{"as_of":"2026-08-16T16:23:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a25b71c7936d62c2b9e926b4bb3774108616ec3a429296802c26214f554dc55e","coverage":[{"denominator":30,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":30,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T15:42:47.042537Z","state":"measured"},{"denominator":30,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":30,"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/1908.00683/citation-record","integrity":"/paper/1908.00683/integrity","json":"/paper/1908.00683/citation-record.json","paper":"/paper/1908.00683"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T15:42:47.467174Z","title":"Towards K-m eans-friendly spaces: Simul- taneous deep learning and clustering,","venue":null,"work_id":"c878e850-df23-4317-8b84-d63f5cffceac","year":2017},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.810680Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:7497001b4a599cd21f56d5eb55db6c3c2342a79557da09b1191b129c16fb7a5f","observation_id":"3deb52c6-68f7-48fd-8a6d-785e8129a87a","resolution":{"observed_at":"2026-08-14T15:42:47.471442Z","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":"2026-08-14T15:42:47.453166Z","title":"A cluster-then-label semi-supervised learning approach for pathology image classiﬁcation,","venue":null,"work_id":"b7fee844-d14d-413c-9107-960d6d0cf40f","year":2018},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.815522Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:63257a19385d0fa25162f8b228e0a08158d68b8a7d4919400b35b36a0e014f84","observation_id":"9408be45-6a08-4290-80d0-7deed895753a","resolution":{"observed_at":"2026-08-14T15:42:47.457631Z","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":"2026-08-14T15:42:46.820050Z","title":"Subspace clustering,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.820050Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:c13d8006e1450ceded51e52790295d4ef6b79023503c4ed8bc7b3c38dccb3fdf","observation_id":"a154453c-3399-405b-af7c-28fe4097d561","resolution":{"observed_at":"2026-08-14T15:42:46.820050Z","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":"2026-08-14T15:42:47.429373Z","title":"A geometric analysis of subspace clustering with outliers,","venue":null,"work_id":"bde8733d-d962-409d-a123-8cc5935b3eae","year":2012},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.823929Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:eee16f8c85f252141c83df464b3b89b0b7a12b7e145e665fb16066e6435651c2","observation_id":"3ee0a860-6218-4d6c-90f6-125cacc6b55d","resolution":{"observed_at":"2026-08-14T15:42:47.435167Z","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":"2026-08-14T15:42:47.416381Z","title":"Robus t subspace clustering,","venue":null,"work_id":"e9b3cbeb-3769-45aa-85e4-11d1451273ea","year":2014},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.828390Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:1bfd8e90db86058512564a060eff83813acc620ac7b36e4984f55e7537c34109","observation_id":"67eab6f2-20f3-4284-aaf0-a0357b356b9c","resolution":{"observed_at":"2026-08-14T15:42:47.420404Z","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":"2026-08-14T15:42:47.403819Z","title":"Subspace clustering of hi gh-dimensional data: a predictive approach,","venue":null,"work_id":"e9afac60-9ef1-40da-91c3-f759c9c6222b","year":2014},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.832558Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:4a3a42be8b79d61edcf280af7ae82a5a68c39cda1bdc711c7fbf472e80eaa73f","observation_id":"65729cf0-32c2-43a8-832f-6c5dbb46a53d","resolution":{"observed_at":"2026-08-14T15:42:47.407878Z","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":"2026-08-14T15:42:47.390443Z","title":"Sparse subspace clustering: Algorithm, theory, and applica- tions,","venue":null,"work_id":"30339670-08ab-46ab-a434-fa2cfdc19cb8","year":2013},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.837000Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:b2d853bdfe57fe6cc21602e82ec32e8b453c4ed6ddb7810b7b91d8d808c32e5a","observation_id":"d0cf8d0c-d6ee-4050-908d-b7d89b22e80f","resolution":{"observed_at":"2026-08-14T15:42:47.395187Z","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":"2026-08-14T15:42:47.377543Z","title":"Sparse subspace