Literatura científica selecionada sobre o tema "Approximate counting"
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Artigos de revistas sobre o assunto "Approximate counting"
BUSS, SAMUEL R., LESZEK ALEKSANDER KOŁODZIEJCZYK e NEIL THAPEN. "FRAGMENTS OF APPROXIMATE COUNTING". Journal of Symbolic Logic 79, n.º 2 (junho de 2014): 496–525. http://dx.doi.org/10.1017/jsl.2013.37.
Texto completo da fonteAronov, Boris, e Micha Sharir. "Approximate Halfspace Range Counting". SIAM Journal on Computing 39, n.º 7 (janeiro de 2010): 2704–25. http://dx.doi.org/10.1137/080736600.
Texto completo da fonteLouchard, Guy, e Helmut Prodinger. "Generalized approximate counting revisited". Theoretical Computer Science 391, n.º 1-2 (fevereiro de 2008): 109–25. http://dx.doi.org/10.1016/j.tcs.2007.10.035.
Texto completo da fonteJeřábek, Emil. "Approximate counting in bounded arithmetic". Journal of Symbolic Logic 72, n.º 3 (setembro de 2007): 959–93. http://dx.doi.org/10.2178/jsl/1191333850.
Texto completo da fonteCichoń, Jacek, e Karol Gotfryd. "Average Counting via Approximate Histograms". ACM Transactions on Sensor Networks 14, n.º 2 (21 de julho de 2018): 1–32. http://dx.doi.org/10.1145/3177922.
Texto completo da fonteKirschenhofer, Peter, e Helmut Prodinger. "Approximate counting : an alternative approach". RAIRO - Theoretical Informatics and Applications 25, n.º 1 (1991): 43–48. http://dx.doi.org/10.1051/ita/1991250100431.
Texto completo da fonteBORDEWICH, M., M. FREEDMAN, L. LOVÁSZ e D. WELSH. "Approximate Counting and Quantum Computation". Combinatorics, Probability and Computing 14, n.º 5-6 (11 de outubro de 2005): 737. http://dx.doi.org/10.1017/s0963548305007005.
Texto completo da fonteFlajolet, Philippe. "Approximate counting: A detailed analysis". BIT 25, n.º 1 (março de 1985): 113–34. http://dx.doi.org/10.1007/bf01934993.
Texto completo da fonteErdős, Péter L., Sándor Z. Kiss, István Miklós e Lajos Soukup. "Approximate Counting of Graphical Realizations". PLOS ONE 10, n.º 7 (10 de julho de 2015): e0131300. http://dx.doi.org/10.1371/journal.pone.0131300.
Texto completo da fonteAldous, David. "Approximate Counting via Markov Chains". Statistical Science 8, n.º 1 (fevereiro de 1993): 16–19. http://dx.doi.org/10.1214/ss/1177011078.
Texto completo da fonteTeses / dissertações sobre o assunto "Approximate counting"
Ben, Mazziane Younes. "Analyse probabiliste pour le caching". Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ4014.
Texto completo da fonteCaches are small memories that speed up data retrieval. Caching policies may aim to choose cache content to minimize latency in responding to item requests. A more general problem permits an item's request to be approximately answered by a similar cached item. This concept, referred to as "similarity caching," proves valuable for content-based image retrieval and recommendation systems. The objective is to further minimize latency while delivering satisfactory answers.Theoretical understanding of cache memory management algorithms under specific assumptions on the requests provides guidelines for choosing a suitable algorithm. The Least-Frequently-Used (LFU) and the Least-Recently-Used (LRU) are popular caching eviction policies. LFU is efficient when the requests process is stationary, while LRU adapts to changes in the patterns of the requests. Online learning algorithms, such as the randomized Follow-the-Perturbed Leader (FPL) algorithm, applied for caching, enjoy worst-case guarantees. Both LFU and FPL rely on items' request count. However, counting is challenging in memory-constrained scenarios. To overcome this problem, caching policies operate with approximate counting schemes, such as the Count-Min Sketch with Conservative Updates (CMS-CU), to balance counts' accuracy and memory usage. In the similarity caching setting, RND-LRU is a modified LRU where a request is probabilistically answered by the most similar cached item. Unfortunately, a theoretical analysis of an LFU cache utilizing CMS-CU, an FPL cache with an approximate counting algorithm, and RND-LRU remains difficult.This thesis investigates three randomized algorithms: CMS-CU, FPL with noisy items' request counts estimations (NFPL), and RND-LRU. For CMS-CU, we propose a novel approach to derive new upper bounds on the expected value and the complementary cumulative distribution function of the estimation error under a renewal request process. Additionally, we prove that NFPL behaves as well as the optimal omniscient static caching policy for any request sequence under specific conditions on the noisy counts. Finally, we introduce a new analytically tractable similarity caching policy and show that it can approximate RND-LRU
Dreier, Jan [Verfasser], Peter [Akademischer Betreuer] Rossmanith e Sebastian [Akademischer Betreuer] Siebertz. "Two new perspectives on algorithmic meta-theorems : evaluating approximate first-order counting queries on bounded expansion and first-order queries on random graphs / Jan Dreier ; Peter Rossmanith, Sebastian Siebertz". Aachen : Universitätsbibliothek der RWTH Aachen, 2020. http://d-nb.info/1228630380/34.
