{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:5REY64N6VDPZPHMXGATARBHESK","short_pith_number":"pith:5REY64N6","canonical_record":{"source":{"id":"1709.03239","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-11T04:41:06Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"a1f86dc4da1745bf833392175dffaf0dd9897314826f3baa7b9ad19d34dae580","abstract_canon_sha256":"45e56818de9d53b11a3dfd779de9dcf125b2236f58acadb4c384c4a93332bff1"},"schema_version":"1.0"},"canonical_sha256":"ec498f71bea8df979d9730260884e492ba3dccba4b3669f1d055f10ccd69e905","source":{"kind":"arxiv","id":"1709.03239","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.03239","created_at":"2026-05-18T00:09:42Z"},{"alias_kind":"arxiv_version","alias_value":"1709.03239v2","created_at":"2026-05-18T00:09:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.03239","created_at":"2026-05-18T00:09:42Z"},{"alias_kind":"pith_short_12","alias_value":"5REY64N6VDPZ","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_16","alias_value":"5REY64N6VDPZPHMX","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_8","alias_value":"5REY64N6","created_at":"2026-05-18T12:31:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:5REY64N6VDPZPHMXGATARBHESK","target":"record","payload":{"canonical_record":{"source":{"id":"1709.03239","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-11T04:41:06Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"a1f86dc4da1745bf833392175dffaf0dd9897314826f3baa7b9ad19d34dae580","abstract_canon_sha256":"45e56818de9d53b11a3dfd779de9dcf125b2236f58acadb4c384c4a93332bff1"},"schema_version":"1.0"},"canonical_sha256":"ec498f71bea8df979d9730260884e492ba3dccba4b3669f1d055f10ccd69e905","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:09:42.079334Z","signature_b64":"GG/NQGbmpoTMQNpaf6MImVpoc4UIlkRQIi0HT0Rf8TpfFObwsIT0udtZfBTNlWp2uyiLKgrH8fF7eLeKt13sBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ec498f71bea8df979d9730260884e492ba3dccba4b3669f1d055f10ccd69e905","last_reissued_at":"2026-05-18T00:09:42.078640Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:09:42.078640Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1709.03239","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:09:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GSPzxz+xlQZhsK8irD57u2uahXtRfJ4/9xHszFZnAqF8dkytzVlH4Ll/Jjmq9MvTkhb6sTamSD8sQbhVXsk4Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T22:15:16.895899Z"},"content_sha256":"eda7afd701df89729d54024119cc802f06917bc22ca18b7a3d49a7a5faa6b2b7","schema_version":"1.0","event_id":"sha256:eda7afd701df89729d54024119cc802f06917bc22ca18b7a3d49a7a5faa6b2b7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:5REY64N6VDPZPHMXGATARBHESK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"On better training the infinite restricted Boltzmann machines","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"cs.LG","authors_text":"Xiang Li, Xuan Peng, Xunzhang Gao","submitted_at":"2017-09-11T04:41:06Z","abstract_excerpt":"The infinite restricted Boltzmann machine (iRBM) is an extension of the classic RBM. It enjoys a good property of automatically deciding the size of the hidden layer according to specific training data. With sufficient training, the iRBM can achieve a competitive performance with that of the classic RBM. However, the convergence of learning the iRBM is slow, due to the fact that the iRBM is sensitive to the ordering of its hidden units, the learned filters change slowly from the left-most hidden unit to right. To break this dependency between neighboring hidden units and speed up the convergen"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.03239","kind":"arxiv","version":2},"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":"2026-05-18T00:09:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zT9v0vRvql+uiuebPox1r6Y6q5mTBawMJ+NLhq0nuylsp0BvwUuwAbOmyOUSGMFPUFM2SH3AIp4ugCtE2kx8Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T22:15:16.896254Z"},"content_sha256":"9f8c14b96112bf70f25d28cc187591c95fcffe260523aa391b55dd1ea9f9bf52","schema_version":"1.0","event_id":"sha256:9f8c14b96112bf70f25d28cc187591c95fcffe260523aa391b55dd1ea9f9bf52"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5REY64N6VDPZPHMXGATARBHESK/bundle.json","state_url":"