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Статті в журналах з теми "Approximate counting"
BUSS, SAMUEL R., LESZEK ALEKSANDER KOŁODZIEJCZYK, and NEIL THAPEN. "FRAGMENTS OF APPROXIMATE COUNTING." Journal of Symbolic Logic 79, no. 2 (June 2014): 496–525. http://dx.doi.org/10.1017/jsl.2013.37.
Повний текст джерелаAronov, Boris, and Micha Sharir. "Approximate Halfspace Range Counting." SIAM Journal on Computing 39, no. 7 (January 2010): 2704–25. http://dx.doi.org/10.1137/080736600.
Повний текст джерелаLouchard, Guy, and Helmut Prodinger. "Generalized approximate counting revisited." Theoretical Computer Science 391, no. 1-2 (February 2008): 109–25. http://dx.doi.org/10.1016/j.tcs.2007.10.035.
Повний текст джерелаJeřábek, Emil. "Approximate counting in bounded arithmetic." Journal of Symbolic Logic 72, no. 3 (September 2007): 959–93. http://dx.doi.org/10.2178/jsl/1191333850.
Повний текст джерелаCichoń, Jacek, and Karol Gotfryd. "Average Counting via Approximate Histograms." ACM Transactions on Sensor Networks 14, no. 2 (July 21, 2018): 1–32. http://dx.doi.org/10.1145/3177922.
Повний текст джерелаKirschenhofer, Peter, and Helmut Prodinger. "Approximate counting : an alternative approach." RAIRO - Theoretical Informatics and Applications 25, no. 1 (1991): 43–48. http://dx.doi.org/10.1051/ita/1991250100431.
Повний текст джерелаBORDEWICH, M., M. FREEDMAN, L. LOVÁSZ, and D. WELSH. "Approximate Counting and Quantum Computation." Combinatorics, Probability and Computing 14, no. 5-6 (October 11, 2005): 737. http://dx.doi.org/10.1017/s0963548305007005.
Повний текст джерелаFlajolet, Philippe. "Approximate counting: A detailed analysis." BIT 25, no. 1 (March 1985): 113–34. http://dx.doi.org/10.1007/bf01934993.
Повний текст джерелаErdős, Péter L., Sándor Z. Kiss, István Miklós, and Lajos Soukup. "Approximate Counting of Graphical Realizations." PLOS ONE 10, no. 7 (July 10, 2015): e0131300. http://dx.doi.org/10.1371/journal.pone.0131300.
Повний текст джерелаAldous, David. "Approximate Counting via Markov Chains." Statistical Science 8, no. 1 (February 1993): 16–19. http://dx.doi.org/10.1214/ss/1177011078.
Повний текст джерелаДисертації з теми "Approximate counting"
Ben, Mazziane Younes. "Analyse probabiliste pour le caching." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ4014.
Повний текст джерелаCaches 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, and 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.
Повний текст джерелаZou, Tingxiang. "Structures pseudo-finies et dimensions de comptage." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSE1083/document.
Повний текст джерелаThis 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.
Повний текст джерелаSella, Francesco. "Typical and Atypical Development of Numerical Representation." Doctoral thesis, Università degli studi di Padova, 2013. http://hdl.handle.net/11577/3426396.
Повний текст джерелаCome 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.
Повний текст джерелаMany 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.
Повний текст джерелаWilkinson, Bryan T. "Adaptive Range Counting and Other Frequency-Based Range Query Problems." Thesis, 2012. http://hdl.handle.net/10012/6739.
Повний текст джерелаHamilton, Christopher. "Range Searching Data Structures with Cache Locality." 2011. http://hdl.handle.net/10222/13363.
Повний текст джерела"Approximately Counting Perfect and General Matchings in Bipartite and General Graphs." Diss., 2009. http://hdl.handle.net/10161/1054.
Повний текст джерелаКниги з теми "Approximate counting"
Dyer, Martin. Approximately counting Hamilton cycles in dense graphs. Edinburgh: LFCS, Dept. of Computer Science, University of Edinburgh, 1993.
Знайти повний текст джерелаMurphy, Stuart J. Coyotes All Around (Mathstart). HarperCollins Publishers, 2003.
Знайти повний текст джерелаLeFevre, Jo-Anne, Emma Wells, and Carla Sowinski. Individual Differences in Basic Arithmetical Processes in Children and Adults. Edited by Roi Cohen Kadosh and Ann Dowker. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199642342.013.005.
