{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:TM4JZCDW63SIDLVMRXGI2AN7AS","short_pith_number":"pith:TM4JZCDW","canonical_record":{"source":{"id":"1708.04403","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-08-15T06:00:33Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"d2986faf855db1d5d3cbced5b9f5cb57db87bc51ed421b0052382a0eb05f64a8","abstract_canon_sha256":"17b9b0720fd2ba414767e91ce2f0a1208141f900679e6bb6b588da73127cdf4f"},"schema_version":"1.0"},"canonical_sha256":"9b389c8876f6e481aeac8dcc8d01bf048a2c9581cd3f1d9cdbfc268b52efc157","source":{"kind":"arxiv","id":"1708.04403","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.04403","created_at":"2026-05-18T00:37:59Z"},{"alias_kind":"arxiv_version","alias_value":"1708.04403v1","created_at":"2026-05-18T00:37:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.04403","created_at":"2026-05-18T00:37:59Z"},{"alias_kind":"pith_short_12","alias_value":"TM4JZCDW63SI","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"TM4JZCDW63SIDLVM","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"TM4JZCDW","created_at":"2026-05-18T12:31:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:TM4JZCDW63SIDLVMRXGI2AN7AS","target":"record","payload":{"canonical_record":{"source":{"id":"1708.04403","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-08-15T06:00:33Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"d2986faf855db1d5d3cbced5b9f5cb57db87bc51ed421b0052382a0eb05f64a8","abstract_canon_sha256":"17b9b0720fd2ba414767e91ce2f0a1208141f900679e6bb6b588da73127cdf4f"},"schema_version":"1.0"},"canonical_sha256":"9b389c8876f6e481aeac8dcc8d01bf048a2c9581cd3f1d9cdbfc268b52efc157","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:37:59.404005Z","signature_b64":"Znu3ctk5Q6Owvrd4ym69QClLwOlhBviceR1LU7fZpsrFCwMCAnmNwb1aURqndjr0WWAvrvpfCI1Hpwqg61n/Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9b389c8876f6e481aeac8dcc8d01bf048a2c9581cd3f1d9cdbfc268b52efc157","last_reissued_at":"2026-05-18T00:37:59.403378Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:37:59.403378Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1708.04403","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":"2026-05-18T00:37:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kFoDL+DbCCgazByk/VaKTUsRkRwO0UPEaOOn8Sk6fboeTkZ79Ob5NHmRK2r5c3aoCP2KjUqaUooOhA/iXd/tBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T04:31:09.419811Z"},"content_sha256":"3efe74202076eebc0d83a5f75d2056342fd9939bbbe4fafebf371c5df3ac8e4d","schema_version":"1.0","event_id":"sha256:3efe74202076eebc0d83a5f75d2056342fd9939bbbe4fafebf371c5df3ac8e4d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:TM4JZCDW63SIDLVMRXGI2AN7AS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Theoretical Foundation of Co-Training and Disagreement-Based Algorithms","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"cs.LG","authors_text":"Wei Wang, Zhi-Hua Zhou","submitted_at":"2017-08-15T06:00:33Z","abstract_excerpt":"Disagreement-based approaches generate multiple classifiers and exploit the disagreement among them with unlabeled data to improve learning performance. Co-training is a representative paradigm of them, which trains two classifiers separately on two sufficient and redundant views; while for the applications where there is only one view, several successful variants of co-training with two different classifiers on single-view data instead of two views have been proposed. For these disagreement-based approaches, there are several important issues which still are unsolved, in this article we prese"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.04403","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":"2026-05-18T00:37:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GICO4hjKxxCJ9cO1ruD0K3yGfgdJMxZzRCyfem+CuT43yOW5EdbIctfN9vEwfDSj1YPOtqTLe0CTyNk9g9+3BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T04:31:09.420930Z"},"content_sha256":"4d4cf4e19a89a564337425b5ba33f6437984bbe8470c50fe4ae8e80ed85576be","schema_version":"1.0","event_id":"sha256:4d4cf4e19a89a564337425b5ba33f6437984bbe8470c50fe4ae8e80ed85576be"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TM4JZCDW63SIDLVMRXGI2AN7AS/bundle.json","state_url":"https