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Parameterized Approximation Schemes for Clustering with General Norm Objectives.

F. Abbasi, S. Banerjee, J. Byrka, P. Chalermsook, A. Gadekar, K. Khodamoradi, D. Marx, R. Sharma, and J. Spoerhase. FOCS, page 1377-1399. IEEE, (2023)

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Ameet Patil

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Parameterized Approximation for Robust Clustering in Discrete Geometric SpacesF. Abbasi, S. Banerjee, J. Byrka, P. Chalermsook, A. Gadekar, K. Khodamoradi, D. Marx, R. Sharma, and J. Spoerhase. Proc. 51st International Colloquium on Automata, Languages and Programming (ICALP'24), (2024)Independent Set in $k$-Claw-Free Graphs: Conditional $\chi$-Boundedness and the Power of LP/SDP RelaxationsP. Chalermsook, A. Gadekar, K. Khodamoradi, and J. Spoerhase. Proc. International Workshop on Approximation and Online Algorithms (WAOA'23), (2023)to appear.Diversity-aware clustering: Computational Complexity and Approximation Algorithms.S. Thejaswi, A. Gadekar, B. Ordozgoiti, and A. Gionis. CoRR, (2024)Approximation algorithms for k-median with lower-bound constraints.A. Gadekar, B. Ordozgoiti, and S. Thejaswi. CoRR, (2021)Clustering with Fair-Center Representation: Parameterized Approximation Algorithms and Heuristics.S. Thejaswi, A. Gadekar, B. Ordozgoiti, and M. Osadnik. KDD, page 1749-1759. ACM, (2022)Parameterized Approximation Schemes for Clustering with General Norm Objectives.F. Abbasi, S. Banerjee, J. Byrka, P. Chalermsook, A. Gadekar, K. Khodamoradi, D. Marx, R. Sharma, and J. Spoerhase. FOCS, page 1377-1399. IEEE, (2023)Improved learning of k-parities.A. Bhattacharyya, A. Gadekar, and N. Rajgopal. Theor. Comput. Sci., (2020)On the parameterized complexity of Compact Set Packing.A. Gadekar. CoRR, (2021)Parameterized Approximation Results for Clustering and Graph Packing Problems.A. Gadekar. Aalto University, Espoo, Finland, (2023)base-search.net (ftaaltouniv:oai:aaltodoc.aalto.fi:123456789/125675).On the Parameterized Complexity of Compact Set Packing.A. Gadekar. WALCOM, volume 13973 of Lecture Notes in Computer Science, page 359-370. Springer, (2023)

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Parameterized Approximation Schemes for Clustering with General Norm Objectives.

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Ameet Patil

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Parameterized Approximation Schemes for Clustering with General Norm Objectives.

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Ameet Patil

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Parameterized Approximation Schemes for Clustering with General Norm Objectives.