clustering,","venue":null,"work_id":"838c3760-afa4-42bd-8da7-e49954fbc7c0","year":2009},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.840993Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:08bbd81959f01b9a565b46cc7cef4be8466c2ea7d23ae46398526e98591531c6","observation_id":"e09aa52b-12c9-45ba-8611-23ed04cdceef","resolution":{"observed_at":"2026-08-14T15:42:47.381902Z","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":"2026-08-14T15:42:47.363874Z","title":"A tutorial on spectral clustering,","venue":null,"work_id":"069f41a8-9775-436d-b8a6-541f202940dd","year":2007},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.845111Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:f4f60c1fac2c09c4b11b3a6a97845196ad54d766cc341820e9f5934d50ecd4a9","observation_id":"fb88ecde-0816-4c6b-8b96-07c846f7c746","resolution":{"observed_at":"2026-08-14T15:42:47.368127Z","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":"2026-08-14T15:42:47.349915Z","title":"Fast approximate spect ral clustering,","venue":null,"work_id":"60129965-6ab6-4ab1-a587-e1e619ecd5c7","year":2009},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.849518Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:ae2e62e7f57534b502106765746f92e35749055a2de1504398333cca4e63c18b","observation_id":"ee9de9dc-de0c-48a4-87e3-0d8ac1b768d0","resolution":{"observed_at":"2026-08-14T15:42:47.354440Z","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":"2026-08-14T15:42:47.336101Z","title":"Learning dee p representations for graph clustering,","venue":null,"work_id":"0bb8c4d7-42a8-4462-802f-f9c1d7c365c1","year":2014},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.853380Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:bdc3a3794a1c833bdfa12cc46e19ea0847d447bb334f8040b92577f1f70dd38c","observation_id":"d505aa6a-9f0d-453a-845a-81e8862ad72e","resolution":{"observed_at":"2026-08-14T15:42:47.340872Z","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":"2026-08-14T15:42:47.322014Z","title":"A randomized app roach to eﬃcient kernel clustering,","venue":null,"work_id":"9416a92f-f72d-444e-892e-329109b9ce38","year":2016},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.857269Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:f109a9075eb7191211673332181c10e7fb1d582b4dc0aa0a8cd8793d54b30350","observation_id":"6fb7bb04-41c5-4719-858e-55eb0ddba104","resolution":{"observed_at":"2026-08-14T15:42:47.326542Z","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":"2026-08-14T15:42:47.308244Z","title":"Spe ctral clustering of large- scale data by directly solving normalized cut,","venue":null,"work_id":"c62632cc-dfbe-41b5-929a-5bab95cce4b0","year":2018},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.861512Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:85987178c23e4b0ba1dd18bd6112b9161de6f59d9e237b563b157dc775a3a656","observation_id":"f7c623ac-5b67-4849-8f9e-b6485d4e9f19","resolution":{"observed_at":"2026-08-14T15:42:47.312746Z","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":"2026-08-14T15:42:47.294573Z","title":"A simple and fast algorithm for K-med oids clustering,","venue":null,"work_id":"2a40a2d6-1169-4b5d-9714-b32fbf3f9719","year":2009},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.865883Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:d78d9f125ade51f2877973c8b8fcd9cd5a837f874cdd985f87af97f016ce32d7","observation_id":"7007c5fc-aee1-43d8-b1c6-ddc392f14de6","resolution":{"observed_at":"2026-08-14T15:42:47.299244Z","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":"2026-08-14T15:42:47.281254Z","title":"Sketched subspace clu stering,","venue":null,"work_id":"221c6e4e-dcc0-482a-ab91-a449494931ff","year":2018},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.869656Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:d2e130e4cca6326aa61d34c97cfbca4b888f5255954fb18a792110a1335d2f22","observation_id":"eb85d2a1-ad1b-4f68-81a4-265effbcf299","resolution":{"observed_at":"2026-08-14T15:42:47.285587Z","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":"2026-08-14T15:42:47.268016Z","title":"Preconditioned data sparsiﬁcation for big data with applications to PCA and