Texto completo da fonteZou, Tingxiang. "Structures pseudo-finies et dimensions de comptage". Thesis, Lyon, 2019. http://www.theses.fr/2019LYSE1083/document.
Texto completo da fonteThis thesis is about the model theory of pseudofinite structures with the focus on groups and fields. The aim is to deepen our understanding of how pseudofinite counting dimensions can interact with the algebraic properties of underlying structures and how we could classify certain classes of structures according to their counting dimensions. Our approach is by studying examples. We treat three classes of structures: The first one is the class of H-structures, which are generic expansions of existing structures. We give an explicit construction of pseudofinite H-structures as ultraproducts of finite structures. The second one is the class of finite difference fields. We study properties of coarse pseudofinite dimension in this class, show that it is definable and integer-valued and build a partial connection between this dimension and transformal transcendence degree. The third example is the class of pseudofinite primitive permutation groups. We generalise Hrushovski's classical classification theorem for stable permutation groups acting on a strongly minimal set to the case where there exists an abstract notion of dimension, which includes both the classical model theoretic ranks and pseudofinite counting dimensions. In this thesis, we also generalise Schlichting's theorem for groups to the case of approximate subgroups with a notion of commensurability
Kelk, Steven M. "On the relative complexity of approximately counting H-colourings". Thesis, University of Warwick, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.398734.
Texto completo da fonteSella, Francesco. "Typical and Atypical Development of Numerical Representation". Doctoral thesis, Università degli studi di Padova, 2013. http://hdl.handle.net/11577/3426396.
Texto completo da fonteCome viene rappresentata l’informazione numerica? Recenti ricerche hanno evidenziato il ruolo fondamentale dei sistemi cognitive preverbali nella rappresentazione numerica: l’Object Tracking System (OTS) e l’Approximate Number System (ANS; o Analogue Magnitude System). Il primo è un meccanismo generale che permette di conservare in memoria le caratteristiche spazio-temporali degli stimoli e la sua capacità è limitata (3-4 elementi). Il secondo è un meccanismo quantitativo che rappresenta ogni numerosità come una distribuzione d’attivazione su teorica linea numerica mentale. Nella presente lavoro di tesi, presenteremo diversi studi volti ad indagare il funzionamento di questi meccanismi in interazione con processi di stima numerica e non-numerica in contesto di sviluppo tipico ed atipico. Nello Studio 1.1, abbiamo utilizzato un compito di imitazione per indagare la capacità di concentrarsi spontaneamente sulla numerosità in bambini di 2 ½ anni. I risultati hanno evidenziato come la maggior parte dei bambini adotti un sistema analogico di quantità quando analizzano spontaneamente delle quantità numeriche. La selezione di questo meccanismo è probabilmente legata sia alla minor richiesta di risorse attentive, sia alla disponibilità di altri indizi quantitativi (non numerici) che covariano con la numerosità. Nello Studio 1.2, bambini di 2 ½ anni hanno svolto un compito di categorizzazione per investigare la loro capacità di stimare la grandezza numerica di insiemi. Le stime dei bambini erano indipendenti dalle caratteristiche visive degli elementi dell’insieme (i.e. perimetro o densità) per le quantità dentro il range di OTS (1-4 elementi). Le stime di quantità più grandi (5-9 elementi) erano invece influenzate dalle caratteristiche visive degli stimoli: in particolare, l’aumento del perimetro con densità costante sembra essere la combinazione di caratteristiche visive degli stimoli che fa aumentare