 and 5: Manuscripts
Fisco, Dana. "Reef Fish Spatial Distribution and Benthic Habitat Associations on the Southeast Florida Reef Tract." NSUWorks, 2016. http://nsuworks.nova.edu/occ_stuetd/408.
Full textBooks on the topic "Distribution Shift"
Metcalf, Gilbert E. A distributional analysis of an environmental tax shift. Cambridge, MA: National Bureau of Economic Research, 1998.
Find full textWorld Data Center A for Rockets and Satellites., ed. A compilation of redshifts and velocity dispersions for Abell clusters (Struble and Rood 1987): Documentation for the machine-readable version. Greenbelt, Md: National Space Science Data Center, World Data Center A for Rockets and Satellites, National Aeronautics and Space Administration, Goddard Space Flight Center, 1989.
Find full textUnited States. National Aeronautics and Space Administration., ed. Extended X-ray emission around quasars at intermediate redshift: NASA grant NAG5-2476, annual report for the period 1 December 1995 through 30 November 1997. Cambridge, Mass: Smithsonian Institution, Astrophysical Observatory, 1998.
Find full textUnited States. National Aeronautics and Space Administration., ed. Extended X-ray emission around quasars at intermediate redshift: NASA grant NAG5-2476, annual report for the period 1 December 1995 through 30 November 1997. Cambridge, Mass: Smithsonian Institution, Astrophysical Observatory, 1998.
Find full textUnited States. National Aeronautics and Space Administration., ed. Extended X-ray emission around quasars at intermediate redshift: NASA grant NAG5-2476, annual report for the period 1 December 1995 through 30 November 1997. Cambridge, Mass: Smithsonian Institution, Astrophysical Observatory, 1998.
Find full textLanguage shift among schoolchildren in Gaeltacht areas, 1974-1984: An analysis of the distribution of £10 grant qualifiers. Baile Átha Cliath [Dublin]: Linguistics Institute of Ireland, 1990.
Find full textKrueger, Alan B. Labor market shifts and the price puzzle revisited. Cambridge, MA: National Bureau of Economic Research, 1997.
Find full textubker, Malte Lu. Assessing the impact of past distributional shifts on global poverty levels. Geneva: International Labour Office, 2002.
Find full textRadner, Daniel. Shifts in the aged-nonaged income relationship, 1979-85. Washington: Social Security Administration, Office of Policy, Office of Research and Statistics, 1988.
Find full textWalls, Margaret A. Distributional impacts of an environmental tax shift: The case of motor vehicle emissions taxes. Washington, DC: Resources for the Future, 1996.
Find full textBook chapters on the topic "Distribution Shift"
Oza, Poojan, Hien V. Nguyen, and Vishal M. Patel. "Multiple Class Novelty Detection Under Data Distribution Shift." In Computer Vision – ECCV 2020, 432–49. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58571-6_26.
Full textHwang, Sehyun, Sohyun Lee, Sungyeon Kim, Jungseul Ok, and Suha Kwak. "Combating Label Distribution Shift for Active Domain Adaptation." In Lecture Notes in Computer Science, 549–66. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19827-4_32.
Full textAlexander, Esther. "An Income-Distribution Demand-Shift Model of Inflation." In Soft Order in Physical Systems, 203–21. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2458-8_29.
Full textLupart, Simon, Thibault Formal, and Stéphane Clinchant. "MS-Shift: An Analysis of MS MARCO Distribution Shifts on Neural Retrieval." In Lecture Notes in Computer Science, 636–52. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-28244-7_40.
Full textYue, Yaojie, Peng Su, Yuan Gao, Puying Zhang, Ran Wang, Anyu Zhang, Qinghua Jiang, Weidong Ma, Yuantao Zhou, and Jing’ai Wang. "Mapping Global Crop Distribution." In Atlas of Global Change Risk of Population and Economic Systems, 131–48. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6691-9_10.
Full textDussap, Bastien, Gilles Blanchard, and Badr-Eddine Chérief-Abdellatif. "Label Shift Quantification with Robustness Guarantees via Distribution Feature Matching." In Machine Learning and Knowledge Discovery in Databases: Research Track, 69–85. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-43424-2_5.
Full textBardaji, J. B., B. E. J. Bodmann, M. T. Vilhena, and A. C. M. Alvim. "Half-Life Distribution Shift of Fission Products by Coupled Fission–Fusion Processes." In Integral Methods in Science and Engineering, 43–55. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16727-5_4.
Full textZhao, Chenyang, Zihao Zhou, and Bin Liu. "On Context Distribution Shift in Task Representation Learning for Online Meta RL." In Lecture Notes in Computer Science, 614–28. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-4761-4_52.
Full textKumar, Abhinandan, and T. Ghose. "Sensitivity Factor Analysis of Hybrid AC–DC Distribution System and Overload Alleviation Using Modified Generator Shift Distribution Factor." In Advances in Smart Grid Automation and Industry 4.0, 777–85. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-7675-1_78.
Full textStade, Dawid, and Martin Manns. "Robotic Assembly Line Balancing with Multimodal Stochastic Processing Times." In Advances in Automotive Production Technology – Towards Software-Defined Manufacturing and Resilient Supply Chains, 78–84. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-27933-1_8.
Full textConference papers on the topic "Distribution Shift"
Cao, Tri, Jiawen Zhu, and Guansong Pang. "Anomaly Detection under Distribution Shift." In 2023 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2023. http://dx.doi.org/10.1109/iccv51070.2023.00599.
