{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:JCDK3SL6LHMKOAPBRLXHDSTLOY","short_pith_number":"pith:JCDK3SL6","canonical_record":{"source":{"id":"1709.05083","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-15T07:32:20Z","cross_cats_sorted":[],"title_canon_sha256":"15467965acc92be235708d17263dfb8dc56680ae77520dce1eac26e0c774a8a1","abstract_canon_sha256":"a0fb3b8f8c04ae533e8898a46c1bafe8e777a2ed8805b0991f30908e75493e2b"},"schema_version":"1.0"},"canonical_sha256":"4886adc97e59d8a701e18aee71ca6b76299c4f43bd3c04f0cc6bb8f98c10a650","source":{"kind":"arxiv","id":"1709.05083","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.05083","created_at":"2026-05-18T00:35:06Z"},{"alias_kind":"arxiv_version","alias_value":"1709.05083v1","created_at":"2026-05-18T00:35:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.05083","created_at":"2026-05-18T00:35:06Z"},{"alias_kind":"pith_short_12","alias_value":"JCDK3SL6LHMK","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_16","alias_value":"JCDK3SL6LHMKOAPB","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_8","alias_value":"JCDK3SL6","created_at":"2026-05-18T12:31:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:JCDK3SL6LHMKOAPBRLXHDSTLOY","target":"record","payload":{"canonical_record":{"source":{"id":"1709.05083","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-15T07:32:20Z","cross_cats_sorted":[],"title_canon_sha256":"15467965acc92be235708d17263dfb8dc56680ae77520dce1eac26e0c774a8a1","abstract_canon_sha256":"a0fb3b8f8c04ae533e8898a46c1bafe8e777a2ed8805b0991f30908e75493e2b"},"schema_version":"1.0"},"canonical_sha256":"4886adc97e59d8a701e18aee71ca6b76299c4f43bd3c04f0cc6bb8f98c10a650","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:35:06.745501Z","signature_b64":"L+y9UMbAqiO6OqAlbyKcyEMs++zs25Y7wJQIbthICP7NF7dCQnPLJuEcmS5MIFX3DpYsyUa0E2EPF5NOj2qGDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4886adc97e59d8a701e18aee71ca6b76299c4f43bd3c04f0cc6bb8f98c10a650","last_reissued_at":"2026-05-18T00:35:06.744917Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:35:06.744917Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1709.05083","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:35:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uom6LKmD13y8aTsFrfO8FegLkVo+QSW0I8YbWlT3TxpXzZ86Sgw/oHFKObsMhiDumxj7ASaNWL9EpZsvFWZUBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T06:16:40.948972Z"},"content_sha256":"b4dfce04a6d93ca7598bff2178aa57c68d7207e17836d855844cb14217f0d38c","schema_version":"1.0","event_id":"sha256:b4dfce04a6d93ca7598bff2178aa57c68d7207e17836d855844cb14217f0d38c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:JCDK3SL6LHMKOAPBRLXHDSTLOY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Robust Kernelized Multi-View Self-Representations for Clustering by Tensor Multi-Rank Minimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jinyan Liu, Wensheng Zhang, Yanyun Qu, Yuan Xie","submitted_at":"2017-09-15T07:32:20Z","abstract_excerpt":"Most recently, tensor-SVD is implemented on multi-view self-representation clustering and has achieved the promising results in many real-world applications such as face clustering, scene clustering and generic object clustering. However, tensor-SVD based multi-view self-representation clustering is proposed originally to solve the clustering problem in the multiple linear subspaces, leading to unsatisfactory results when dealing with the case of non-linear subspaces. To handle data clustering from the non-linear subspaces, a kernelization method is designed by mapping the data from the origin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.05083","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:35:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tyCDjrYFta8BjNpzyCfoyP2d1JNrJdLkIHJMAtHA4DJwSLoQbdhyhql6K8aAZQ2caO3Y12wl9/2DB6vkD5QBBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T06:16:40.949631Z"},"content_sha256":"4d3232d65b4e0718460ab9afa276dcb649fd073bc8c702a7bb8aae592ab68b69","schema_version":"1.0","event_id":"sha256:4d3232d65b4e0718460ab9afa276dcb649fd073bc8c702a7bb8aae592ab68b69"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JCDK3SL6LHMKOAPBRLXHDSTLOY/bundle.json","state_url":"https://pith