maggiormente la percezione di numerosità. Nello Studio 2, bambini prescolari, di prima primaria e di terza primaria dovevano stimare quantità continue, discrete e simboliche. I risultati suggeriscono la presenza di differenti meccanismi coinvolti nella stima di quantità continue rispetto a quelle numeriche (discrete e simboliche). Nello Studio 3, abbiamo utilizzato il paradigma del doppio compito per studiare la relazione tra memoria visiva a breve termine e subitizing. Dai risultati emerge una marcata corrispondenza tra il numero di elementi memorizzati ed il numero di elementi che possono essere velocemente enumerati attraverso il subitizing. Nello Studio 4.1, bambini con diagnosi di Discalculia Evolutiva (DE) in comorbidità con sindrome non verbale (SNV) e bambini con sviluppo tipico hanno svolto un compito di confronto di quantità numeriche. Abbiamo riscontrato un deficit nella discriminazione di numerosità nel gruppo DE-SNV rispetto ai bambini a sviluppo tipico. In particolare, la capacità di OTS sembra essere ridotta nei bambini con DE-SNV rispetto ai bambini a sviluppo tipico. Nello Studio 4.2, bambini con diagnosi di Discalculia Evolutiva (DE) e bambini con sviluppo tipico hanno completato due compiti di stima sulla linea numerica. I bambini con DE hanno mostrato minor precisione nella stima di quantità simboliche suggerendo una rappresentazione numerica deficitaria rispetto al gruppo con sviluppo tipico. Nello Studio 5, ragazzi con sindrome di Down (SD) e bambini con sviluppo tipico pareggiati per età mentale (EM) ed età cronologica (EC) hanno svolto due compiti numerici per valutare le loro abilità di discriminazione numerica e di conteggio. I ragazzi con SD hanno mostrato un deficit nel discriminare piccole quantità, all’interno del range di OTS, rispetto ai bambini a sviluppo tipico pareggiati sia per EM che per EC. Nella comparazione di numerosità più grandi, i ragazzi con SD hanno ottenuto una performance simile ai bambini pareggiati per EM e minore rispetto ai ragazzi pareggiati per EC. Infine, l’abilità di conteggio appare simile tra i partecipanti con SD e i bambini pareggiati per EM.
Schott, Sarah. "TPA: A New Method for Approximate Counting". Diss., 2012. http://hdl.handle.net/10161/5429.
Texto completo da fonteMany high dimensional integrals can be reduced to the problem of finding the relative measure of two sets. Often one set will be exponentially larger than the other. A standard method of dealing with this problem is to interpolate between the sets with a series of nested sets where neighboring nested sets have relative measures bounded above by a constant. Choosing these sets can be very difficult in practice. Here a new approach that creates a randomly drawn sequence of such sets is presented. This procedure gives faster approximation algorithms and a well-balanced set of nested sets that are essential to building effective tempering and annealing algorithms.
Dissertation
Afshani, Peyman. "On Geometric Range Searching, Approximate Counting and Depth Problems". Thesis, 2008. http://hdl.handle.net/10012/4032.
Texto completo da fonteWilkinson, Bryan T. "Adaptive Range Counting and Other Frequency-Based Range Query Problems". Thesis, 2012. http://hdl.handle.net/10012/6739.
Texto completo da fonteHamilton, Christopher. "Range Searching Data Structures with Cache Locality". 2011. http://hdl.handle.net/10222/13363.
Texto completo da fonte"Approximately Counting Perfect and General Matchings in Bipartite and General Graphs". Diss., 2009. http://hdl.handle.net/10161/1054.
Texto completo da fonteLivros sobre o assunto "Approximate counting"
Dyer, Martin. Approximately counting Hamilton cycles in dense graphs. Edinburgh: LFCS, Dept. of Computer Science, University of Edinburgh, 1993.
Encontre o texto completo da fonteMurphy, Stuart J. Coyotes All Around (Mathstart). HarperCollins Publishers, 2003.
