{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2005:3KBN4OS2CCGBI7T5JLOTGVUYRB","short_pith_number":"pith:3KBN4OS2","canonical_record":{"source":{"id":"cs/0506023","kind":"arxiv","version":1},"metadata":{"license":"","primary_cat":"cs.CE","submitted_at":"2005-06-08T21:08:38Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"8d21df84a339033d52f12569d061279a2258a9f7b1b683649359a49faa6694cc","abstract_canon_sha256":"e2cb77dd8f235e022f6e8f0bb4b30ec77ddf2d92be4776255f734d44c2a4167b"},"schema_version":"1.0"},"canonical_sha256":"da82de3a5a108c147e7d4add33569888644271175db5829a9bc8320148565a41","source":{"kind":"arxiv","id":"cs/0506023","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"cs/0506023","created_at":"2026-07-04T14:25:02Z"},{"alias_kind":"arxiv_version","alias_value":"cs/0506023v1","created_at":"2026-07-04T14:25:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.cs/0506023","created_at":"2026-07-04T14:25:02Z"},{"alias_kind":"pith_short_12","alias_value":"3KBN4OS2CCGB","created_at":"2026-07-04T14:25:02Z"},{"alias_kind":"pith_short_16","alias_value":"3KBN4OS2CCGBI7T5","created_at":"2026-07-04T14:25:02Z"},{"alias_kind":"pith_short_8","alias_value":"3KBN4OS2","created_at":"2026-07-04T14:25:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2005:3KBN4OS2CCGBI7T5JLOTGVUYRB","target":"record","payload":{"canonical_record":{"source":{"id":"cs/0506023","kind":"arxiv","version":1},"metadata":{"license":"","primary_cat":"cs.CE","submitted_at":"2005-06-08T21:08:38Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"8d21df84a339033d52f12569d061279a2258a9f7b1b683649359a49faa6694cc","abstract_canon_sha256":"e2cb77dd8f235e022f6e8f0bb4b30ec77ddf2d92be4776255f734d44c2a4167b"},"schema_version":"1.0"},"canonical_sha256":"da82de3a5a108c147e7d4add33569888644271175db5829a9bc8320148565a41","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-04T14:25:02.969364Z","signature_b64":"9tVXEPLCWFw7ftN1WSUFW7W5iFZIBYlD9xAYoyit/poTzAiSyBlQTKGjZkQMFQM3zraQBfrERBZJnGZAx4wuAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"da82de3a5a108c147e7d4add33569888644271175db5829a9bc8320148565a41","last_reissued_at":"2026-07-04T14:25:02.968945Z","signature_status":"signed_v1","first_computed_at":"2026-07-04T14:25:02.968945Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"cs/0506023","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":"2026-07-04T14:25:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u2rIC5AIypbaTi2p/Wvst++/2Kg8oPIMPtcx1qzE2wUJqowFmQsEJcBhrIOBqiooEQ2+g3sn7cO4lwtD0Jt0AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T19:47:41.232126Z"},"content_sha256":"cd0c2d3c396f80a1e6caf0b1dcc2f88a92f83c4604d8721ec1fb0344620395d8","schema_version":"1.0","event_id":"sha256:cd0c2d3c396f80a1e6caf0b1dcc2f88a92f83c4604d8721ec1fb0344620395d8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2005:3KBN4OS2CCGBI7T5JLOTGVUYRB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sparse Covariance Selection via Robust Maximum Likelihood Estimation","license":"","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CE","authors_text":"Alexandre d'Aspremont, Laurent El Ghaoui, Onureena Banerjee","submitted_at":"2005-06-08T21:08:38Z","abstract_excerpt":"We address a problem of covariance selection, where we seek a trade-off between a high likelihood against the number of non-zero elements in the inverse covariance matrix. We solve a maximum likelihood problem with a penalty term given by the sum of absolute values of the elements of the inverse covariance matrix, and allow for imposing bounds on the condition number of the solution. The problem is directly amenable to now standard interior-point algorithms for convex optimization, but remains challenging due to its size. We first give some results on the theoretical computational complexity o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"cs/0506023","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/cs/0506023/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-04T14:25:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+M0/xvsOv8P5VOUn6a9+t2cfO5ToKDDrQKIlUfW85X8hoNRTiFOeain6vCPFXMBzp03s/F822zqU+g+Tsn2rAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T19:47:41.232851Z"},"content_sha256":"aafbf79084ac93da26f1347f1ceb477b721f2bf145c879e2ce9a3f723ddcb6ae","schema_version":"1.0","event_id":"sha256:aafbf79084ac93da26f1347f1ceb477b721f2bf145c879e2ce9a3f723ddcb6ae"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3KBN4OS2CCGBI7T5JLOTGVUYRB/bundle.json","state