{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:2SXYCEFTESIYEHSCAZBRCRYBTP","short_pith_number":"pith:2SXYCEFT","canonical_record":{"source":{"id":"1301.3545","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-01-16T01:40:20Z","cross_cats_sorted":["cs.NE","stat.ML"],"title_canon_sha256":"f73ad516ae940591f5082d168e10243eee09675dc37cd251188d35b89f8975cb","abstract_canon_sha256":"33e252f3c176b9d15baeeddb0e0ea057346d12b8e67f4582875e43c42454e3f0"},"schema_version":"1.0"},"canonical_sha256":"d4af8110b32491821e4206431147019be3866e769e9c4ddf74b2bac5cc4a0132","source":{"kind":"arxiv","id":"1301.3545","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1301.3545","created_at":"2026-05-18T03:30:41Z"},{"alias_kind":"arxiv_version","alias_value":"1301.3545v2","created_at":"2026-05-18T03:30:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1301.3545","created_at":"2026-05-18T03:30:41Z"},{"alias_kind":"pith_short_12","alias_value":"2SXYCEFTESIY","created_at":"2026-05-18T12:27:32Z"},{"alias_kind":"pith_short_16","alias_value":"2SXYCEFTESIYEHSC","created_at":"2026-05-18T12:27:32Z"},{"alias_kind":"pith_short_8","alias_value":"2SXYCEFT","created_at":"2026-05-18T12:27:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:2SXYCEFTESIYEHSCAZBRCRYBTP","target":"record","payload":{"canonical_record":{"source":{"id":"1301.3545","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-01-16T01:40:20Z","cross_cats_sorted":["cs.NE","stat.ML"],"title_canon_sha256":"f73ad516ae940591f5082d168e10243eee09675dc37cd251188d35b89f8975cb","abstract_canon_sha256":"33e252f3c176b9d15baeeddb0e0ea057346d12b8e67f4582875e43c42454e3f0"},"schema_version":"1.0"},"canonical_sha256":"d4af8110b32491821e4206431147019be3866e769e9c4ddf74b2bac5cc4a0132","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:30:41.042994Z","signature_b64":"HPbk9CqlLXfykcNF6oJi6KmvpPqjyUFHam0UiYuDwQKQwIchcQgPMxfeVSvr6LAUBL45X+NBEih+F095ycUXDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d4af8110b32491821e4206431147019be3866e769e9c4ddf74b2bac5cc4a0132","last_reissued_at":"2026-05-18T03:30:41.042179Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:30:41.042179Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1301.3545","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":"2026-05-18T03:30:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rZkY33IRC1oZFd2y0V0Y5QPYkz4htxBKoIYKsy7jYu3zjRbB1iq4H8fc1d6noQKMGo0noI9aozzN68GToLEKCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T13:33:00.988413Z"},"content_sha256":"51439ecacd658ed4924cfa83e37d0af9afb5ffbd038ce8a3899cec9f9268d7cc","schema_version":"1.0","event_id":"sha256:51439ecacd658ed4924cfa83e37d0af9afb5ffbd038ce8a3899cec9f9268d7cc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:2SXYCEFTESIYEHSCAZBRCRYBTP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Metric-Free Natural Gradient for Joint-Training of Boltzmann Machines","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NE","stat.ML"],"primary_cat":"cs.LG","authors_text":"Aaron Courville, Guillaume Desjardins, Razvan Pascanu, Yoshua Bengio","submitted_at":"2013-01-16T01:40:20Z","abstract_excerpt":"This paper introduces the Metric-Free Natural Gradient (MFNG) algorithm for training Boltzmann Machines. Similar in spirit to the Hessian-Free method of Martens [8], our algorithm belongs to the family of truncated Newton methods and exploits an efficient matrix-vector product to avoid explicitely storing the natural gradient metric $L$. This metric is shown to be the expected second derivative of the log-partition function (under the model distribution), or equivalently, the variance of the vector of partial derivatives of the energy function. We evaluate our method on the task of joint-train"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1301.3545","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":"2026-05-18T03:30:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3194Ks5GfM9A0vI5e7Se7YqjG6A8AHerEQXfT+cmtv3Q9zspZfTO2+khgEBblbeSvyjbFCPv6xv5RFn5rKZOAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T13:33:00.988767Z"},"content_sha256":"f57c2ab83a1b3b4d87d0abb5356e5ead43faa29fbdf6be06502d12293e14f3cd","schema_version":"1.0","event_id":"sha256:f57c2ab83a1b3b4d87d0abb5356e5ead43faa29fbdf6be06502d12293e14f3cd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2SXYCEFTESIYEHSCAZBRCRYBTP/bundle.json","state_url":"https://pith.science/pith