{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:7U73RXO7J6DAUZU24NC646MYBZ","short_pith_number":"pith:7U73RXO7","canonical_record":{"source":{"id":"1904.06307","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-12T16:26:04Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"3b55ece18ecde236003b99e1e3c822606b43edfcda2586e0b71da8196a88388a","abstract_canon_sha256":"b5a8a41f06de80937b79f6c397f3f148b3f45fc67d78b38ba3a36ae6410130ff"},"schema_version":"1.0"},"canonical_sha256":"fd3fb8dddf4f860a669ae345ee79980e70aa80a1ddce56bef82ccb064f17bcc2","source":{"kind":"arxiv","id":"1904.06307","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.06307","created_at":"2026-05-17T23:48:43Z"},{"alias_kind":"arxiv_version","alias_value":"1904.06307v1","created_at":"2026-05-17T23:48:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.06307","created_at":"2026-05-17T23:48:43Z"},{"alias_kind":"pith_short_12","alias_value":"7U73RXO7J6DA","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"7U73RXO7J6DAUZU2","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"7U73RXO7","created_at":"2026-05-18T12:33:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:7U73RXO7J6DAUZU24NC646MYBZ","target":"record","payload":{"canonical_record":{"source":{"id":"1904.06307","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-12T16:26:04Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"3b55ece18ecde236003b99e1e3c822606b43edfcda2586e0b71da8196a88388a","abstract_canon_sha256":"b5a8a41f06de80937b79f6c397f3f148b3f45fc67d78b38ba3a36ae6410130ff"},"schema_version":"1.0"},"canonical_sha256":"fd3fb8dddf4f860a669ae345ee79980e70aa80a1ddce56bef82ccb064f17bcc2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:48:43.635155Z","signature_b64":"90TH/iAVLWMYO5+St/xzJUTDeyI+ZT8vHrpdcWn6RwIT/PhMd87H0/kmPhghLJeHMFuQrNYQBE+125cyyPbRAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fd3fb8dddf4f860a669ae345ee79980e70aa80a1ddce56bef82ccb064f17bcc2","last_reissued_at":"2026-05-17T23:48:43.634704Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:48:43.634704Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.06307","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":"2026-05-17T23:48:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LiD6wT+zayuC3ON5eYOg8BCN4TN12JPAXMDKpJ18pa4Oi6yjQeJulGnST/Jk6HcTz7oZt0hKLVPTMmzvMC7qAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T08:49:10.402436Z"},"content_sha256":"c1198b80b95fb30dedf8192efa7f35c30d2b1cd784bfd50bd3e929d7e001ba47","schema_version":"1.0","event_id":"sha256:c1198b80b95fb30dedf8192efa7f35c30d2b1cd784bfd50bd3e929d7e001ba47"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:7U73RXO7J6DAUZU24NC646MYBZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Revisit Lmser and its further development based on convolutional layers","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Lei Xu, Shikui Tu, Wenjing Huang","submitted_at":"2019-04-12T16:26:04Z","abstract_excerpt":"Proposed in 1991, Least Mean Square Error Reconstruction for self-organizing network, shortly Lmser, was a further development of the traditional auto-encoder (AE) by folding the architecture with respect to the central coding layer and thus leading to the features of symmetric weights and neurons, as well as jointly supervised and unsupervised learning. However, its advantages were only demonstrated in a one-hidden-layer implementation due to the lack of computing resources and big data at that time. In this paper, we revisit Lmser from the perspective of deep learning, develop Lmser network "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.06307","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":"2026-05-17T23:48:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+qRL6hkw8rrx43YBgShXyTNrvSJhe1hWGUiVQPOhhPY54hVtvcrxbcBV6rdVCHMpnx4zcErUEkL8Q+y2Ln4ADA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T08:49:10.403079Z"},"content_sha256":"37d552951acc9a12b6e88143d9b26b858bcd5da2b4ddc340d14f346e305b8b89","schema_version":"1.0","event_id":"sha256:37d552951acc9a12b6e88143d9b26b858bcd5da2b4ddc340d14f346e305b8b89"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7U73RXO7J6DAUZU24NC646MYBZ/bundle.json","state_url":"https