{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:2MANKIMRI2HVF3V2JNITZLXW5N","short_pith_number":"pith:2MANKIMR","schema_version":"1.0","canonical_sha256":"d300d52191468f52eeba4b513caef6eb49fe9a8e98e03da1f28e22a7b774c1ea","source":{"kind":"arxiv","id":"1605.06886","version":2},"attestation_state":"computed","paper":{"title":"Stochastic Patching Process","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.AI","authors_text":"Bin Li, Fang Chen, Xuhui Fan, Yang Wang, Yi Wang","submitted_at":"2016-05-23T03:43:01Z","abstract_excerpt":"Stochastic partition models tailor a product space into a number of rectangular regions such that the data within each region exhibit certain types of homogeneity. Due to constraints of partition strategy, existing models may cause unnecessary dissections in sparse regions when fitting data in dense regions. To alleviate this limitation, we propose a parsimonious partition model, named Stochastic Patching Process (SPP), to deal with multi-dimensional arrays. SPP adopts an \"enclosing\" strategy to attach rectangular patches to dense regions. SPP is self-consistent such that it can be extended to"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1605.06886","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2016-05-23T03:43:01Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"be1d552688ddb4371e36b238e6eb239c6065479a887d3210a9e62164c86007d2","abstract_canon_sha256":"000129a26d624668dc399852f24203500e41112b17a17f740f065cb6526bb0a6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:50:01.277540Z","signature_b64":"n2Z5kBfQTpGwNMcJ+6WeYdlzIA92Wwq/vck1qt5DKs6guN1KtOdbTCj5J1iwc9f02CBurxVFR+nNGH1nxlcCDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d300d52191468f52eeba4b513caef6eb49fe9a8e98e03da1f28e22a7b774c1ea","last_reissued_at":"2026-05-18T00:50:01.276850Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:50:01.276850Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Stochastic Patching Process","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.AI","authors_text":"Bin Li, Fang Chen, Xuhui Fan, Yang Wang, Yi Wang","submitted_at":"2016-05-23T03:43:01Z","abstract_excerpt":"Stochastic partition models tailor a product space into a number of rectangular regions such that the data within each region exhibit certain types of homogeneity. Due to constraints of partition strategy, existing models may cause unnecessary dissections in sparse regions when fitting data in dense regions. To alleviate this limitation, we propose a parsimonious partition model, named Stochastic Patching Process (SPP), to deal with multi-dimensional arrays. SPP adopts an \"enclosing\" strategy to attach rectangular patches to dense regions. SPP is self-consistent such that it can be extended to"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1605.06886","kind":"arxiv","version":2},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1605.06886","created_at":"2026-05-18T00:50:01.276946+00:00"},{"alias_kind":"arxiv_version","alias_value":"1605.06886v2","created_at":"2026-05-18T00:50:01.276946+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1605.06886","created_at":"2026-05-18T00:50:01.276946+00:00"},{"alias_kind":"pith_short_12","alias_value":"2MANKIMRI2HV","created_at":"2026-05-18T12:29:55.572404+00:00"},{"alias_kind":"pith_short_16","alias_value":"2MANKIMRI2HVF3V2","created_at":"2026-05-18T12:29:55.572404+00:00"},{"alias_kind":"pith_short_8","alias_value":"2MANKIMR","created_at":"2026-05-18T12:29:55.572404+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/2MANKIMRI2HVF3V2JNITZLXW5N","json":"https://pith.science/pith/2MANKIMRI2HVF3V2JNITZLXW5N.json","graph_json":"https://pith.science/api/pith-number/2MANKIMRI2HVF3V2JNITZLXW5N/graph.json","events_json":"https://pith.science/api/pith-number/2MANKIMRI2HVF3V2JNITZLXW5N/events.json","paper":"https://pith.science/paper/2MANKIMR"},"agent_actions":{"view_html":"https://pith.science/pith/2MANKIMRI2HVF3V2JNITZLXW5N","download_json":"https://pith.science/pith/2MANKIMRI2HVF3V2JNITZLXW5N.json","view_paper":"https://pith.science/paper/2MANKIMR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1605.06886&json=true","fetch_graph":"https://pith.science/api/pith-number/2MANKIMRI2HVF3V2JNITZLXW5N/graph.json","fetch_events":"https://pith.science/api/pith-number/2MANKIMRI2HVF3V2JNITZLXW5N/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2MANKIMRI2HVF3V2JNITZLXW5N/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2MANKIMRI2HVF3V2JNITZLXW5N/action/storage_attestation","attest_author":"https://pith.science/pith/2MANKIMRI2HVF3V2JNITZLXW5N/action/author_attestation","sign_citation":"https://pith.science/pith/2MANKIMRI2HVF3V2JNITZLXW5N/action/citation_signature","submit_replication":"https://pith.science/pith/2MANKIMRI2HVF3V2JNITZLXW5N/action/replication_record"}},"created_at":"2026-05-18T00:50:01.276946+00:00","updated_at":"2026-05-18T00:50:01.276946+00:00"}