{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:ZUQ4MUQMY7LE7Z6PG7MAKEA2UB","short_pith_number":"pith:ZUQ4MUQM","canonical_record":{"source":{"id":"1905.10424","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-05-24T19:50:37Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"8438dfe298b6178f2224b70f4e0ce70736fccd88b10df68cc6d3a884e8aaea61","abstract_canon_sha256":"c67fe5f963a603e09b5cd5b859ff1f81eacdbbb3bbaa5019dc57f58d5f377453"},"schema_version":"1.0"},"canonical_sha256":"cd21c6520cc7d64fe7cf37d805101aa06f4ab3b7c75673b46656c09126bfc26a","source":{"kind":"arxiv","id":"1905.10424","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.10424","created_at":"2026-05-17T23:45:08Z"},{"alias_kind":"arxiv_version","alias_value":"1905.10424v1","created_at":"2026-05-17T23:45:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.10424","created_at":"2026-05-17T23:45:08Z"},{"alias_kind":"pith_short_12","alias_value":"ZUQ4MUQMY7LE","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"ZUQ4MUQMY7LE7Z6P","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"ZUQ4MUQM","created_at":"2026-05-18T12:33:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:ZUQ4MUQMY7LE7Z6PG7MAKEA2UB","target":"record","payload":{"canonical_record":{"source":{"id":"1905.10424","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-05-24T19:50:37Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"8438dfe298b6178f2224b70f4e0ce70736fccd88b10df68cc6d3a884e8aaea61","abstract_canon_sha256":"c67fe5f963a603e09b5cd5b859ff1f81eacdbbb3bbaa5019dc57f58d5f377453"},"schema_version":"1.0"},"canonical_sha256":"cd21c6520cc7d64fe7cf37d805101aa06f4ab3b7c75673b46656c09126bfc26a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:45:08.579256Z","signature_b64":"QP6cAiUSSrCxJK5Zf0lm1kFQv+ZOLTf/acplHuKtWHoaU4F8nCLayDZu5b5Ep6N6cYjbpte9y3uAeQWSv5iqCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cd21c6520cc7d64fe7cf37d805101aa06f4ab3b7c75673b46656c09126bfc26a","last_reissued_at":"2026-05-17T23:45:08.578500Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:45:08.578500Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1905.10424","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":"2026-05-17T23:45:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jtqLt5I1sOO5v+2LSyAGfHBh636oWelhaO3AsURTv5DzKxPra90qlIcB1ieSGmSUodBzBBFgTgqOfFJJOsD4CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T05:18:52.466522Z"},"content_sha256":"69fb0dd85ebb5aea4ce32c15de4ecfcc42da3dadd0b112924224cbcfdf76b01c","schema_version":"1.0","event_id":"sha256:69fb0dd85ebb5aea4ce32c15de4ecfcc42da3dadd0b112924224cbcfdf76b01c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:ZUQ4MUQMY7LE7Z6PG7MAKEA2UB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A general method for regularizing tensor decomposition methods via pseudo-data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Finale Doshi-Velez, Omer Gottesman, Weiwei Pan","submitted_at":"2019-05-24T19:50:37Z","abstract_excerpt":"Tensor decomposition methods allow us to learn the parameters of latent variable models through decomposition of low-order moments of data. A significant limitation of these algorithms is that there exists no general method to regularize them, and in the past regularization has mostly been performed using bespoke modifications to the algorithms, tailored for the particular form of the desired regularizer. We present a general method of regularizing tensor decomposition methods which can be used for any likelihood model that is learnable using tensor decomposition methods and any differentiable"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.10424","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":"2026-05-17T23:45:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"B1AAgrc34Jf7y2wWPqqoY6fLxPIL4/6Y3SMaKoiZDrG/uoZk4aHzJfFLSK41MKiF6yLNN9ySZMNxDm/vrHp7DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T05:18:52.466933Z"},"content_sha256":"a879099fe6d2c67751b4fbe00a57614956d467d0e76a3f8f24aae88079ca3c99","schema_version":"1.0","event_id":"sha256:a879099fe6d2c67751b4fbe00a57614956d467d0e76a3f8f24aae88079ca3c99"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZUQ4MUQMY7LE7Z6PG7MAKEA2UB/bundle.json","state_url":"https://pith.science