{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:AQVAFOI7KBXQTXHMR77EDIRW3U","short_pith_number":"pith:AQVAFOI7","canonical_record":{"source":{"id":"1809.05172","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-09-13T20:39:37Z","cross_cats_sorted":["stat.ML","stat.TH"],"title_canon_sha256":"9402d20ba484d6400cdc8f49725fd0d80d3df8a7f2c9eda263eef4022ec2bcce","abstract_canon_sha256":"c39063f678ddf4e3fea783990f84b84eb790a814d14280b21dc829be516bd87e"},"schema_version":"1.0"},"canonical_sha256":"042a02b91f506f09dcec8ffe41a236dd1484c4fd6a072dc4fdddf5b61bfc32d2","source":{"kind":"arxiv","id":"1809.05172","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.05172","created_at":"2026-05-18T00:05:44Z"},{"alias_kind":"arxiv_version","alias_value":"1809.05172v1","created_at":"2026-05-18T00:05:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.05172","created_at":"2026-05-18T00:05:44Z"},{"alias_kind":"pith_short_12","alias_value":"AQVAFOI7KBXQ","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"AQVAFOI7KBXQTXHM","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"AQVAFOI7","created_at":"2026-05-18T12:32:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:AQVAFOI7KBXQTXHMR77EDIRW3U","target":"record","payload":{"canonical_record":{"source":{"id":"1809.05172","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-09-13T20:39:37Z","cross_cats_sorted":["stat.ML","stat.TH"],"title_canon_sha256":"9402d20ba484d6400cdc8f49725fd0d80d3df8a7f2c9eda263eef4022ec2bcce","abstract_canon_sha256":"c39063f678ddf4e3fea783990f84b84eb790a814d14280b21dc829be516bd87e"},"schema_version":"1.0"},"canonical_sha256":"042a02b91f506f09dcec8ffe41a236dd1484c4fd6a072dc4fdddf5b61bfc32d2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:05:44.567558Z","signature_b64":"ANbZTiM79OvOOR7WC/iEtOp71qPGi+ajqINdYvpLuEoTOyqSgrPvZzPGobG8bFRbEpWb1vns9SOBuTeEX/x8CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"042a02b91f506f09dcec8ffe41a236dd1484c4fd6a072dc4fdddf5b61bfc32d2","last_reissued_at":"2026-05-18T00:05:44.566838Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:05:44.566838Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1809.05172","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":"2026-05-18T00:05:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aET76RIN4Zi1wsq76M6t71uBalQhk2YrKpzcRCUQ6tf+FspENRU6VFUk/YL5wRyRq4732vav4VaAJfixu/FsAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T12:35:24.450911Z"},"content_sha256":"bdd09dbbfd8a46da1ed047574b253cb3dce32548b9a5ab996ce10db91321520c","schema_version":"1.0","event_id":"sha256:bdd09dbbfd8a46da1ed047574b253cb3dce32548b9a5ab996ce10db91321520c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:AQVAFOI7KBXQTXHMR77EDIRW3U","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deterministic Inequalities for Smooth M-estimators","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML","stat.TH"],"primary_cat":"math.ST","authors_text":"Arun Kumar Kuchibhotla","submitted_at":"2018-09-13T20:39:37Z","abstract_excerpt":"Ever since the proof of asymptotic normality of maximum likelihood estimator by Cramer (1946), it has been understood that a basic technique of the Taylor series expansion suffices for asymptotics of $M$-estimators with smooth/differentiable loss function. Although the Taylor series expansion is a purely deterministic tool, the realization that the asymptotic normality results can also be made deterministic (and so finite sample) received far less attention. With the advent of big data and high-dimensional statistics, the need for finite sample results has increased. In this paper, we use the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.05172","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":"2026-05-18T00:05:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EaZ70dohdnrbawvElnDez8MkR9Kn04uJUrxEmmo6ruhYr6KBXr5Y+CfhG7UlYOGbo7f+zw8cGCdHUi4xtImzDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T12:35:24.451254Z"},"content_sha256":"d65857e0a81e4b63c6837ee9ebd501a60a5d4f81f36d67632bb5c84e1ae11adf","schema_version":"1.0","event_id":"sha256:d65857e0a81e4b63c6837ee9ebd501a60a5d4f81f36d67632bb5c84e1ae11adf"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AQVAFOI7KBXQTXHMR77EDIRW3U/bundle.json","state_url":"https://pith.