{"as_of":"2026-08-16T18:44:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c1a6da683a9fd22d808900372d737e3cde47ac3264ddc1e4b94f8bee29266341","coverage":[{"denominator":20,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":20,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T11:39:01.317885Z","state":"measured"},{"denominator":20,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":20,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/1908.08713/citation-record","integrity":"/paper/1908.08713/integrity","json":"/paper/1908.08713/citation-record.json","paper":"/paper/1908.08713"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.674765Z","title":"How slow is the k-means method? InSymposium on Computational Geometry, pages 1–10, 2006","venue":null,"work_id":"2982540d-83e8-4718-a7c7-e653dfd3935c","year":2006},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.224281Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:10ba73795e0744f96c45d41df91dc9733cf4b55123b32e8ef2e611c880056cae","observation_id":"0526da4d-6296-4278-9b00-754b663fdf20","resolution":{"observed_at":"2026-08-14T11:39:01.679995Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.658007Z","title":"Proximal alternating linearized minimization or nonconvex and nonsmooth problems.Mathematical Programming, 146(1-2):459–494, 2014","venue":null,"work_id":"03338861-ea3c-4bfe-b284-c290d1463cd5","year":2014},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.229750Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:1e82a66039571f2987b772f2c4b24090265b718282f498ac84c3a3173e456dde","observation_id":"ad7a6787-08b6-44be-abbb-76dea7612e77","resolution":{"observed_at":"2026-08-14T11:39:01.663452Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.641150Z","title":"Randomized dimen- sionality reduction fork-means clustering","venue":null,"work_id":"ecc70ff7-1e73-4795-985d-2ac04fec44de","year":2014},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.234845Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:d45b74e8e83d1c25a8f99f029af568f16ac94b61c336332fa680d3f782f8fea7","observation_id":"7461a601-d9a2-4d26-87e8-62f0381a6e57","resolution":{"observed_at":"2026-08-14T11:39:01.646719Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.622443Z","title":"Revisiting the nyström method for improved large-scale machine learning","venue":null,"work_id":"ba95935d-9d2c-4350-8bf6-99862e81092a","year":2016},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.239925Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:879442e56ec1b351d661036ffce95beb95bbd16f1a3a686419e86d3e224e0f14","observation_id":"8fb917eb-df2e-41a2-87e0-41a0d7fed577","resolution":{"observed_at":"2026-08-14T11:39:01.629651Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.601650Z","title":"Algorithm as 136: A k-means clustering algorithm.Journal of the Royal Statistical Society","venue":null,"work_id":"bae564c2-2666-40da-9e86-bbf9b68808f1","year":1979},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.244852Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:826905cc09fff26148528709be49071d0fb88e23349dbc586a376ee55126b8a1","observation_id":"e4915c75-c14b-4047-8303-124b0b1e0c76","resolution":{"observed_at":"2026-08-14T11:39:01.610468Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.249861Z","title":"Data clustering: 50 years beyond k-means.Pattern recognition letters, 31(8):651–666, 2010","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.249861Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:0152094e182f5d1d3b38d801cf40b033889a80f79db63b3e6cb37b7b9d5fe552","observation_id":"315ba5e6-7063-4238-93cc-975f2676ff60","resolution":{"observed_at":"2026-08-14T11:39:01.249861Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.573054Z","title":"Sampling methods for the nyström method","venue":null,"work_id":"acf18565-30d2-4d6d-841a-98fc0e81294e","year":2012},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.256467Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:c6dc8fa5a711248a42246e79f1ad1b6e34f3c279b3d0017ecf4634dd0cc5de2d","observation_id":"b86a597a-d189-48d7-a650-2b59e62fe950","resolution":{"observed_at":"2026-08-14T11:39:01.578431Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.557779Z","title":"Fastfood—approximating kernel expansions in loglinear time","venue":null,"work_id":"ea71fe2e-3ee6-4035-9316-0589af2f34a3","year":2013},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.261062Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:333ca8ab5867b500c62dfcd23a9fe8006a82c0b7d5b553807c4cd8d6d35af776","observation_id":"c5f70ef9-0ec3-4f70-9621-4daa2f7b5330","resolution":{"observed_at":"2026-08-14T11:39:01.562658Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.542620Z","title":"Flexible multilayer sparse approximations of matrices and applications","venue":null,"work_id":"39ac8925-8fa6-4957-9b94-e007fd262d78","year":2016},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.265527Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:bf14bd0a7ca588f5ddd30153f397abc4430df3e907f1885d7ba4d1b15cdda73d","observation_id":"fb6f9df8-05db-459e-ab4b-e4a3e562969a","resolution":{"observed_at":"2026-08-14T11:39:01.547284Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.526101Z","title":"MNIST handwritten digit database, 2010","venue":null,"work_id":"a8e2774f-8535-4145-a294-e7a4089f9fb7","year":2010},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.270318Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:e2eca1670e3dc2e697551c4838bc11b357f17c9b828bbb16559cfb103c146caf","observation_id":"db9454ee-b19e-45ce-9ff8-d6b1fbb4d08c","resolution":{"observed_at":"2026-08-14T11:39:01.531250Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.508404Z","title":"Sparse