/pith/ZUQ4MUQMY7LE7Z6PG7MAKEA2UB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZUQ4MUQMY7LE7Z6PG7MAKEA2UB/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":"2026-05-26T05:18:52Z","links":{"resolver":"https://pith.science/pith/ZUQ4MUQMY7LE7Z6PG7MAKEA2UB","bundle":"https://pith.science/pith/ZUQ4MUQMY7LE7Z6PG7MAKEA2UB/bundle.json","state":"https://pith.science/pith/ZUQ4MUQMY7LE7Z6PG7MAKEA2UB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZUQ4MUQMY7LE7Z6PG7MAKEA2UB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:ZUQ4MUQMY7LE7Z6PG7MAKEA2UB","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":"c67fe5f963a603e09b5cd5b859ff1f81eacdbbb3bbaa5019dc57f58d5f377453","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-05-24T19:50:37Z","title_canon_sha256":"8438dfe298b6178f2224b70f4e0ce70736fccd88b10df68cc6d3a884e8aaea61"},"schema_version":"1.0","source":{"id":"1905.10424","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.10424","created_at":"2026-05-17T23:45:08Z"},{"alias_kind":"arxiv_version","alias_value":"1905.10424v1","created_at":"2026-05-17T23:45:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.10424","created_at":"2026-05-17T23:45:08Z"},{"alias_kind":"pith_short_12","alias_value":"ZUQ4MUQMY7LE","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"ZUQ4MUQMY7LE7Z6P","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"ZUQ4MUQM","created_at":"2026-05-18T12:33:33Z"}],"graph_snapshots":[{"event_id":"sha256:a879099fe6d2c67751b4fbe00a57614956d467d0e76a3f8f24aae88079ca3c99","target":"graph","created_at":"2026-05-17T23:45:08Z","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":"Tensor decomposition methods allow us to learn the parameters of latent variable models through decomposition of low-order moments of data. A significant limitation of these algorithms is that there exists no general method to regularize them, and in the past regularization has mostly been performed using bespoke modifications to the algorithms, tailored for the particular form of the desired regularizer. We present a general method of regularizing tensor decomposition methods which can be used for any likelihood model that is learnable using tensor decomposition methods and any differentiable","authors_text":"Finale Doshi-Velez, Omer Gottesman, Weiwei Pan","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-05-24T19:50:37Z","title":"A general method for regularizing tensor decomposition methods via pseudo-data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.10424","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":"sha256:69fb0dd85ebb5aea4ce32c15de4ecfcc42da3dadd0b112924224cbcfdf76b01c","target":"record","created_at":"2026-05-17T23:45:08Z","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":"c67fe5f963a603e09b5cd5b859ff1f81eacdbbb3bbaa5019dc57f58d5f377453","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2019-05-24T19:50:37Z","title_canon_sha256":"8438dfe298b6178f2224b70f4e0ce70736fccd88b10df68cc6d3a884e8aaea61"},"schema_version":"1.0","source":{"id":"1905.10424","kind":"arxiv","version":1}},"canonical_sha256":"cd21c6520cc7d64fe7cf37d805101aa06f4ab3b7c75673b46656c09126bfc26a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cd21c6520cc7d64fe7cf37d805101aa06f4ab3b7c75673b46656c09126bfc26a","first_computed_at":"2026-05-17T23:45:08.578500Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:45:08.578500Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QP6cAiUSSrCxJK5Zf0lm1kFQv+ZOLTf/acplHuKtWHoaU4F8nCLayDZu5b5Ep6N6cYjbpte9y3uAeQWSv5iqCQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:45:08.579256Z","signed_message":"canonical_sha256_bytes"},"source_id":"1905.10424","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:69fb0dd85ebb5aea4ce32c15de4ecfcc42da3dadd0b112924224cbcfdf76b01c","sha256:a879099fe6d2c67751b4fbe00a57614956d467d0e76a3f8f24aae88079ca3c99"],"state_sha256":"5f15ffbfa296cae85d2f80e996c873e83dc9ecc14e99881007910dece7e3e31f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KiCK1yZfnpc1ILFuENw8/seNBtoc08JrZUUWcPxCL+/kqdZQz7pjrUy61mlRiiUFbbkp8zwU2HYQ96QKwrn8AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T05:18:52.469833Z","bundle_sha256":"79069d895ed22081adc29c2d0888dd88c1a555003ab2ca420b48b4c7a980c483"}}