{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:MNCL6IQDGGXPJCR2EK32MTU2VS","short_pith_number":"pith:MNCL6IQD","canonical_record":{"source":{"id":"1406.2623","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2014-06-10T16:44:32Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"af45ce004435f9de39dccbfedb0d592a2abaf9c9a7368e5b7fe345722e8fbcea","abstract_canon_sha256":"9e95ef08aa332e711c9916c6120c0de3d501bf5e409e4854c787ff15e41144d6"},"schema_version":"1.0"},"canonical_sha256":"6344bf220331aef48a3a22b7a64e9aaca7415a9a064486bc6de0b775bed3a7c1","source":{"kind":"arxiv","id":"1406.2623","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1406.2623","created_at":"2026-05-18T02:49:55Z"},{"alias_kind":"arxiv_version","alias_value":"1406.2623v2","created_at":"2026-05-18T02:49:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1406.2623","created_at":"2026-05-18T02:49:55Z"},{"alias_kind":"pith_short_12","alias_value":"MNCL6IQDGGXP","created_at":"2026-05-18T12:28:38Z"},{"alias_kind":"pith_short_16","alias_value":"MNCL6IQDGGXPJCR2","created_at":"2026-05-18T12:28:38Z"},{"alias_kind":"pith_short_8","alias_value":"MNCL6IQD","created_at":"2026-05-18T12:28:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:MNCL6IQDGGXPJCR2EK32MTU2VS","target":"record","payload":{"canonical_record":{"source":{"id":"1406.2623","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2014-06-10T16:44:32Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"af45ce004435f9de39dccbfedb0d592a2abaf9c9a7368e5b7fe345722e8fbcea","abstract_canon_sha256":"9e95ef08aa332e711c9916c6120c0de3d501bf5e409e4854c787ff15e41144d6"},"schema_version":"1.0"},"canonical_sha256":"6344bf220331aef48a3a22b7a64e9aaca7415a9a064486bc6de0b775bed3a7c1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:49:55.367952Z","signature_b64":"y0E3ysAwMCdqL7RS9pJiHg5pQBSd9pxECNs73qe5AU32uuxC2EQ44k4jjZa2ABiFhwlNCvxH1X3gjY/BhBxiBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6344bf220331aef48a3a22b7a64e9aaca7415a9a064486bc6de0b775bed3a7c1","last_reissued_at":"2026-05-18T02:49:55.367481Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:49:55.367481Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1406.2623","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:49:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HJJnKlcZrInz7dRQdYtsJwyzwmJy2TIf6ApTLDqruD3lDzXZHkK7WfeOKUHbCnGqWgHpwK7WNp6a7ioWMkIjBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T01:29:40.720240Z"},"content_sha256":"b16f51bf5dd9fff3aa20efafcfa64ddc1729f9712e2a0a9f38963ba85db61483","schema_version":"1.0","event_id":"sha256:b16f51bf5dd9fff3aa20efafcfa64ddc1729f9712e2a0a9f38963ba85db61483"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:MNCL6IQDGGXPJCR2EK32MTU2VS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Maximum Likelihood-based Online Adaptation of Hyper-parameters in CMA-ES","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.NE","authors_text":"Ilya Loshchilov (LIS), INRIA Saclay - Ile de France), Marc Schoenauer (LRI, Mich\\`ele Sebag (LRI), Nikolaus Hansen (INRIA Saclay - Ile de France)","submitted_at":"2014-06-10T16:44:32Z","abstract_excerpt":"The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is widely accepted as a robust derivative-free continuous optimization algorithm for non-linear and non-convex optimization problems. CMA-ES is well known to be almost parameterless, meaning that only one hyper-parameter, the population size, is proposed to be tuned by the user. In this paper, we propose a principled approach called self-CMA-ES to achieve the online adaptation of CMA-ES hyper-parameters in order to improve its overall performance. Experimental results show that for larger-than-default population size, the default set"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1406.2623","kind":"arxiv","version":2},"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":"2026-05-18T02:49:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lfsZQT2nRYgcM8sFStg/sd727ibbm+iLE6ygvdF5sOpXmCyc3sI1W6fDPigmtWbV9C6riDRPiePPe/YMu9vZBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T01:29:40.721011Z"},"content_sha256":"5fb6d83b238a630efceef62e8e7e1507bc0a11196f03a2e12b612400c753f918","schema_version":"1.0","event_id":"sha256:5fb6d83b238a630efceef62e8e7e1507bc0a11196f03a2e12b612400c753f918"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MNCL6IQDGGXPJCR2EK32MTU2VS/bundle.json","state_url":"https://pith.