K-means,","venue":null,"work_id":"026721a8-dc7b-459e-8c54-36afbc05b7b1","year":2017},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.873877Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:3cb1b8960573cf755681b3a4f831a45928bd4de2fe3f7454321d7962440f9ba1","observation_id":"b2f6a042-c54f-40cd-aa84-04d350c8bd1d","resolution":{"observed_at":"2026-08-14T15:42:47.272167Z","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":"2026-08-14T15:42:47.254401Z","title":"Distributed optimization and statistical learning via the alternating direction method of multipliers,","venue":null,"work_id":"b669287d-8649-4567-91d7-e1f89e9cc3d3","year":2011},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.878371Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:106a2d51fe4b0d439db0220b2ec20b30d6d22a14394201ff1da174a2c5d5825f","observation_id":"c000c608-eada-48e7-9cea-aae87e32f6ca","resolution":{"observed_at":"2026-08-14T15:42:47.258968Z","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":{"arxiv_id":"1804.06291","last_updated":"2020-02-20T03:19:41Z","snapshot_observed_at":"2026-08-14T19:25:02.601048Z","submitted_at":"2018-04-17T14:41:52Z","title":"Efficient Solvers for Sparse Subspace Clustering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.06291","snapshot_observed_at":"2026-08-14T15:42:46.882701Z","title":"Eﬃcient solvers for sparse subspace clustering,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.882701Z"},"links":{"cited_paper":"/paper/1804.06291","citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:d75ae01a0213c7af5e380ef8994c8a48b49dc80c51745a00d533a7bd35f619d4","observation_id":"3aa9dc57-6780-4f96-b95d-dfc992223479","resolution":{"observed_at":"2026-08-14T15:42:46.882701Z","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":"2026-08-14T15:42:47.241779Z","title":"Scalable sparse subs pace clustering by orthogonal matching pursuit,","venue":null,"work_id":"b335e23e-c73c-4e39-b7f2-c357c97212d8","year":2016},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.887769Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:8d0d943f0ad99ccb424298241a957aac32cb3dd1696e52418930db657e70882d","observation_id":"ccc1435f-34fe-4b62-8131-830e1774ba88","resolution":{"observed_at":"2026-08-14T15:42:47.245864Z","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":"2026-08-14T15:42:47.228650Z","title":"A scalable exem plar-based subspace clustering algorithm for class-imbalanced data,","venue":null,"work_id":"297b57db-cc03-48f1-95c9-677cc4bd6fbe","year":2018},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:46.891939Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:7fd94f950cfcf46613c6304f2d4dd1300c62bc4f8154b4075ac662983fb996d0","observation_id":"d4b447fd-e6ec-4a55-ae9d-b0e626002a4b","resolution":{"observed_at":"2026-08-14T15:42:47.233078Z","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":"2026-08-14T15:42:47.214752Z","title":"Scalable K-means cl ustering via lightweight coresets,","venue":null,"work_id":"2436fb74-5ef2-40cc-88dc-147504e568e5","year":2018},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:47.001529Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:9366cb6ae5a74b2a8fc811f7e0dae794ce1bf4e8dcc66f65553a1694b03ecd68","observation_id":"9154c64f-5ea0-4f0f-a06a-083c136a44b9","resolution":{"observed_at":"2026-08-14T15:42:47.219259Z","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":"2026-08-14T15:42:47.200489Z","title":"Train ing Gaussian mixture models at scale via coresets,","venue":null,"work_id":"9f293172-c848-4ca9-af5a-4d79f1eb6d2a","year":2018},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:47.006395Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:09b019303a93a4733a2a7d2b4d03c2b1835ef68e87ad22a516e01b541f7178d8","observation_id":"f7d7456a-d6f0-478b-8b02-5468f0f062f7","resolution":{"observed_at":"2026-08-14T15:42:47.205140Z","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":"2026-08-14T15:42:47.186167Z","title":"Rando mized clustered Nystr¨ om for large- scale kernel machines,","venue":null,"work_id":"42400415-f34b-47d1-a68c-27263fe1c2ff","year":2018},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:47.011081Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:6fffdb4b03d6a91501c599b3848091779e239f9a5f582101c771649821dd8ed2","observation_id":"fbd4ec57-311e-4577-aa8a-0abe007423ac","resolution":{"observed_at":"2026-08-14T15:42:47.190852Z","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":"2026-08-14T15:42:47.171654Z","title":"Finding structu