://pith.science/pith/TM4JZCDW63SIDLVMRXGI2AN7AS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TM4JZCDW63SIDLVMRXGI2AN7AS/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":"2026-08-11T04:31:09Z","links":{"resolver":"https://pith.science/pith/TM4JZCDW63SIDLVMRXGI2AN7AS","bundle":"https://pith.science/pith/TM4JZCDW63SIDLVMRXGI2AN7AS/bundle.json","state":"https://pith.science/pith/TM4JZCDW63SIDLVMRXGI2AN7AS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TM4JZCDW63SIDLVMRXGI2AN7AS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:TM4JZCDW63SIDLVMRXGI2AN7AS","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":"17b9b0720fd2ba414767e91ce2f0a1208141f900679e6bb6b588da73127cdf4f","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-08-15T06:00:33Z","title_canon_sha256":"d2986faf855db1d5d3cbced5b9f5cb57db87bc51ed421b0052382a0eb05f64a8"},"schema_version":"1.0","source":{"id":"1708.04403","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.04403","created_at":"2026-05-18T00:37:59Z"},{"alias_kind":"arxiv_version","alias_value":"1708.04403v1","created_at":"2026-05-18T00:37:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.04403","created_at":"2026-05-18T00:37:59Z"},{"alias_kind":"pith_short_12","alias_value":"TM4JZCDW63SI","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"TM4JZCDW63SIDLVM","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"TM4JZCDW","created_at":"2026-05-18T12:31:46Z"}],"graph_snapshots":[{"event_id":"sha256:4d4cf4e19a89a564337425b5ba33f6437984bbe8470c50fe4ae8e80ed85576be","target":"graph","created_at":"2026-05-18T00:37:59Z","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":"Disagreement-based approaches generate multiple classifiers and exploit the disagreement among them with unlabeled data to improve learning performance. Co-training is a representative paradigm of them, which trains two classifiers separately on two sufficient and redundant views; while for the applications where there is only one view, several successful variants of co-training with two different classifiers on single-view data instead of two views have been proposed. For these disagreement-based approaches, there are several important issues which still are unsolved, in this article we prese","authors_text":"Wei Wang, Zhi-Hua Zhou","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-08-15T06:00:33Z","title":"Theoretical Foundation of Co-Training and Disagreement-Based Algorithms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.04403","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":"sha256:3efe74202076eebc0d83a5f75d2056342fd9939bbbe4fafebf371c5df3ac8e4d","target":"record","created_at":"2026-05-18T00:37:59Z","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":"17b9b0720fd2ba414767e91ce2f0a1208141f900679e6bb6b588da73127cdf4f","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-08-15T06:00:33Z","title_canon_sha256":"d2986faf855db1d5d3cbced5b9f5cb57db87bc51ed421b0052382a0eb05f64a8"},"schema_version":"1.0","source":{"id":"1708.04403","kind":"arxiv","version":1}},"canonical_sha256":"9b389c8876f6e481aeac8dcc8d01bf048a2c9581cd3f1d9cdbfc268b52efc157","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9b389c8876f6e481aeac8dcc8d01bf048a2c9581cd3f1d9cdbfc268b52efc157","first_computed_at":"2026-05-18T00:37:59.403378Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:37:59.403378Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Znu3ctk5Q6Owvrd4ym69QClLwOlhBviceR1LU7fZpsrFCwMCAnmNwb1aURqndjr0WWAvrvpfCI1Hpwqg61n/Cw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:37:59.404005Z","signed_message":"canonical_sha256_bytes"},"source_id":"1708.04403","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3efe74202076eebc0d83a5f75d2056342fd9939bbbe4fafebf371c5df3ac8e4d","sha256:4d4cf4e19a89a564337425b5ba33f6437984bbe8470c50fe4ae8e80ed85576be"],"state_sha256":"ba7c80648d3e84bd0a6a21015317c6faf8656f7d6f828f765078358806f60160"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0pHbyoQDay15XOT0hdT5AAkSD7AGcHg9JGZ5OxF/byiQ+rLH6jP0pmLZsMEUDXIaCzhal8LHq6dwrW8SDFm0Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T04:31:09.425984Z","bundle_sha256":"055c8398c6ddebb2e92e4172d696c8d101dd102e948c4e1e885eee8b2663b94e"}}