science/pith/MNCL6IQDGGXPJCR2EK32MTU2VS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MNCL6IQDGGXPJCR2EK32MTU2VS/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":"2026-06-09T01:29:40Z","links":{"resolver":"https://pith.science/pith/MNCL6IQDGGXPJCR2EK32MTU2VS","bundle":"https://pith.science/pith/MNCL6IQDGGXPJCR2EK32MTU2VS/bundle.json","state":"https://pith.science/pith/MNCL6IQDGGXPJCR2EK32MTU2VS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MNCL6IQDGGXPJCR2EK32MTU2VS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:MNCL6IQDGGXPJCR2EK32MTU2VS","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":"9e95ef08aa332e711c9916c6120c0de3d501bf5e409e4854c787ff15e41144d6","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2014-06-10T16:44:32Z","title_canon_sha256":"af45ce004435f9de39dccbfedb0d592a2abaf9c9a7368e5b7fe345722e8fbcea"},"schema_version":"1.0","source":{"id":"1406.2623","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1406.2623","created_at":"2026-05-18T02:49:55Z"},{"alias_kind":"arxiv_version","alias_value":"1406.2623v2","created_at":"2026-05-18T02:49:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1406.2623","created_at":"2026-05-18T02:49:55Z"},{"alias_kind":"pith_short_12","alias_value":"MNCL6IQDGGXP","created_at":"2026-05-18T12:28:38Z"},{"alias_kind":"pith_short_16","alias_value":"MNCL6IQDGGXPJCR2","created_at":"2026-05-18T12:28:38Z"},{"alias_kind":"pith_short_8","alias_value":"MNCL6IQD","created_at":"2026-05-18T12:28:38Z"}],"graph_snapshots":[{"event_id":"sha256:5fb6d83b238a630efceef62e8e7e1507bc0a11196f03a2e12b612400c753f918","target":"graph","created_at":"2026-05-18T02:49:55Z","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":"The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is widely accepted as a robust derivative-free continuous optimization algorithm for non-linear and non-convex optimization problems. CMA-ES is well known to be almost parameterless, meaning that only one hyper-parameter, the population size, is proposed to be tuned by the user. In this paper, we propose a principled approach called self-CMA-ES to achieve the online adaptation of CMA-ES hyper-parameters in order to improve its overall performance. Experimental results show that for larger-than-default population size, the default set","authors_text":"Ilya Loshchilov (LIS), INRIA Saclay - Ile de France), Marc Schoenauer (LRI, Mich\\`ele Sebag (LRI), Nikolaus Hansen (INRIA Saclay - Ile de France)","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2014-06-10T16:44:32Z","title":"Maximum Likelihood-based Online Adaptation of Hyper-parameters in CMA-ES"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1406.2623","kind":"arxiv","version":2},"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:b16f51bf5dd9fff3aa20efafcfa64ddc1729f9712e2a0a9f38963ba85db61483","target":"record","created_at":"2026-05-18T02:49:55Z","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":"9e95ef08aa332e711c9916c6120c0de3d501bf5e409e4854c787ff15e41144d6","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2014-06-10T16:44:32Z","title_canon_sha256":"af45ce004435f9de39dccbfedb0d592a2abaf9c9a7368e5b7fe345722e8fbcea"},"schema_version":"1.0","source":{"id":"1406.2623","kind":"arxiv","version":2}},"canonical_sha256":"6344bf220331aef48a3a22b7a64e9aaca7415a9a064486bc6de0b775bed3a7c1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6344bf220331aef48a3a22b7a64e9aaca7415a9a064486bc6de0b775bed3a7c1","first_computed_at":"2026-05-18T02:49:55.367481Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:49:55.367481Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"y0E3ysAwMCdqL7RS9pJiHg5pQBSd9pxECNs73qe5AU32uuxC2EQ44k4jjZa2ABiFhwlNCvxH1X3gjY/BhBxiBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T02:49:55.367952Z","signed_message":"canonical_sha256_bytes"},"source_id":"1406.2623","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b16f51bf5dd9fff3aa20efafcfa64ddc1729f9712e2a0a9f38963ba85db61483","sha256:5fb6d83b238a630efceef62e8e7e1507bc0a11196f03a2e12b612400c753f918"],"state_sha256":"cb315b5da06cf23e12a15c5039ac2301d500e11eb3250b9b9c81665a51b97840"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"reWxn3WbOw6uKToAmEs8H0M5R6QO8SZOU62IQRsuG7XQMV/knNYTnS7kc3FbFiQk0uNvMWTGyJUZ/r3qrGn5Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-09T01:29:40.724962Z","bundle_sha256":"7f21e8c16f7341c6cafeab3017f82ff1bfe5579d9b2237e5e02c3b29b65b6633"}}