re with randomness: Probabilis- tic algorithms for constructing approximate matrix decomp ositions,","venue":null,"work_id":"126065f3-885e-428b-a6dc-a353e3c06b55","year":2011},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:47.015358Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:898c8401b3c07a476923033e3e6b2ead39ac872e7a5aa90cef636a33dc897172","observation_id":"490018d1-2a2c-40e6-85da-c600ee51b210","resolution":{"observed_at":"2026-08-14T15:42:47.176492Z","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":"2026-08-14T15:42:47.156805Z","title":"Sparse modeling for im age and vision processing,","venue":null,"work_id":"0e110b8d-eea2-4ede-b459-7199511aca63","year":2014},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:47.019573Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:145ac16e865b307da812fa459cf94c53eb320dd0fe3448633609c36c89daee40","observation_id":"8218eafe-ada4-4979-8b04-fc4731833d38","resolution":{"observed_at":"2026-08-14T15:42:47.161842Z","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":"2026-08-14T15:42:47.142540Z","title":"Gradient- based learning applied to docu- ment recognition,","venue":null,"work_id":"c22be029-072a-4099-a888-f1c6c058a012","year":1998},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:47.024132Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:63b2ed9f7cae02ff165c74a48ea36b0209af220cc6e176f164bac211ae7f33ea","observation_id":"742af795-f6d4-4e5a-8012-5690f99dbedb","resolution":{"observed_at":"2026-08-14T15:42:47.146674Z","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":"2026-08-14T15:42:47.128548Z","title":"Invariant scattering convolut ion networks,","venue":null,"work_id":"5bb03524-a9bf-4022-ac79-d48efedfa961","year":2013},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:47.028591Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:61d99a5f9b1a4dcd2cd53577a73eeeab37a330968e55ff503b8e925ec43ef709","observation_id":"51d06ee7-c34f-4953-97a1-02ee1ca122c9","resolution":{"observed_at":"2026-08-14T15:42:47.132647Z","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":"2026-08-14T15:42:47.115254Z","title":"Memory and compu tation eﬃcient PCA via very sparse random projections,","venue":null,"work_id":"49d3238b-23a4-4be2-b074-4517d220bed9","year":2014},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:47.033184Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:8b4490746e5a118f8b017d50fea896636bb122802e25485eb6d666d0c8b8b881","observation_id":"9e2702ee-56c5-49a9-bdf7-5df30e7a16a9","resolution":{"observed_at":"2026-08-14T15:42:47.119389Z","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":"2026-08-14T15:42:47.101949Z","title":"Dimensiona lity-reduced subspace clustering,","venue":null,"work_id":"37035f2f-c6b2-4ad9-b8e6-0030f6fec137","year":2017},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:47.037935Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:4ed46e64655f153e413372e3d1104c58f688eadd8b89743d2ebd9f8d0805cd13","observation_id":"2bf3f7a4-0433-482d-a7e5-9b31b5648064","resolution":{"observed_at":"2026-08-14T15:42:47.106110Z","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":"2026-08-14T15:42:47.086740Z","title":"A general framework for understanding compressed sub- space clustering algorithms,","venue":null,"work_id":"46f7af74-1a6a-41e3-ae17-3a227010b61b","year":2018},"citing_paper":{"arxiv_id":"1908.00683","last_updated":"2019-08-02T02:39:40Z","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T15:42:47.042537Z"},"links":{"citing_paper":"/paper/1908.00683"},"observation_digest":"sha256:e93b12f4889f61825079d3d8b434b95de8f7218d271b8f880b3bb2d4fadb732a","observation_id":"a6cf53eb-2a05-4d02-9044-420637262266","resolution":{"observed_at":"2026-08-14T15:42:47.092674Z","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":"1908.00683","last_updated":"2019-08-02T02:39:40Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T09:54:16.245507Z","submitted_at":"2019-08-02T02:39:40Z","title":"Large-Scale Sparse Subspace Clustering Using Landmarks"},"reference_resolution":{"displayed":30,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":2,"verified_exact":0,"verified_fuzzy":28},"total_outbound_references":30},"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 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:1908.00683."}