{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:HGZUXAOO473MWYQJU24KAZW3ZY","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":"dc665962ec1f180468c7905d2577e5494f93857d7d6eac4058245f06169afc9c","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-19T07:48:07Z","title_canon_sha256":"12323cb7f2c6cf7c2945efadb49ec0efa98b7d177f0d6c3a20e49584a648735f"},"schema_version":"1.0","source":{"id":"1902.06938","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.06938","created_at":"2026-05-17T23:53:40Z"},{"alias_kind":"arxiv_version","alias_value":"1902.06938v1","created_at":"2026-05-17T23:53:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.06938","created_at":"2026-05-17T23:53:40Z"},{"alias_kind":"pith_short_12","alias_value":"HGZUXAOO473M","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_16","alias_value":"HGZUXAOO473MWYQJ","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_8","alias_value":"HGZUXAOO","created_at":"2026-05-18T12:33:18Z"}],"graph_snapshots":[{"event_id":"sha256:67a698cc6dea81585578a4b7ba50c9f44aa14bd1eed865e6d8136611a8eb1a28","target":"graph","created_at":"2026-05-17T23:53:40Z","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":"Generative Adversarial Networks (GANs) have achieved great success in generating realistic images. Most of these are conditional models, although acquisition of class labels is expensive and time-consuming in practice. To reduce the dependence on labeled data, we propose an un-conditional generative adversarial model, called K-Means-GAN (KM-GAN), which incorporates the idea of updating centers in K-Means into GANs. Specifically, we redesign the framework of GANs by applying K-Means on the features extracted from the discriminator. With obtained labels from K-Means, we propose new objective fun","authors_text":"Ce Wang, Kun Shang, Zhangling Chen","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-19T07:48:07Z","title":"Label-Removed Generative Adversarial Networks Incorporating with K-Means"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.06938","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":"sha256:6149940c055359ddfa04f03f99a6120552e79c3d934bbf5eaabbab5badc4c1a9","target":"record","created_at":"2026-05-17T23:53:40Z","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":"dc665962ec1f180468c7905d2577e5494f93857d7d6eac4058245f06169afc9c","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-02-19T07:48:07Z","title_canon_sha256":"12323cb7f2c6cf7c2945efadb49ec0efa98b7d177f0d6c3a20e49584a648735f"},"schema_version":"1.0","source":{"id":"1902.06938","kind":"arxiv","version":1}},"canonical_sha256":"39b34b81cee7f6cb6209a6b8a066dbce3ab5d28fb06f96e688e6ea20f4f2a950","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"39b34b81cee7f6cb6209a6b8a066dbce3ab5d28fb06f96e688e6ea20f4f2a950","first_computed_at":"2026-05-17T23:53:40.376272Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:53:40.376272Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"e0hI4NCMJaW7N/NnFJ/V5rw6daF6dpQ94cK60ESqB5YU+sjXb3NtVq4d0NqhN+CNrp/qa4w0863gWUbfu2xgAw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:53:40.376777Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.06938","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6149940c055359ddfa04f03f99a6120552e79c3d934bbf5eaabbab5badc4c1a9","sha256:67a698cc6dea81585578a4b7ba50c9f44aa14bd1eed865e6d8136611a8eb1a28"],"state_sha256":"bac018dccfeab3aee7ebd13dc058200e38c50ee4ddba37f38392ce84a069fb10"}