embeddedk-means clustering","venue":null,"work_id":"dab49340-8416-4498-a60a-dd54c3aa35f9","year":2017},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.275025Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:10aabebc7eb004daf28c2a02af6050e4463c03622cf2b6e385a49b73a1cbba2c","observation_id":"f41e01a9-442d-4481-99c4-296915e2bf1d","resolution":{"observed_at":"2026-08-14T11:39:01.513604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.489904Z","title":"The Linear Complexity of Computation.Journal of the ACM, 22(2):184–194, April 1975","venue":null,"work_id":"8f324092-85a8-42a7-ae4c-25af8506eaae","year":1975},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.279790Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:a344ffaebbc9a7398301950e9c87bf5f01a88db24d6c4c20a6aa40f8a86ded6e","observation_id":"d996ca0b-524c-48a4-b668-134d968b4287","resolution":{"observed_at":"2026-08-14T11:39:01.496045Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.473271Z","title":"Scalable nearest neighbor algorithms for high dimensional data.IEEE transactions on pattern analysis and machine intelligence, 36(11):2227–2240, 2014","venue":null,"work_id":"9389589f-4ced-41a8-9071-c0b1504bfc38","year":2014},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.284702Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:9172093439d56895997d5a0c66f404f089558ccce37d0282cead79252fbbea49","observation_id":"fce8a382-93c5-499c-9f7c-cde8085f0e77","resolution":{"observed_at":"2026-08-14T11:39:01.478460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.458081Z","title":"Recursive sampling for the nystrom method","venue":null,"work_id":"f8ad6536-8610-4a18-93fb-3fbc24034915","year":2017},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.289483Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:2352fb6b5c6903ece13689654ba85d17d2fc7dbe32c5403eff3115e1fbc33e7b","observation_id":"3dee5a79-c4e9-4d03-8d5e-31b95d03507f","resolution":{"observed_at":"2026-08-14T11:39:01.462825Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.440562Z","title":"Pedregosa, G","venue":null,"work_id":"2b8cc7b6-55cf-4ec7-a2a4-73f621d646c8","year":2011},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.294600Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:44c2559400a958025945000d5be02231a448f14acbcacf6d83373d5b02a41fbe","observation_id":"fd336a68-6d31-4725-a708-ad576cccbe21","resolution":{"observed_at":"2026-08-14T11:39:01.446487Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.420143Z","title":"Back to the future: Radial basis function networks revisited","venue":null,"work_id":"9596f98a-b140-4c87-8917-d21e9598214a","year":2016},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.299232Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:b3336fdf6d39416d7e80be9d32f829b993fee4acbba9e9ecc62b83f1a1745c4f","observation_id":"5c8a1e1f-a88a-4500-99a6-214d9725f413","resolution":{"observed_at":"2026-08-14T11:39:01.425146Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.402846Z","title":"Web-scale k-means clustering","venue":null,"work_id":"27ae9794-927c-4fdd-b7c6-e9b0a1d70872","year":2010},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.304044Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:a22e893d09e113c6fce2e8fc7e7d38bda447103994a42f7b09c8148b65d3be2d","observation_id":"89ed7943-6d3c-4ce0-b8fe-961d19c6a090","resolution":{"observed_at":"2026-08-14T11:39:01.408869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.386441Z","title":"Compressed k-means for large-scale clustering","venue":null,"work_id":"9289d827-eeb1-4190-9eb3-b493263349c3","year":2017},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.308522Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:ec8615b4e338208a8e98adbe4f7bf5f01fff79def0f20b487e32caee036dd82d","observation_id":"4814bf92-43e3-44e0-ab02-163e5ce3911d","resolution":{"observed_at":"2026-08-14T11:39:01.391576Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.368617Z","title":"Computationally eﬃcient nyström approximation using fast transforms","venue":null,"work_id":"8673ed82-fa6a-441c-bf5b-b9f737a7594b","year":2016},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.313291Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:9e6029ee6235ba6b478e1566e04cdc13d5c781e48301032d418ed9ce828d6e69","observation_id":"36950cf4-fcc1-4ba2-b1bc-4b69f74cf17d","resolution":{"observed_at":"2026-08-14T11:39:01.374622Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:39:01.349857Z","title":"Local network community detection with continuous optimization of conductance and weighted kernel k-means.The Journal of Machine Learning Research, 17(1):5148–5175, 2016","venue":null,"work_id":"4c2e828f-4024-4cb9-ba77-a7586de7f107","year":2016},"citing_paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T11:39:01.317885Z"},"links":{"citing_paper":"/paper/1908.08713"},"observation_digest":"sha256:dab787f810c76099377dda6ba28a1dcd08ab4eaed8cf6ca40364304baef57ea3","observation_id":"ec6ce5e2-12af-4759-8b9f-2cb5aa72da16","resolution":{"observed_at":"2026-08-14T11:39:01.357676Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.08713","last_updated":"2019-08-23T08:20:53Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-14T11:29:13.007288Z","submitted_at":"2019-08-23T08:20:53Z","title":"QuicK-means: Acceleration of K-means by learning a fast transform"},"reference_resolution":{"displayed":20,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":0,"verified_fuzzy":19},"total_outbound_references":20},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:1908.08713."}