{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:UC7NQQX2QYBYNNBEL7ZNIEKWUN","short_pith_number":"pith:UC7NQQX2","canonical_record":{"source":{"id":"1605.07689","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-05-25T00:12:06Z","cross_cats_sorted":["cs.IT","cs.LG","math.IT","math.OC","stat.ME"],"title_canon_sha256":"a4f88c527ee3c0a12949f6569a2bb106477bd5fe209644d0b7ee8ee47ac75a6c","abstract_canon_sha256":"1302cae643a641a64783c91daacb5f4611b971bb77cd27d96f5d2d7ddd4fb6f3"},"schema_version":"1.0"},"canonical_sha256":"a0bed842fa860386b4245ff2d41156a3502ea4570c625a73522f3c4fcd94270b","source":{"kind":"arxiv","id":"1605.07689","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1605.07689","created_at":"2026-05-18T01:00:05Z"},{"alias_kind":"arxiv_version","alias_value":"1605.07689v3","created_at":"2026-05-18T01:00:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1605.07689","created_at":"2026-05-18T01:00:05Z"},{"alias_kind":"pith_short_12","alias_value":"UC7NQQX2QYBY","created_at":"2026-05-18T12:30:46Z"},{"alias_kind":"pith_short_16","alias_value":"UC7NQQX2QYBYNNBE","created_at":"2026-05-18T12:30:46Z"},{"alias_kind":"pith_short_8","alias_value":"UC7NQQX2","created_at":"2026-05-18T12:30:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:UC7NQQX2QYBYNNBEL7ZNIEKWUN","target":"record","payload":{"canonical_record":{"source":{"id":"1605.07689","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-05-25T00:12:06Z","cross_cats_sorted":["cs.IT","cs.LG","math.IT","math.OC","stat.ME"],"title_canon_sha256":"a4f88c527ee3c0a12949f6569a2bb106477bd5fe209644d0b7ee8ee47ac75a6c","abstract_canon_sha256":"1302cae643a641a64783c91daacb5f4611b971bb77cd27d96f5d2d7ddd4fb6f3"},"schema_version":"1.0"},"canonical_sha256":"a0bed842fa860386b4245ff2d41156a3502ea4570c625a73522f3c4fcd94270b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:00:05.812372Z","signature_b64":"GTgAahEz1RICFMtO9+G8WGEZzE5Ir2r9d8GWY50qGOrY+eaOr+6jKFMFfvf9yrwcPBNXb8tqWYAjNGURrOPoBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a0bed842fa860386b4245ff2d41156a3502ea4570c625a73522f3c4fcd94270b","last_reissued_at":"2026-05-18T01:00:05.811736Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:00:05.811736Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1605.07689","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:00:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FPW7c3IsMBbS2+PaKSf87AHfAHzOlgBiS4SCwed1mTnatFuHd2Lgb1Zv072b99XSeYNoxoDqqHHF5DwYSUaoAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T06:20:04.096843Z"},"content_sha256":"f1696e8b8730c5a540fb82bc5df27b9a49b34058e928db3787472c548e03c4c3","schema_version":"1.0","event_id":"sha256:f1696e8b8730c5a540fb82bc5df27b9a49b34058e928db3787472c548e03c4c3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:UC7NQQX2QYBYNNBEL7ZNIEKWUN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Communication-Efficient Distributed Statistical Inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IT","cs.LG","math.IT","math.OC","stat.ME"],"primary_cat":"stat.ML","authors_text":"Jason D. Lee, Michael I. Jordan, Yun Yang","submitted_at":"2016-05-25T00:12:06Z","abstract_excerpt":"We present a Communication-efficient Surrogate Likelihood (CSL) framework for solving distributed statistical inference problems. CSL provides a communication-efficient surrogate to the global likelihood that can be used for low-dimensional estimation, high-dimensional regularized estimation and Bayesian inference. For low-dimensional estimation, CSL provably improves upon naive averaging schemes and facilitates the construction of confidence intervals. For high-dimensional regularized estimation, CSL leads to a minimax-optimal estimator with controlled communication cost. For Bayesian inferen"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1605.07689","kind":"arxiv","version":3},"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":"2026-05-18T01:00:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V1RKJiadtWLJqsecxwu7RGVtzyXuQSfS+aUCwrDbtzwhyfQJqrneo5pWf6Ug2liP6W3ypLYPPiiyve7FPANPCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T06:20:04.097509Z"},"content_sha256":"5e6ca97b77ee632160f05b749f2e94716c863cc6ca8f867569e9f393eaac42e5","schema_version":"1.0","event_id":"sha256:5e6ca97b77ee632160f05b749f2e94716c863cc6ca8f867569e9f393eaac42e5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UC7NQQX2QYBYNNBEL7ZNIEKWUN/bundle.json","state_url":"https://pith.science/pith/UC7NQQX2QYBYNNBEL7ZNIEKWUN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UC7NQQX2QYBYNNBEL7ZNIEKWUN/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":"2026-05-31T06:20:04Z","links":{"resolver":"https://pith.science/pith/UC7NQQX2QYBYNNBEL7ZNIEKWUN","bundle":"https://pith.science/pith/UC7NQQX2QYBYNNBEL7ZNIEKWUN/bundle.json","state":"https://pith.science/pith/UC7NQQX2QYBYNNBEL7ZNIEKWUN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UC7NQQX2QYBYNNBEL7ZNIEKWUN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:UC7NQQX2QYBYNNBEL7ZNIEKWUN","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":"1302cae643a641a64783c91daacb5f4611b971bb77cd27d96f5d2d7ddd4fb6f3","cross_cats_sorted":["cs.IT","cs.LG","math.IT","math.OC","stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-05-25T00:12:06Z","title_canon_sha256":"a4f88c527ee3c0a12949f6569a2bb106477bd5fe209644d0b7ee8ee47ac75a6c"},"schema_version":"1.0","source":{"id":"1605.07689","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1605.07689","created_at":"2026-05-18T01:00:05Z"},{"alias_kind":"arxiv_version","alias_value":"1605.07689v3","created_at":"2026-05-18T01:00:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1605.07689","created_at":"2026-05-18T01:00:05Z"},{"alias_kind":"pith_short_12","alias_value":"UC7NQQX2QYBY","created_at":"2026-05-18T12:30:46Z"},{"alias_kind":"pith_short_16","alias_value":"UC7NQQX2QYBYNNBE","created_at":"2026-05-18T12:30:46Z"},{"alias_kind":"pith_short_8","alias_value":"UC7NQQX2","created_at":"2026-05-18T12:30:46Z"}],"graph_snapshots":[{"event_id":"sha256:5e6ca97b77ee632160f05b749f2e94716c863cc6ca8f867569e9f393eaac42e5","target":"graph","created_at":"2026-05-18T01:00:05Z","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":"We present a Communication-efficient Surrogate Likelihood (CSL) framework for solving distributed statistical inference problems. CSL provides a communication-efficient surrogate to the global likelihood that can be used for low-dimensional estimation, high-dimensional regularized estimation and Bayesian inference. For low-dimensional estimation, CSL provably improves upon naive averaging schemes and facilitates the construction of confidence intervals. For high-dimensional regularized estimation, CSL leads to a minimax-optimal estimator with controlled communication cost. For Bayesian inferen","authors_text":"Jason D. Lee, Michael I. Jordan, Yun Yang","cross_cats":["cs.IT","cs.LG","math.IT","math.OC","stat.ME"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-05-25T00:12:06Z","title":"Communication-Efficient Distributed Statistical Inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1605.07689","kind":"arxiv","version":3},"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:f1696e8b8730c5a540fb82bc5df27b9a49b34058e928db3787472c548e03c4c3","target":"record","created_at":"2026-05-18T01:00:05Z","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":"1302cae643a641a64783c91daacb5f4611b971bb77cd27d96f5d2d7ddd4fb6f3","cross_cats_sorted":["cs.IT","cs.LG","math.IT","math.OC","stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-05-25T00:12:06Z","title_canon_sha256":"a4f88c527ee3c0a12949f6569a2bb106477bd5fe209644d0b7ee8ee47ac75a6c"},"schema_version":"1.0","source":{"id":"1605.07689","kind":"arxiv","version":3}},"canonical_sha256":"a0bed842fa860386b4245ff2d41156a3502ea4570c625a73522f3c4fcd94270b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a0bed842fa860386b4245ff2d41156a3502ea4570c625a73522f3c4fcd94270b","first_computed_at":"2026-05-18T01:00:05.811736Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:00:05.811736Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GTgAahEz1RICFMtO9+G8WGEZzE5Ir2r9d8GWY50qGOrY+eaOr+6jKFMFfvf9yrwcPBNXb8tqWYAjNGURrOPoBw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:00:05.812372Z","signed_message":"canonical_sha256_bytes"},"source_id":"1605.07689","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f1696e8b8730c5a540fb82bc5df27b9a49b34058e928db3787472c548e03c4c3","sha256:5e6ca97b77ee632160f05b749f2e94716c863cc6ca8f867569e9f393eaac42e5"],"state_sha256":"5e7cdf0e108e07ad9ebf6ac1620081fc9ae4cd441655fca61eeabba5b48d3f64"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ozxEtbf1+ZVaLRMAiB64ll4csePRnWIROjK5Isbw/DI2F2zKbMQrPS2ICvKgxsi0i4oP0kX67Ydpb9PQDd+DBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T06:20:04.100974Z","bundle_sha256":"f9ff82f426686374688f47ec13ea3ded7fe06e66ab40a832f0dd05768e70d78a"}}