.science/pith/JCDK3SL6LHMKOAPBRLXHDSTLOY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JCDK3SL6LHMKOAPBRLXHDSTLOY/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-04T06:16:40Z","links":{"resolver":"https://pith.science/pith/JCDK3SL6LHMKOAPBRLXHDSTLOY","bundle":"https://pith.science/pith/JCDK3SL6LHMKOAPBRLXHDSTLOY/bundle.json","state":"https://pith.science/pith/JCDK3SL6LHMKOAPBRLXHDSTLOY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JCDK3SL6LHMKOAPBRLXHDSTLOY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:JCDK3SL6LHMKOAPBRLXHDSTLOY","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"a0fb3b8f8c04ae533e8898a46c1bafe8e777a2ed8805b0991f30908e75493e2b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-15T07:32:20Z","title_canon_sha256":"15467965acc92be235708d17263dfb8dc56680ae77520dce1eac26e0c774a8a1"},"schema_version":"1.0","source":{"id":"1709.05083","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.05083","created_at":"2026-05-18T00:35:06Z"},{"alias_kind":"arxiv_version","alias_value":"1709.05083v1","created_at":"2026-05-18T00:35:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.05083","created_at":"2026-05-18T00:35:06Z"},{"alias_kind":"pith_short_12","alias_value":"JCDK3SL6LHMK","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_16","alias_value":"JCDK3SL6LHMKOAPB","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_8","alias_value":"JCDK3SL6","created_at":"2026-05-18T12:31:21Z"}],"graph_snapshots":[{"event_id":"sha256:4d3232d65b4e0718460ab9afa276dcb649fd073bc8c702a7bb8aae592ab68b69","target":"graph","created_at":"2026-05-18T00:35:06Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Most recently, tensor-SVD is implemented on multi-view self-representation clustering and has achieved the promising results in many real-world applications such as face clustering, scene clustering and generic object clustering. However, tensor-SVD based multi-view self-representation clustering is proposed originally to solve the clustering problem in the multiple linear subspaces, leading to unsatisfactory results when dealing with the case of non-linear subspaces. To handle data clustering from the non-linear subspaces, a kernelization method is designed by mapping the data from the origin","authors_text":"Jinyan Liu, Wensheng Zhang, Yanyun Qu, Yuan Xie","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-15T07:32:20Z","title":"Robust Kernelized Multi-View Self-Representations for Clustering by Tensor Multi-Rank Minimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.05083","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:b4dfce04a6d93ca7598bff2178aa57c68d7207e17836d855844cb14217f0d38c","target":"record","created_at":"2026-05-18T00:35:06Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"a0fb3b8f8c04ae533e8898a46c1bafe8e777a2ed8805b0991f30908e75493e2b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-15T07:32:20Z","title_canon_sha256":"15467965acc92be235708d17263dfb8dc56680ae77520dce1eac26e0c774a8a1"},"schema_version":"1.0","source":{"id":"1709.05083","kind":"arxiv","version":1}},"canonical_sha256":"4886adc97e59d8a701e18aee71ca6b76299c4f43bd3c04f0cc6bb8f98c10a650","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4886adc97e59d8a701e18aee71ca6b76299c4f43bd3c04f0cc6bb8f98c10a650","first_computed_at":"2026-05-18T00:35:06.744917Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:35:06.744917Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"L+y9UMbAqiO6OqAlbyKcyEMs++zs25Y7wJQIbthICP7NF7dCQnPLJuEcmS5MIFX3DpYsyUa0E2EPF5NOj2qGDg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:35:06.745501Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.05083","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b4dfce04a6d93ca7598bff2178aa57c68d7207e17836d855844cb14217f0d38c","sha256:4d3232d65b4e0718460ab9afa276dcb649fd073bc8c702a7bb8aae592ab68b69"],"state_sha256":"b49c252440a92b6c4d7cad16ce8087c7eb2f0d39c149625a5ba5b0607b8f5a7d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KslRtaahqjYxakrdtxSqSGfyBtWgqHR63bqKGymrkAbfrhjiNFdBs1ydQkrMtfcXxxT0pLU2PM6QbvPJ8Io5AA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T06:16:40.952696Z","bundle_sha256":"ba26735290171737d9215fbb4f9e6df3a03bdf2398b10a176aa5dbbebcceb763"}}