science/pith/AQVAFOI7KBXQTXHMR77EDIRW3U/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AQVAFOI7KBXQTXHMR77EDIRW3U/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":"2026-05-28T12:35:24Z","links":{"resolver":"https://pith.science/pith/AQVAFOI7KBXQTXHMR77EDIRW3U","bundle":"https://pith.science/pith/AQVAFOI7KBXQTXHMR77EDIRW3U/bundle.json","state":"https://pith.science/pith/AQVAFOI7KBXQTXHMR77EDIRW3U/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AQVAFOI7KBXQTXHMR77EDIRW3U/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:AQVAFOI7KBXQTXHMR77EDIRW3U","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":"c39063f678ddf4e3fea783990f84b84eb790a814d14280b21dc829be516bd87e","cross_cats_sorted":["stat.ML","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-09-13T20:39:37Z","title_canon_sha256":"9402d20ba484d6400cdc8f49725fd0d80d3df8a7f2c9eda263eef4022ec2bcce"},"schema_version":"1.0","source":{"id":"1809.05172","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.05172","created_at":"2026-05-18T00:05:44Z"},{"alias_kind":"arxiv_version","alias_value":"1809.05172v1","created_at":"2026-05-18T00:05:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.05172","created_at":"2026-05-18T00:05:44Z"},{"alias_kind":"pith_short_12","alias_value":"AQVAFOI7KBXQ","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"AQVAFOI7KBXQTXHM","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"AQVAFOI7","created_at":"2026-05-18T12:32:13Z"}],"graph_snapshots":[{"event_id":"sha256:d65857e0a81e4b63c6837ee9ebd501a60a5d4f81f36d67632bb5c84e1ae11adf","target":"graph","created_at":"2026-05-18T00:05:44Z","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":"Ever since the proof of asymptotic normality of maximum likelihood estimator by Cramer (1946), it has been understood that a basic technique of the Taylor series expansion suffices for asymptotics of $M$-estimators with smooth/differentiable loss function. Although the Taylor series expansion is a purely deterministic tool, the realization that the asymptotic normality results can also be made deterministic (and so finite sample) received far less attention. With the advent of big data and high-dimensional statistics, the need for finite sample results has increased. In this paper, we use the ","authors_text":"Arun Kumar Kuchibhotla","cross_cats":["stat.ML","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-09-13T20:39:37Z","title":"Deterministic Inequalities for Smooth M-estimators"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.05172","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:bdd09dbbfd8a46da1ed047574b253cb3dce32548b9a5ab996ce10db91321520c","target":"record","created_at":"2026-05-18T00:05:44Z","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":"c39063f678ddf4e3fea783990f84b84eb790a814d14280b21dc829be516bd87e","cross_cats_sorted":["stat.ML","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-09-13T20:39:37Z","title_canon_sha256":"9402d20ba484d6400cdc8f49725fd0d80d3df8a7f2c9eda263eef4022ec2bcce"},"schema_version":"1.0","source":{"id":"1809.05172","kind":"arxiv","version":1}},"canonical_sha256":"042a02b91f506f09dcec8ffe41a236dd1484c4fd6a072dc4fdddf5b61bfc32d2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"042a02b91f506f09dcec8ffe41a236dd1484c4fd6a072dc4fdddf5b61bfc32d2","first_computed_at":"2026-05-18T00:05:44.566838Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:05:44.566838Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ANbZTiM79OvOOR7WC/iEtOp71qPGi+ajqINdYvpLuEoTOyqSgrPvZzPGobG8bFRbEpWb1vns9SOBuTeEX/x8CQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:05:44.567558Z","signed_message":"canonical_sha256_bytes"},"source_id":"1809.05172","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bdd09dbbfd8a46da1ed047574b253cb3dce32548b9a5ab996ce10db91321520c","sha256:d65857e0a81e4b63c6837ee9ebd501a60a5d4f81f36d67632bb5c84e1ae11adf"],"state_sha256":"3178b1311e68319da3df647c00e207b4a0b2e93f0e3b3a404a0a9179d7d8157c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2qfRAmh7g8oq3Q281/0tyXAdOi2hsaVlkg9GaM/Q/X4TKQ5mqH1YeetktXih2vhSZmrc2Y7w/O1zW9JBuS4WCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T12:35:24.453218Z","bundle_sha256":"030f618d990c87036f486642ee5d4c9bbc1067ee3ce5668ca8fd2cc946b60f9e"}}