Повний текст джерелаUittenhove, Kim, and Patrick Lemaire. Numerical Cognition during Cognitive Aging. Edited by Roi Cohen Kadosh and Ann Dowker. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199642342.013.045.
Повний текст джерелаNúñez, Rafael, and Tyler Marghetis. Cognitive Linguistics and the Concept(s) of Number. Edited by Roi Cohen Kadosh and Ann Dowker. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199642342.013.023.
Повний текст джерелаThe 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.
Знайти повний текст джерелаJucker, J., and 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.
Знайти повний текст джерелаЧастини книг з теми "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.
Повний текст джерелаLipton, 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.
Повний текст джерелаAaronson, Scott, and 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.
Повний текст джерелаTan, Yong Kiam, Jiong Yang, Mate Soos, Magnus O. Myreen, and 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.
Повний текст джерелаGao, Younan, and 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.
Повний текст джерелаYang, Jiong, and 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.
Повний текст джерелаManjunath, Madhusudan, Kurt Mehlhorn, Konstantinos Panagiotou, and 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.
Повний текст джерелаBordewich, Magnus, Martin Dyer, and 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.
Повний текст джерелаBendík, Jaroslav, and 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.
Повний текст джерелаWang, Jinyan, Minghao Yin, and 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.
Повний текст джерелаТези доповідей конференцій з теми "Approximate counting"
Meng, Chang, Hanyu Wang, Yuqi Mai, Weikang Qian, and 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.
Повний текст джерелаMitchell, Scott A., and 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.
Повний текст джерелаAndrei, Stefan, Gabriel Manolache, Roland H. C. Yap, and 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.
Повний текст джерелаDyer, 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.
Повний текст джерелаNelson, Jelani, and 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.
Повний текст джерелаSlota, George M., and 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.
Повний текст джерелаHuber, 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.
Повний текст джерелаChan, Timothy M., and 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.
Повний текст джерелаTing, 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.
Повний текст джерелаAfshani, Peyman, and 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.
Повний текст джерелаЗвіти організацій з теми "Approximate counting"
Rosenkrantz, Walter A. Approximate Counting. A Martingale Approach. Fort Belvoir, VA: Defense Technical Information Center, February 1986. http://dx.doi.org/10.21236/ada170229.
Повний текст джерелаBaader, Franz, Pavlos Marantidis, and Alexander Okhotin. Approximately Solving Set Equations. Technische Universität Dresden, 2016. http://dx.doi.org/10.25368/2022.227.
Повний текст джерелаDavis, James C., John Cromartie, Tracey Farrigan, Brandon Genetin, Austin Sanders, and Justin B. Winikoff. Rural America at a glance. Washington, D.C: United States Department of Agriculture, Economic Research Service, November 2023. http://dx.doi.org/10.32747/2023.8134362.ers.
Повний текст джерелаConnell, 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.
Повний текст джерелаArhin, Stephen, Babin Manandhar, Hamdiat Baba Adam, and Adam Gatiba. Predicting Bus Travel Times in Washington, DC Using Artificial Neural Networks (ANNs). Mineta Transportation Institute, April 2021. http://dx.doi.org/10.31979/mti.2021.1943.
Повний текст джерелаAhn, Yushin, and Richard Poythress. Impervious Surfaces from High Resolution Aerial Imagery: Cities in Fresno County. Mineta Transportation Institute, May 2024. http://dx.doi.org/10.31979/mti.2024.2257.
Повний текст джерелаPfisterer, Nathan, and Nathan Beane. Estimating present value cost of invasive Emerald Ash Borer (Agrilus planipennis) on USACE project lands. Engineer Research and Development Center (U.S.), February 2023. http://dx.doi.org/10.21079/11681/46475.
Повний текст джерелаAnderson, Zachary W., Greg N. McDonald, Elizabeth A. Balgord, and W. Adolph Yonkee. Interim Geologic Map of the Browns Hole Quadrangle, Weber and Cache Counties, Utah. Utah Geological Survey, December 2023. http://dx.doi.org/10.34191/ofr-760.
Повний текст джерелаPesis, Edna, Elizabeth J. Mitcham, Susan E. Ebeler, and Amnon Lers. Application of Pre-storage Short Anaerobiosis to Alleviate Superficial Scald and Bitter Pit in Granny Smith Apples. United States Department of Agriculture, January 2013. http://dx.doi.org/10.32747/2013.7593394.bard.
Повний текст джерела