{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/clustering/papers/108","list_of":"/task/clustering","task":"Clustering","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":108,"pages_in_order":108,"rows_per_page":100,"rows":[10701,10718],"of":10718,"counts":{"archive_papers_tagged":10718,"with_a_code_link":2823,"where_syntology_ran_a_sample":419,"not_listed_spam_title":0,"listed":10718,"listed_where_code_ran":419,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":335,"every_run_a_failure_of_syntologys_instrument":84,"listed_with_a_run_with_no_instrument_failure":335,"listed_every_run_a_failure_of_syntologys_instrument":84,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/clustering","prev":"/task/clustering/papers/107","next":null,"papers":[{"url":null,"slug":"an-efficient-sequential-monte-carlo-algorithm","title":"An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering","date":"2008-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"cyclizing-clusters-via-zeta-function-of-a","title":"Cyclizing Clusters via Zeta Function of a Graph","date":"2008-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"dimensionality-reduction-for-data-in-multiple","title":"Dimensionality Reduction for Data in Multiple Feature Representations","date":"2008-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"kernel-measures-of-independence-for-non-iid","title":"Kernel Measures of Independence for non-iid Data","date":"2008-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-taxonomies-by-dependence","title":"Learning Taxonomies by Dependence Maximization","date":"2008-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mcboost-multiple-classifier-boosting-for","title":"MCBoost: Multiple Classifier Boosting for Perceptual Co-clustering of Images and Visual Features","date":"2008-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"measures-of-clustering-quality-a-working-set","title":"Measures of Clustering Quality: A Working Set of Axioms for Clustering","date":"2008-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-reliability-of-clustering-stability-in","title":"On the Reliability of Clustering Stability in the Large Sample Regime","date":"2008-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"regularized-co-clustering-with-dual","title":"Regularized Co-Clustering with Dual Supervision","date":"2008-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"spectral-clustering-with-perturbed-data","title":"Spectral Clustering with Perturbed Data","date":"2008-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"extracting-key-entities-and-significant","title":"Extracting Key Entities and Significant Events from Online Daily News","date":"2008-11-02","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"diffrac-a-discriminative-and-flexible","title":"DIFFRAC: a discriminative and flexible framework for clustering","date":"2007-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"discriminative-k-means-for-clustering","title":"Discriminative K-means for Clustering","date":"2007-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"r-1-pca-rotational-invariant-l-1-norm","title":"R 1 -PCA: Rotational Invariant L 1 -norm Principal Component Analysis for Robust Subspace Factorization","date":"2006-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"image-segmentation-by-uniform-color","title":"Image Segmentation by Uniform Color Clustering Approach and Benchmark Results","date":"2005-06-03","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"image-segmentation-based-on-watershed-and","title":"Image Segmentation Based on Watershed and Edge Detection Techniques","date":"2005-02-13","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"calibrating-the-nonlinear-matter-power","title":"Calibrating the Nonlinear Matter Power Spectrum: Requirements for Future Weak Lensing Surveys","date":"2004-12-06","arxiv_id":"astro-ph/0412142","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-bit-of-progress-in-language-modeling","title":"A Bit of Progress in Language Modeling","date":"2001-08-09","arxiv_id":"cs/0108005","repositories_listed":0,"syntology":null}],"record_sha256":"064a958afb25b15c9c8e6d978f5e72822bdd1803d1cead752aa8610b40b0ba21","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}