/2SXYCEFTESIYEHSCAZBRCRYBTP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2SXYCEFTESIYEHSCAZBRCRYBTP/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":"2026-05-28T13:33:00Z","links":{"resolver":"https://pith.science/pith/2SXYCEFTESIYEHSCAZBRCRYBTP","bundle":"https://pith.science/pith/2SXYCEFTESIYEHSCAZBRCRYBTP/bundle.json","state":"https://pith.science/pith/2SXYCEFTESIYEHSCAZBRCRYBTP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2SXYCEFTESIYEHSCAZBRCRYBTP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:2SXYCEFTESIYEHSCAZBRCRYBTP","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":"33e252f3c176b9d15baeeddb0e0ea057346d12b8e67f4582875e43c42454e3f0","cross_cats_sorted":["cs.NE","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-01-16T01:40:20Z","title_canon_sha256":"f73ad516ae940591f5082d168e10243eee09675dc37cd251188d35b89f8975cb"},"schema_version":"1.0","source":{"id":"1301.3545","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1301.3545","created_at":"2026-05-18T03:30:41Z"},{"alias_kind":"arxiv_version","alias_value":"1301.3545v2","created_at":"2026-05-18T03:30:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1301.3545","created_at":"2026-05-18T03:30:41Z"},{"alias_kind":"pith_short_12","alias_value":"2SXYCEFTESIY","created_at":"2026-05-18T12:27:32Z"},{"alias_kind":"pith_short_16","alias_value":"2SXYCEFTESIYEHSC","created_at":"2026-05-18T12:27:32Z"},{"alias_kind":"pith_short_8","alias_value":"2SXYCEFT","created_at":"2026-05-18T12:27:32Z"}],"graph_snapshots":[{"event_id":"sha256:f57c2ab83a1b3b4d87d0abb5356e5ead43faa29fbdf6be06502d12293e14f3cd","target":"graph","created_at":"2026-05-18T03:30:41Z","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":"This paper introduces the Metric-Free Natural Gradient (MFNG) algorithm for training Boltzmann Machines. Similar in spirit to the Hessian-Free method of Martens [8], our algorithm belongs to the family of truncated Newton methods and exploits an efficient matrix-vector product to avoid explicitely storing the natural gradient metric $L$. This metric is shown to be the expected second derivative of the log-partition function (under the model distribution), or equivalently, the variance of the vector of partial derivatives of the energy function. We evaluate our method on the task of joint-train","authors_text":"Aaron Courville, Guillaume Desjardins, Razvan Pascanu, Yoshua Bengio","cross_cats":["cs.NE","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-01-16T01:40:20Z","title":"Metric-Free Natural Gradient for Joint-Training of Boltzmann Machines"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1301.3545","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":"sha256:51439ecacd658ed4924cfa83e37d0af9afb5ffbd038ce8a3899cec9f9268d7cc","target":"record","created_at":"2026-05-18T03:30:41Z","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":"33e252f3c176b9d15baeeddb0e0ea057346d12b8e67f4582875e43c42454e3f0","cross_cats_sorted":["cs.NE","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-01-16T01:40:20Z","title_canon_sha256":"f73ad516ae940591f5082d168e10243eee09675dc37cd251188d35b89f8975cb"},"schema_version":"1.0","source":{"id":"1301.3545","kind":"arxiv","version":2}},"canonical_sha256":"d4af8110b32491821e4206431147019be3866e769e9c4ddf74b2bac5cc4a0132","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d4af8110b32491821e4206431147019be3866e769e9c4ddf74b2bac5cc4a0132","first_computed_at":"2026-05-18T03:30:41.042179Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:30:41.042179Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HPbk9CqlLXfykcNF6oJi6KmvpPqjyUFHam0UiYuDwQKQwIchcQgPMxfeVSvr6LAUBL45X+NBEih+F095ycUXDw==","signature_status":"signed_v1","signed_at":"2026-05-18T03:30:41.042994Z","signed_message":"canonical_sha256_bytes"},"source_id":"1301.3545","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:51439ecacd658ed4924cfa83e37d0af9afb5ffbd038ce8a3899cec9f9268d7cc","sha256:f57c2ab83a1b3b4d87d0abb5356e5ead43faa29fbdf6be06502d12293e14f3cd"],"state_sha256":"82f32262ae88c4034aa529448ec158b6112661eb48b986d59ebb334829715b34"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zo9xCCjKZZBx1j41Mo1ZrwyDBeHLEjX8/l+biTrrbmRBQbzGECKjwaw4XE9VaW2ZxhN6Shjx2kQKkhBLbFE5CQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T13:33:00.990743Z","bundle_sha256":"7d0921a957fc6537e8dca1ece1321b2e6d5c952603f3509a54c1c4f3c1103c2c"}}