{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2009:TSI52M5FF4GEPYKO4UZMKLCE5I","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":"986abef9d2ea0b0e34d38a21f1ab07e212874b0b49716306e928640aa716560c","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2009-12-30T18:32:21Z","title_canon_sha256":"11c0205f588b5f192cadb974b25957db0bbddac2cae51f916ce368ebc36121e9"},"schema_version":"1.0","source":{"id":"0912.5507","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"0912.5507","created_at":"2026-05-18T03:28:54Z"},{"alias_kind":"arxiv_version","alias_value":"0912.5507v1","created_at":"2026-05-18T03:28:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.0912.5507","created_at":"2026-05-18T03:28:54Z"},{"alias_kind":"pith_short_12","alias_value":"TSI52M5FF4GE","created_at":"2026-05-18T12:26:02Z"},{"alias_kind":"pith_short_16","alias_value":"TSI52M5FF4GEPYKO","created_at":"2026-05-18T12:26:02Z"},{"alias_kind":"pith_short_8","alias_value":"TSI52M5F","created_at":"2026-05-18T12:26:02Z"}],"graph_snapshots":[{"event_id":"sha256:e7aa6c9efcda7614a5937ea7f4a190750338863c0351c7e4e51f937977198def","target":"graph","created_at":"2026-05-18T03:28:54Z","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":"Supervised topic models utilize document's side information for discovering predictive low dimensional representations of documents. Existing models apply the likelihood-based estimation. In this paper, we present a general framework of max-margin supervised topic models for both continuous and categorical response variables. Our approach, the maximum entropy discrimination latent Dirichlet allocation (MedLDA), utilizes the max-margin principle to train supervised topic models and estimate predictive topic representations that are arguably more suitable for prediction tasks. The general princi","authors_text":"Amr Ahmed, Eric P. Xing, Jun Zhu","cross_cats":["stat.ME"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2009-12-30T18:32:21Z","title":"MedLDA: A General Framework of Maximum Margin Supervised Topic Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"0912.5507","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":"sha256:3011fdf2e009c05f4e6436411976e52d26362a4c95529bdbc56b4e5aff8b7e53","target":"record","created_at":"2026-05-18T03:28:54Z","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":"986abef9d2ea0b0e34d38a21f1ab07e212874b0b49716306e928640aa716560c","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2009-12-30T18:32:21Z","title_canon_sha256":"11c0205f588b5f192cadb974b25957db0bbddac2cae51f916ce368ebc36121e9"},"schema_version":"1.0","source":{"id":"0912.5507","kind":"arxiv","version":1}},"canonical_sha256":"9c91dd33a52f0c47e14ee532c52c44ea1ca84cb2c724004049a298e04c28bba4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9c91dd33a52f0c47e14ee532c52c44ea1ca84cb2c724004049a298e04c28bba4","first_computed_at":"2026-05-18T03:28:54.483528Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:28:54.483528Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XcJwpDKgRVlhK4ydGD05MMoKO1GrnVmUZWtanN2tqi+fLYdqrzx12xFV08Onrdrl/4wZO7W478DnlYXc0SEZBA==","signature_status":"signed_v1","signed_at":"2026-05-18T03:28:54.483953Z","signed_message":"canonical_sha256_bytes"},"source_id":"0912.5507","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3011fdf2e009c05f4e6436411976e52d26362a4c95529bdbc56b4e5aff8b7e53","sha256:e7aa6c9efcda7614a5937ea7f4a190750338863c0351c7e4e51f937977198def"],"state_sha256":"bcac788b00689fbe4a5304af16e0337a7d886a39f34f0fe4934edbd514bdec33"}