Encontre o texto completo da fonteLeFevre, Jo-Anne, Emma Wells e Carla Sowinski. Individual Differences in Basic Arithmetical Processes in Children and Adults. Editado por Roi Cohen Kadosh e Ann Dowker. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199642342.013.005.
Texto completo da fonteUittenhove, Kim, e Patrick Lemaire. Numerical Cognition during Cognitive Aging. Editado por Roi Cohen Kadosh e Ann Dowker. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199642342.013.045.
Texto completo da fonteNúñez, Rafael, e Tyler Marghetis. Cognitive Linguistics and the Concept(s) of Number. Editado por Roi Cohen Kadosh e Ann Dowker. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199642342.013.023.
Texto completo da fonteThe Bruce-Grey Plant Committee (Owen Sound Field Naturalists). Asters, Goldenrods and Fleabanes of Grey and Bruce Counties: Includes Approximately 50% of Ontario Species. Stan Brown Printers Ltd., 2000.
Encontre o texto completo da fonteJucker, J., e G. J. Trinkaus. Design and Estimate of Approximate Cost of a Sanitary Sewer System for the Village of Barrington, Cook and Lake Counties, Illinois. Creative Media Partners, LLC, 2018.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Approximate counting"
Bubley, Russ. "Approximate Counting". In Randomized Algorithms: Approximation, Generation and Counting, 29–36. London: Springer London, 2001. http://dx.doi.org/10.1007/978-1-4471-0695-1_3.
Texto completo da fonteLipton, Richard J. "An Approximate Counting Method". In The P=NP Question and Gödel’s Lost Letter, 115–18. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-7155-5_25.
Texto completo da fonteAaronson, Scott, e Patrick Rall. "Quantum Approximate Counting, Simplified". In Symposium on Simplicity in Algorithms, 24–32. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2020. http://dx.doi.org/10.1137/1.9781611976014.5.
Texto completo da fonteTan, Yong Kiam, Jiong Yang, Mate Soos, Magnus O. Myreen e Kuldeep S. Meel. "Formally Certified Approximate Model Counting". In Computer Aided Verification, 153–77. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65627-9_8.
Texto completo da fonteGao, Younan, e Meng He. "On Approximate Colored Path Counting". In Lecture Notes in Computer Science, 209–24. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-55598-5_14.
Texto completo da fonteYang, Jiong, e Kuldeep S. Meel. "Rounding Meets Approximate Model Counting". In Computer Aided Verification, 132–62. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-37703-7_7.
Texto completo da fonteManjunath, Madhusudan, Kurt Mehlhorn, Konstantinos Panagiotou e He Sun. "Approximate Counting of Cycles in Streams". In Algorithms – ESA 2011, 677–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23719-5_57.
Texto completo da fonteBordewich, Magnus, Martin Dyer e Marek Karpinski. "Stopping Times, Metrics and Approximate Counting". In Automata, Languages and Programming, 108–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11786986_11.
Texto completo da fonteBendík, Jaroslav, e Kuldeep S. Meel. "Approximate Counting of Minimal Unsatisfiable Subsets". In Computer Aided Verification, 439–62. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-53288-8_21.
Texto completo da fonteWang, Jinyan, Minghao Yin e Jingli Wu. "Approximate Model Counting via Extension Rule". In Frontiers in Algorithmics, 229–40. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19647-3_22.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Approximate counting"
Meng, Chang, Hanyu Wang, Yuqi Mai, Weikang Qian e Giovanni De Micheli. "VACSEM: Verifying Average Errors in Approximate Circuits Using Simulation-Enhanced Model Counting". In 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE), 1–6. IEEE, 2024. http://dx.doi.org/10.23919/date58400.2024.10546819.
Texto completo da fonteMitchell, Scott A., e David M. Day. "Flexible approximate counting". In the 15th Symposium. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2076623.2076655.
Texto completo da fonteAndrei, Stefan, Gabriel Manolache, Roland H. C. Yap e Victor Felea. "Approximate Satisfiability Counting". In 2007 Ninth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing. IEEE, 2007. http://dx.doi.org/10.1109/synasc.2007.16.