_url":"https://pith.science/pith/3KBN4OS2CCGBI7T5JLOTGVUYRB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3KBN4OS2CCGBI7T5JLOTGVUYRB/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":"2026-08-05T19:47:41Z","links":{"resolver":"https://pith.science/pith/3KBN4OS2CCGBI7T5JLOTGVUYRB","bundle":"https://pith.science/pith/3KBN4OS2CCGBI7T5JLOTGVUYRB/bundle.json","state":"https://pith.science/pith/3KBN4OS2CCGBI7T5JLOTGVUYRB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3KBN4OS2CCGBI7T5JLOTGVUYRB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2005:3KBN4OS2CCGBI7T5JLOTGVUYRB","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":"e2cb77dd8f235e022f6e8f0bb4b30ec77ddf2d92be4776255f734d44c2a4167b","cross_cats_sorted":["cs.AI"],"license":"","primary_cat":"cs.CE","submitted_at":"2005-06-08T21:08:38Z","title_canon_sha256":"8d21df84a339033d52f12569d061279a2258a9f7b1b683649359a49faa6694cc"},"schema_version":"1.0","source":{"id":"cs/0506023","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"cs/0506023","created_at":"2026-07-04T14:25:02Z"},{"alias_kind":"arxiv_version","alias_value":"cs/0506023v1","created_at":"2026-07-04T14:25:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.cs/0506023","created_at":"2026-07-04T14:25:02Z"},{"alias_kind":"pith_short_12","alias_value":"3KBN4OS2CCGB","created_at":"2026-07-04T14:25:02Z"},{"alias_kind":"pith_short_16","alias_value":"3KBN4OS2CCGBI7T5","created_at":"2026-07-04T14:25:02Z"},{"alias_kind":"pith_short_8","alias_value":"3KBN4OS2","created_at":"2026-07-04T14:25:02Z"}],"graph_snapshots":[{"event_id":"sha256:aafbf79084ac93da26f1347f1ceb477b721f2bf145c879e2ce9a3f723ddcb6ae","target":"graph","created_at":"2026-07-04T14:25:02Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/cs/0506023/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We address a problem of covariance selection, where we seek a trade-off between a high likelihood against the number of non-zero elements in the inverse covariance matrix. We solve a maximum likelihood problem with a penalty term given by the sum of absolute values of the elements of the inverse covariance matrix, and allow for imposing bounds on the condition number of the solution. The problem is directly amenable to now standard interior-point algorithms for convex optimization, but remains challenging due to its size. We first give some results on the theoretical computational complexity o","authors_text":"Alexandre d'Aspremont, Laurent El Ghaoui, Onureena Banerjee","cross_cats":["cs.AI"],"headline":"","license":"","primary_cat":"cs.CE","submitted_at":"2005-06-08T21:08:38Z","title":"Sparse Covariance Selection via Robust Maximum Likelihood Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"cs/0506023","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:cd0c2d3c396f80a1e6caf0b1dcc2f88a92f83c4604d8721ec1fb0344620395d8","target":"record","created_at":"2026-07-04T14:25:02Z","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":"e2cb77dd8f235e022f6e8f0bb4b30ec77ddf2d92be4776255f734d44c2a4167b","cross_cats_sorted":["cs.AI"],"license":"","primary_cat":"cs.CE","submitted_at":"2005-06-08T21:08:38Z","title_canon_sha256":"8d21df84a339033d52f12569d061279a2258a9f7b1b683649359a49faa6694cc"},"schema_version":"1.0","source":{"id":"cs/0506023","kind":"arxiv","version":1}},"canonical_sha256":"da82de3a5a108c147e7d4add33569888644271175db5829a9bc8320148565a41","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"da82de3a5a108c147e7d4add33569888644271175db5829a9bc8320148565a41","first_computed_at":"2026-07-04T14:25:02.968945Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-04T14:25:02.968945Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9tVXEPLCWFw7ftN1WSUFW7W5iFZIBYlD9xAYoyit/poTzAiSyBlQTKGjZkQMFQM3zraQBfrERBZJnGZAx4wuAA==","signature_status":"signed_v1","signed_at":"2026-07-04T14:25:02.969364Z","signed_message":"canonical_sha256_bytes"},"source_id":"cs/0506023","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cd0c2d3c396f80a1e6caf0b1dcc2f88a92f83c4604d8721ec1fb0344620395d8","sha256:aafbf79084ac93da26f1347f1ceb477b721f2bf145c879e2ce9a3f723ddcb6ae"],"state_sha256":"b49e5315250e76da03f9c8a834feb2ffecc97c6a8383426ab249f4f9040f955e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sKn1IyNb9JOSlobRl0nNE6lIKHn3cEQ1RXiZUKSFxA+pvFTMGWm1GdbYbOpL+wpqXx5ohfvR6OS3mQc2i9QyDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T19:47:41.242162Z","bundle_sha256":"1b16768aa1f51db4b0ac3537d878a3c4d842c5fda3803efcd06d90a2da3f29b3"}}