https://pith.science/pith/5REY64N6VDPZPHMXGATARBHESK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5REY64N6VDPZPHMXGATARBHESK/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":"2026-05-27T22:15:16Z","links":{"resolver":"https://pith.science/pith/5REY64N6VDPZPHMXGATARBHESK","bundle":"https://pith.science/pith/5REY64N6VDPZPHMXGATARBHESK/bundle.json","state":"https://pith.science/pith/5REY64N6VDPZPHMXGATARBHESK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5REY64N6VDPZPHMXGATARBHESK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:5REY64N6VDPZPHMXGATARBHESK","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":"45e56818de9d53b11a3dfd779de9dcf125b2236f58acadb4c384c4a93332bff1","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-11T04:41:06Z","title_canon_sha256":"a1f86dc4da1745bf833392175dffaf0dd9897314826f3baa7b9ad19d34dae580"},"schema_version":"1.0","source":{"id":"1709.03239","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.03239","created_at":"2026-05-18T00:09:42Z"},{"alias_kind":"arxiv_version","alias_value":"1709.03239v2","created_at":"2026-05-18T00:09:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.03239","created_at":"2026-05-18T00:09:42Z"},{"alias_kind":"pith_short_12","alias_value":"5REY64N6VDPZ","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_16","alias_value":"5REY64N6VDPZPHMX","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_8","alias_value":"5REY64N6","created_at":"2026-05-18T12:31:00Z"}],"graph_snapshots":[{"event_id":"sha256:9f8c14b96112bf70f25d28cc187591c95fcffe260523aa391b55dd1ea9f9bf52","target":"graph","created_at":"2026-05-18T00:09:42Z","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":"The infinite restricted Boltzmann machine (iRBM) is an extension of the classic RBM. It enjoys a good property of automatically deciding the size of the hidden layer according to specific training data. With sufficient training, the iRBM can achieve a competitive performance with that of the classic RBM. However, the convergence of learning the iRBM is slow, due to the fact that the iRBM is sensitive to the ordering of its hidden units, the learned filters change slowly from the left-most hidden unit to right. To break this dependency between neighboring hidden units and speed up the convergen","authors_text":"Xiang Li, Xuan Peng, Xunzhang Gao","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-11T04:41:06Z","title":"On better training the infinite restricted Boltzmann machines"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.03239","kind":"arxiv","version":2},"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:eda7afd701df89729d54024119cc802f06917bc22ca18b7a3d49a7a5faa6b2b7","target":"record","created_at":"2026-05-18T00:09:42Z","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":"45e56818de9d53b11a3dfd779de9dcf125b2236f58acadb4c384c4a93332bff1","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-11T04:41:06Z","title_canon_sha256":"a1f86dc4da1745bf833392175dffaf0dd9897314826f3baa7b9ad19d34dae580"},"schema_version":"1.0","source":{"id":"1709.03239","kind":"arxiv","version":2}},"canonical_sha256":"ec498f71bea8df979d9730260884e492ba3dccba4b3669f1d055f10ccd69e905","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ec498f71bea8df979d9730260884e492ba3dccba4b3669f1d055f10ccd69e905","first_computed_at":"2026-05-18T00:09:42.078640Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:09:42.078640Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GG/NQGbmpoTMQNpaf6MImVpoc4UIlkRQIi0HT0Rf8TpfFObwsIT0udtZfBTNlWp2uyiLKgrH8fF7eLeKt13sBA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:09:42.079334Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.03239","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:eda7afd701df89729d54024119cc802f06917bc22ca18b7a3d49a7a5faa6b2b7","sha256:9f8c14b96112bf70f25d28cc187591c95fcffe260523aa391b55dd1ea9f9bf52"],"state_sha256":"72dd7d9a2991f4da02cdb15f84b6008c9d0508d9b0c15112f691a5839b3714ca"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9O+roXogSesirINxdt5/7q1xDm9wuYQovn9Nlmo7J5TH1MkZy9DxYiWk78c+XrHNvx4sRh5ZV7AjgO6RQojzCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T22:15:16.898199Z","bundle_sha256":"91b5ec9a3a04ab27f38ee56d0cb9b7ca2bd95815beea10a22428607b63391fe1"}}