Full textYu, Runpeng, Songhua Liu, Xingyi Yang, and Xinchao Wang. "Distribution Shift Inversion for Out-of-Distribution Prediction." In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2023. http://dx.doi.org/10.1109/cvpr52729.2023.00350.
Full textInoue, Kyo, Hiroki Takesue, and Toshimori Honjo. "Differential-phase-shift quantum key distribution." In Optics East 2007, edited by Yasuhiko Arakawa, Masahide Sasaki, and Hideyuki Sotobayashi. SPIE, 2007. http://dx.doi.org/10.1117/12.733442.
Full textInoue, Kyo, Edo Waks, and Yoshihisa Yamamoto. "Differential phase-shift quantum key distribution." In Photonics Asia 2002, edited by Songhao Liu, Guangcan Guo, Hoi-Kwong Lo, and Nobuyuki Imoto. SPIE, 2002. http://dx.doi.org/10.1117/12.483037.
Full textSych, Denis, and Gerd Leuchs. "Continuous phase-shift quantum key distribution." In 11th European Quantum Electronics Conference (CLEO/EQEC). IEEE, 2009. http://dx.doi.org/10.1109/cleoe-eqec.2009.5196231.
Full textHiroki Takesue, Toshimori Honjo, Kiyoshi Tamaki, and Yasuhiro Tokura. "Differential phase shift quantum key distribution." In 2008 Innovations in NGN - Future Network and Services, An ITU-T Kaleidoscope Conference (K-INGN). IEEE, 2008. http://dx.doi.org/10.1109/kingn.2008.4542270.
Full textAbrahamsson, H., and M. Bjorkman. "Caching for IPTV distribution with time-shift." In 2013 International Conference on Computing, Networking and Communications (ICNC 2013). IEEE, 2013. http://dx.doi.org/10.1109/iccnc.2013.6504212.
Full textSaha, Sudipan, Shan Zhao, Muhammad Shahzad, and Xiao Xiang Zhu. "Mitigating Distribution Shift for Multi-Sensor Classification." In IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2022. http://dx.doi.org/10.1109/igarss46834.2022.9883596.
Full textZhang, An, Jingnan Zheng, Xiang Wang, Yancheng Yuan, and Tat-Seng Chua. "Invariant Collaborative Filtering to Popularity Distribution Shift." In WWW '23: The ACM Web Conference 2023. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3543507.3583461.
Full textZhu, Yichen, Jian Yuan, Bo Jiang, Tao Lin, Haiming Jin, Xinbing Wang, and Chenghu Zhou. "Prediction with Incomplete Data under Agnostic Mask Distribution Shift." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/525.
Full textReports on the topic "Distribution Shift"
K.Y. Ng. Distribution of incoherent space-charge tune shift of bi-Gaussian beam. Office of Scientific and Technical Information (OSTI), June 2004. http://dx.doi.org/10.2172/825289.
Full textNg, K. Y. Distribution of incoherent space - Charge tune shift of a bi-Gaussian beam. Office of Scientific and Technical Information (OSTI), April 2004. http://dx.doi.org/10.2172/15020210.
Full textSawatzky, Richard, TT Sajobi, L. Russell, OA Awosoga, A. Ademola, JR Böhnke, O. Lawal, et al. A synthesis of response shift effects in quantitative health research: A systematic review and meta-regression protocol. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, September 2022. http://dx.doi.org/10.37766/inplasy2022.9.0033.
Full textDubeck, Margaret M., Jonathan M. B. Stern, and Rehemah Nabacwa. Learning to Read in a Local Language in Uganda: Creating Learner Profiles to Track Progress and Guide Instruction Using Early Grade Reading Assessment Results. RTI Press, June 2021. http://dx.doi.org/10.3768/rtipress.2021.op.0068.2106.
Full textKaymak, Barış, and Immo Schott. Corporate tax cuts and the decline of the manufacturing labor share. Federal Reserve Bank of Cleveland, December 2022. http://dx.doi.org/10.26509/frbc-wp-202239.
Full textZarillo, Gary, Sara Ramos, Kristopher Effinger, Kristen Becker, Irene Watts, Katherine Brutsché, Brian McFall, and Douglas Krafft. Evaluating cross-shore sediment grain size distribution, sediment transport, and morphological evolution of a nearshore berm at Fort Myers Beach, Florida. Engineer Research and Development Center (U.S.), March 2022. http://dx.doi.org/10.21079/11681/43780.
Full textAguilar, Glenn, Dan Blanchon, Hamish Foote, Christina Pollonais, and Asia Mosee. Queensland Fruit Fly Invasion of New Zealand: Predicting Area Suitability Under Future Climate Change Scenarios. Unitec ePress, October 2017. http://dx.doi.org/10.34074/pibs.rs22015.
Full textKostarakos, Ilias, and Petros Varthalitis. Effective tax rates in Ireland. ESRI, November 2020. http://dx.doi.org/10.26504/rs110.
Full textFontanari, Claudia, and Antonella Palumbo. Permanent Scars: The Effects of Wages on Productivity. Institute for New Economic Thinking Working Paper Series, July 2022. http://dx.doi.org/10.36687/inetwp187.
Full textMetcalf, Gilbert. A Distributional Analysis of an Environmental Tax Shift. Cambridge, MA: National Bureau of Economic Research, May 1998. http://dx.doi.org/10.3386/w6546.
Full text