{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:QJKNXK5ABR6RRHM3OBWDFUB4LF","short_pith_number":"pith:QJKNXK5A","schema_version":"1.0","canonical_sha256":"8254dbaba00c7d189d9b706c32d03c596e51bc7702cfee5cf909039587961f41","source":{"kind":"arxiv","id":"1708.05629","version":1},"attestation_state":"computed","paper":{"title":"Learning to Transfer","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.AI","authors_text":"Qiang Yang, Ying Wei, Yu Zhang","submitted_at":"2017-08-18T14:36:29Z","abstract_excerpt":"Transfer learning borrows knowledge from a source domain to facilitate learning in a target domain. Two primary issues to be addressed in transfer learning are what and how to transfer. For a pair of domains, adopting different transfer learning algorithms results in different knowledge transferred between them. To discover the optimal transfer learning algorithm that maximally improves the learning performance in the target domain, researchers have to exhaustively explore all existing transfer learning algorithms, which is computationally intractable. As a trade-off, a sub-optimal algorithm i"},"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":"1708.05629","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-08-18T14:36:29Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"18d97bb8633cbd217eef41a91fd595b1db5133d8b31bf8e7c50e70647b93694d","abstract_canon_sha256":"f718664c6eb53013d8a6c16caf8a30cbf6bafcb6d6c03bceff960942658b77b4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:37:49.460550Z","signature_b64":"vWQoxDSPugj1Gvz8CVwHEjP34/hzk7qlPZoPfHG4Qf+ec8v54hxBSpa3GAki3gJwUz6Fo1qr/UO/l3sY1tCBBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8254dbaba00c7d189d9b706c32d03c596e51bc7702cfee5cf909039587961f41","last_reissued_at":"2026-05-18T00:37:49.459941Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:37:49.459941Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Learning to Transfer","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.AI","authors_text":"Qiang Yang, Ying Wei, Yu Zhang","submitted_at":"2017-08-18T14:36:29Z","abstract_excerpt":"Transfer learning borrows knowledge from a source domain to facilitate learning in a target domain. Two primary issues to be addressed in transfer learning are what and how to transfer. For a pair of domains, adopting different transfer learning algorithms results in different knowledge transferred between them. To discover the optimal transfer learning algorithm that maximally improves the learning performance in the target domain, researchers have to exhaustively explore all existing transfer learning algorithms, which is computationally intractable. As a trade-off, a sub-optimal algorithm i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.05629","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1708.05629","created_at":"2026-05-18T00:37:49.460029+00:00"},{"alias_kind":"arxiv_version","alias_value":"1708.05629v1","created_at":"2026-05-18T00:37:49.460029+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.05629","created_at":"2026-05-18T00:37:49.460029+00:00"},{"alias_kind":"pith_short_12","alias_value":"QJKNXK5ABR6R","created_at":"2026-05-18T12:31:39.905425+00:00"},{"alias_kind":"pith_short_16","alias_value":"QJKNXK5ABR6RRHM3","created_at":"2026-05-18T12:31:39.905425+00:00"},{"alias_kind":"pith_short_8","alias_value":"QJKNXK5A","created_at":"2026-05-18T12:31:39.905425+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/QJKNXK5ABR6RRHM3OBWDFUB4LF","json":"https://pith.science/pith/QJKNXK5ABR6RRHM3OBWDFUB4LF.json","graph_json":"https://pith.science/api/pith-number/QJKNXK5ABR6RRHM3OBWDFUB4LF/graph.json","events_json":"https://pith.science/api/pith-number/QJKNXK5ABR6RRHM3OBWDFUB4LF/events.json","paper":"https://pith.science/paper/QJKNXK5A"},"agent_actions":{"view_html":"https://pith.science/pith/QJKNXK5ABR6RRHM3OBWDFUB4LF","download_json":"https://pith.science/pith/QJKNXK5ABR6RRHM3OBWDFUB4LF.json","view_paper":"https://pith.science/paper/QJKNXK5A","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1708.05629&json=true","fetch_graph":"https://pith.science/api/pith-number/QJKNXK5ABR6RRHM3OBWDFUB4LF/graph.json","fetch_events":"https://pith.science/api/pith-number/QJKNXK5ABR6RRHM3OBWDFUB4LF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QJKNXK5ABR6RRHM3OBWDFUB4LF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QJKNXK5ABR6RRHM3OBWDFUB4LF/action/storage_attestation","attest_author":"https://pith.science/pith/QJKNXK5ABR6RRHM3OBWDFUB4LF/action/author_attestation","sign_citation":"https://pith.science/pith/QJKNXK5ABR6RRHM3OBWDFUB4LF/action/citation_signature","submit_replication":"https://pith.science/pith/QJKNXK5ABR6RRHM3OBWDFUB4LF/action/replication_record"}},"created_at":"2026-05-18T00:37:49.460029+00:00","updated_at":"2026-05-18T00:37:49.460029+00:00"}