://pith.science/pith/7U73RXO7J6DAUZU24NC646MYBZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7U73RXO7J6DAUZU24NC646MYBZ/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":"2026-05-30T08:49:10Z","links":{"resolver":"https://pith.science/pith/7U73RXO7J6DAUZU24NC646MYBZ","bundle":"https://pith.science/pith/7U73RXO7J6DAUZU24NC646MYBZ/bundle.json","state":"https://pith.science/pith/7U73RXO7J6DAUZU24NC646MYBZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7U73RXO7J6DAUZU24NC646MYBZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:7U73RXO7J6DAUZU24NC646MYBZ","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":"b5a8a41f06de80937b79f6c397f3f148b3f45fc67d78b38ba3a36ae6410130ff","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-12T16:26:04Z","title_canon_sha256":"3b55ece18ecde236003b99e1e3c822606b43edfcda2586e0b71da8196a88388a"},"schema_version":"1.0","source":{"id":"1904.06307","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.06307","created_at":"2026-05-17T23:48:43Z"},{"alias_kind":"arxiv_version","alias_value":"1904.06307v1","created_at":"2026-05-17T23:48:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.06307","created_at":"2026-05-17T23:48:43Z"},{"alias_kind":"pith_short_12","alias_value":"7U73RXO7J6DA","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"7U73RXO7J6DAUZU2","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"7U73RXO7","created_at":"2026-05-18T12:33:12Z"}],"graph_snapshots":[{"event_id":"sha256:37d552951acc9a12b6e88143d9b26b858bcd5da2b4ddc340d14f346e305b8b89","target":"graph","created_at":"2026-05-17T23:48:43Z","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":"Proposed in 1991, Least Mean Square Error Reconstruction for self-organizing network, shortly Lmser, was a further development of the traditional auto-encoder (AE) by folding the architecture with respect to the central coding layer and thus leading to the features of symmetric weights and neurons, as well as jointly supervised and unsupervised learning. However, its advantages were only demonstrated in a one-hidden-layer implementation due to the lack of computing resources and big data at that time. In this paper, we revisit Lmser from the perspective of deep learning, develop Lmser network ","authors_text":"Lei Xu, Shikui Tu, Wenjing Huang","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-12T16:26:04Z","title":"Revisit Lmser and its further development based on convolutional layers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.06307","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:c1198b80b95fb30dedf8192efa7f35c30d2b1cd784bfd50bd3e929d7e001ba47","target":"record","created_at":"2026-05-17T23:48:43Z","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":"b5a8a41f06de80937b79f6c397f3f148b3f45fc67d78b38ba3a36ae6410130ff","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-12T16:26:04Z","title_canon_sha256":"3b55ece18ecde236003b99e1e3c822606b43edfcda2586e0b71da8196a88388a"},"schema_version":"1.0","source":{"id":"1904.06307","kind":"arxiv","version":1}},"canonical_sha256":"fd3fb8dddf4f860a669ae345ee79980e70aa80a1ddce56bef82ccb064f17bcc2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fd3fb8dddf4f860a669ae345ee79980e70aa80a1ddce56bef82ccb064f17bcc2","first_computed_at":"2026-05-17T23:48:43.634704Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:48:43.634704Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"90TH/iAVLWMYO5+St/xzJUTDeyI+ZT8vHrpdcWn6RwIT/PhMd87H0/kmPhghLJeHMFuQrNYQBE+125cyyPbRAg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:48:43.635155Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.06307","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c1198b80b95fb30dedf8192efa7f35c30d2b1cd784bfd50bd3e929d7e001ba47","sha256:37d552951acc9a12b6e88143d9b26b858bcd5da2b4ddc340d14f346e305b8b89"],"state_sha256":"27e122816503fe521d12c8d064b1c448487d8c07add100e3721be264642eff34"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5PX8K7EPjEsybEA44FwdjBG4V77Ik049ZBWgO64g+tVnbzZ95BTT+D5x5P/fHKSQ0GzkqeVIExoKQM7Ty8N+AA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T08:49:10.406355Z","bundle_sha256":"754f580080c379e5bd262241027f2ba155f8fce55505972316ddce0bf1113a23"}}