Texto completo da fonteDyer, Martin. "Approximate counting by dynamic programming". In the thirty-fifth ACM symposium. New York, New York, USA: ACM Press, 2003. http://dx.doi.org/10.1145/780542.780643.
Texto completo da fonteNelson, Jelani, e Huacheng Yu. "Optimal Bounds for Approximate Counting". In SIGMOD/PODS '22: International Conference on Management of Data. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3517804.3526225.
Texto completo da fonteSlota, George M., e Kamesh Madduri. "Fast Approximate Subgraph Counting and Enumeration". In 2013 42nd International Conference on Parallel Processing (ICPP). IEEE, 2013. http://dx.doi.org/10.1109/icpp.2013.30.
Texto completo da fonteHuber, Mark. "Exact sampling and approximate counting techniques". In the thirtieth annual ACM symposium. New York, New York, USA: ACM Press, 1998. http://dx.doi.org/10.1145/276698.276709.
Texto completo da fonteChan, Timothy M., e Bryan T. Wilkinson. "Adaptive and Approximate Orthogonal Range Counting". In Proceedings of the Twenty-Fourth Annual ACM-SIAM Symposium on Discrete Algorithms. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2013. http://dx.doi.org/10.1137/1.9781611973105.18.
Texto completo da fonteTing, Daniel. "Streamed approximate counting of distinct elements". In KDD '14: The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2623330.2623669.
Texto completo da fonteAfshani, Peyman, e Timothy M. Chan. "On approximate range counting and depth". In the twenty-third annual symposium. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1247069.1247129.
Texto completo da fonteRelatórios de organizações sobre o assunto "Approximate counting"
Rosenkrantz, Walter A. Approximate Counting. A Martingale Approach. Fort Belvoir, VA: Defense Technical Information Center, fevereiro de 1986. http://dx.doi.org/10.21236/ada170229.
Texto completo da fonteBaader, Franz, Pavlos Marantidis e Alexander Okhotin. Approximately Solving Set Equations. Technische Universität Dresden, 2016. http://dx.doi.org/10.25368/2022.227.
Texto completo da fonteDavis, James C., John Cromartie, Tracey Farrigan, Brandon Genetin, Austin Sanders e Justin B. Winikoff. Rural America at a glance. Washington, D.C: United States Department of Agriculture, Economic Research Service, novembro de 2023. http://dx.doi.org/10.32747/2023.8134362.ers.
Texto completo da fonteConnell, Sean D. Geologic map of the Albuquerque - Rio Rancho metropolitan area and vicinity, Bernalillo and Sandoval counties, New Mexico. New Mexico Bureau of Geology and Mineral Resources, 2008. http://dx.doi.org/10.58799/gm-78.
Texto completo da fonteArhin, Stephen, Babin Manandhar, Hamdiat Baba Adam e Adam Gatiba. Predicting Bus Travel Times in Washington, DC Using Artificial Neural Networks (ANNs). Mineta Transportation Institute, abril de 2021. http://dx.doi.org/10.31979/mti.2021.1943.
Texto completo da fonteAhn, Yushin, e Richard Poythress. Impervious Surfaces from High Resolution Aerial Imagery: Cities in Fresno County. Mineta Transportation Institute, maio de 2024. http://dx.doi.org/10.31979/mti.2024.2257.
Texto completo da fontePfisterer, Nathan, e Nathan Beane. Estimating present value cost of invasive Emerald Ash Borer (Agrilus planipennis) on USACE project lands. Engineer Research and Development Center (U.S.), fevereiro de 2023. http://dx.doi.org/10.21079/11681/46475.
Texto completo da fonteAnderson, Zachary W., Greg N. McDonald, Elizabeth A. Balgord e W. Adolph Yonkee. Interim Geologic Map of the Browns Hole Quadrangle, Weber and Cache Counties, Utah. Utah Geological Survey, dezembro de 2023. http://dx.doi.org/10.34191/ofr-760.
Texto completo da fontePesis, Edna, Elizabeth J. Mitcham, Susan E. Ebeler e Amnon Lers. Application of Pre-storage Short Anaerobiosis to Alleviate Superficial Scald and Bitter Pit in Granny Smith Apples. United States Department of Agriculture, janeiro de 2013. http://dx.doi.org/10.32747/2013.7593394.bard.
Texto completo da fonte