{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:ER5J6L3P6PMIMFBKMD2I3CG72T","short_pith_number":"pith:ER5J6L3P","schema_version":"1.0","canonical_sha256":"247a9f2f6ff3d886142a60f48d88dfd4d8f7b07b97228107fbe9bd63e7a6e42f","source":{"kind":"arxiv","id":"1807.06799","version":1},"attestation_state":"computed","paper":{"title":"Robust Distributed Compression of Symmetrically Correlated Gaussian Sources","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Jun Chen, Li Xie, Xuan Zhang, Yizhong Wang","submitted_at":"2018-07-18T07:10:50Z","abstract_excerpt":"Consider a lossy compression system with $\\ell$ distributed encoders and a centralized decoder. Each encoder compresses its observed source and forwards the compressed data to the decoder for joint reconstruction of the target signals under the mean squared error distortion constraint. It is assumed that the observed sources can be expressed as the sum of the target signals and the corruptive noises, which are generated independently from two symmetric multivariate Gaussian distributions. Depending on the parameters of such distributions, the rate-distortion limit of this system is characteriz"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1807.06799","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2018-07-18T07:10:50Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"5ddfdb08ed9000a8feab53d50fc2db95252a21bae6b0fc2cb37326e6cd525e85","abstract_canon_sha256":"2601a44127b9268f714a8f5b5d48c1d23190e0d4982d9ae9ebf11e2af5452a49"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:10:25.744149Z","signature_b64":"kaS1W1gAp2K2ZDL8A9FXme14AaRb3Z1qMUniMg5Yyk8RW4M6MRjaYDTgn2Y6+JCvcGuFCI4sG8lVX0wCiRN5Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"247a9f2f6ff3d886142a60f48d88dfd4d8f7b07b97228107fbe9bd63e7a6e42f","last_reissued_at":"2026-05-18T00:10:25.743653Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:10:25.743653Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Robust Distributed Compression of Symmetrically Correlated Gaussian Sources","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Jun Chen, Li Xie, Xuan Zhang, Yizhong Wang","submitted_at":"2018-07-18T07:10:50Z","abstract_excerpt":"Consider a lossy compression system with $\\ell$ distributed encoders and a centralized decoder. Each encoder compresses its observed source and forwards the compressed data to the decoder for joint reconstruction of the target signals under the mean squared error distortion constraint. It is assumed that the observed sources can be expressed as the sum of the target signals and the corruptive noises, which are generated independently from two symmetric multivariate Gaussian distributions. Depending on the parameters of such distributions, the rate-distortion limit of this system is characteriz"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.06799","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1807.06799","created_at":"2026-05-18T00:10:25.743742+00:00"},{"alias_kind":"arxiv_version","alias_value":"1807.06799v1","created_at":"2026-05-18T00:10:25.743742+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.06799","created_at":"2026-05-18T00:10:25.743742+00:00"},{"alias_kind":"pith_short_12","alias_value":"ER5J6L3P6PMI","created_at":"2026-05-18T12:32:22.470017+00:00"},{"alias_kind":"pith_short_16","alias_value":"ER5J6L3P6PMIMFBK","created_at":"2026-05-18T12:32:22.470017+00:00"},{"alias_kind":"pith_short_8","alias_value":"ER5J6L3P","created_at":"2026-05-18T12:32:22.470017+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ER5J6L3P6PMIMFBKMD2I3CG72T","json":"https://pith.science/pith/ER5J6L3P6PMIMFBKMD2I3CG72T.json","graph_json":"https://pith.science/api/pith-number/ER5J6L3P6PMIMFBKMD2I3CG72T/graph.json","events_json":"https://pith.science/api/pith-number/ER5J6L3P6PMIMFBKMD2I3CG72T/events.json","paper":"https://pith.science/paper/ER5J6L3P"},"agent_actions":{"view_html":"https://pith.science/pith/ER5J6L3P6PMIMFBKMD2I3CG72T","download_json":"https://pith.science/pith/ER5J6L3P6PMIMFBKMD2I3CG72T.json","view_paper":"https://pith.science/paper/ER5J6L3P","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1807.06799&json=true","fetch_graph":"https://pith.science/api/pith-number/ER5J6L3P6PMIMFBKMD2I3CG72T/graph.json","fetch_events":"https://pith.science/api/pith-number/ER5J6L3P6PMIMFBKMD2I3CG72T/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ER5J6L3P6PMIMFBKMD2I3CG72T/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ER5J6L3P6PMIMFBKMD2I3CG72T/action/storage_attestation","attest_author":"https://pith.science/pith/ER5J6L3P6PMIMFBKMD2I3CG72T/action/author_attestation","sign_citation":"https://pith.science/pith/ER5J6L3P6PMIMFBKMD2I3CG72T/action/citation_signature","submit_replication":"https://pith.science/pith/ER5J6L3P6PMIMFBKMD2I3CG72T/action/replication_record"}},"created_at":"2026-05-18T00:10:25.743742+00:00","updated_at":"2026-05-18T00:10:25.743742+00:00"}