{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:TSPFCXSHNHW7YFSBL3HDHTH47L","short_pith_number":"pith:TSPFCXSH","canonical_record":{"source":{"id":"1301.2115","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2013-01-10T13:29:17Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"003d56f1a0d3a8484f6fd569142a5a582627a7171dbce3ef9e7dc84b671da752","abstract_canon_sha256":"479baf00219404762e682d67ef07f39627029448617f2d1d92971f2191c5ec6d"},"schema_version":"1.0"},"canonical_sha256":"9c9e515e4769edfc16415ece33ccfcfad70cf1c24e86a209f8ec3f789c31a343","source":{"kind":"arxiv","id":"1301.2115","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1301.2115","created_at":"2026-05-18T03:36:47Z"},{"alias_kind":"arxiv_version","alias_value":"1301.2115v1","created_at":"2026-05-18T03:36:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1301.2115","created_at":"2026-05-18T03:36:47Z"},{"alias_kind":"pith_short_12","alias_value":"TSPFCXSHNHW7","created_at":"2026-05-18T12:28:02Z"},{"alias_kind":"pith_short_16","alias_value":"TSPFCXSHNHW7YFSB","created_at":"2026-05-18T12:28:02Z"},{"alias_kind":"pith_short_8","alias_value":"TSPFCXSH","created_at":"2026-05-18T12:28:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:TSPFCXSHNHW7YFSBL3HDHTH47L","target":"record","payload":{"canonical_record":{"source":{"id":"1301.2115","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2013-01-10T13:29:17Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"003d56f1a0d3a8484f6fd569142a5a582627a7171dbce3ef9e7dc84b671da752","abstract_canon_sha256":"479baf00219404762e682d67ef07f39627029448617f2d1d92971f2191c5ec6d"},"schema_version":"1.0"},"canonical_sha256":"9c9e515e4769edfc16415ece33ccfcfad70cf1c24e86a209f8ec3f789c31a343","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:36:47.455151Z","signature_b64":"N+qmMUMpqvGSzDW5uUr2Q4tLZv11/09mylgGWj7NspdyB366aaB6Bl9vO/Fwk7I9lk/PuR3LxwS7sfcm0/VcBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9c9e515e4769edfc16415ece33ccfcfad70cf1c24e86a209f8ec3f789c31a343","last_reissued_at":"2026-05-18T03:36:47.454686Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:36:47.454686Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1301.2115","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":"2026-05-18T03:36:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YPCYZZnuggEmtQysbPk2bx7XavERSlNmW0x0mO5WgR3YTJ8rmhO6rxltEMyJ8/WYoMYF9BaQyFvmB5PINh5GAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T12:56:31.946887Z"},"content_sha256":"3b704eae7ee45b6e6854290c31669b3411de9297f99494b0d957c1f71f23d11f","schema_version":"1.0","event_id":"sha256:3b704eae7ee45b6e6854290c31669b3411de9297f99494b0d957c1f71f23d11f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:TSPFCXSHNHW7YFSBL3HDHTH47L","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Domain Generalization via Invariant Feature Representation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Bernhard Sch\\\"olkopf, David Balduzzi, Krikamol Muandet","submitted_at":"2013-01-10T13:29:17Z","abstract_excerpt":"This paper investigates domain generalization: How to take knowledge acquired from an arbitrary number of related domains and apply it to previously unseen domains? We propose Domain-Invariant Component Analysis (DICA), a kernel-based optimization algorithm that learns an invariant transformation by minimizing the dissimilarity across domains, whilst preserving the functional relationship between input and output variables. A learning-theoretic analysis shows that reducing dissimilarity improves the expected generalization ability of classifiers on new domains, motivating the proposed algorith"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1301.2115","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":"2026-05-18T03:36:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"n40NRGorBBNcp5rg+Sq9IQFikK1ejpN/HO7OSlEBqfhkm6cAntupi83YiPfdMlkkXZaawygeY3QexlwKqH2kCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T12:56:31.947267Z"},"content_sha256":"599f8f950677a30d2a6148a6dc08202205fd80ca1a232153eb535ccf4a86efd5","schema_version":"1.0","event_id":"sha256:599f8f950677a30d2a6148a6dc08202205fd80ca1a232153eb535ccf4a86efd5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TSPFCXSHNHW7YFSBL3HDHTH47L/bundle.json","state_url":"https://pith.science/pith/TSPFCXSHNHW7YFSBL3HDHTH47L/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TSPFCXSHNHW7YFSBL3HDHTH47L/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":"2026-05-26T12:56:31Z","links":{"resolver":"https://pith.science/pith/TSPFCXSHNHW7YFSBL3HDHTH47L","bundle":"https://pith.science/pith/TSPFCXSHNHW7YFSBL3HDHTH47L/bundle.json","state":"https://pith.science/pith/TSPFCXSHNHW7YFSBL3HDHTH47L/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TSPFCXSHNHW7YFSBL3HDHTH47L/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:TSPFCXSHNHW7YFSBL3HDHTH47L","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":"479baf00219404762e682d67ef07f39627029448617f2d1d92971f2191c5ec6d","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2013-01-10T13:29:17Z","title_canon_sha256":"003d56f1a0d3a8484f6fd569142a5a582627a7171dbce3ef9e7dc84b671da752"},"schema_version":"1.0","source":{"id":"1301.2115","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1301.2115","created_at":"2026-05-18T03:36:47Z"},{"alias_kind":"arxiv_version","alias_value":"1301.2115v1","created_at":"2026-05-18T03:36:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1301.2115","created_at":"2026-05-18T03:36:47Z"},{"alias_kind":"pith_short_12","alias_value":"TSPFCXSHNHW7","created_at":"2026-05-18T12:28:02Z"},{"alias_kind":"pith_short_16","alias_value":"TSPFCXSHNHW7YFSB","created_at":"2026-05-18T12:28:02Z"},{"alias_kind":"pith_short_8","alias_value":"TSPFCXSH","created_at":"2026-05-18T12:28:02Z"}],"graph_snapshots":[{"event_id":"sha256:599f8f950677a30d2a6148a6dc08202205fd80ca1a232153eb535ccf4a86efd5","target":"graph","created_at":"2026-05-18T03:36:47Z","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":"This paper investigates domain generalization: How to take knowledge acquired from an arbitrary number of related domains and apply it to previously unseen domains? We propose Domain-Invariant Component Analysis (DICA), a kernel-based optimization algorithm that learns an invariant transformation by minimizing the dissimilarity across domains, whilst preserving the functional relationship between input and output variables. A learning-theoretic analysis shows that reducing dissimilarity improves the expected generalization ability of classifiers on new domains, motivating the proposed algorith","authors_text":"Bernhard Sch\\\"olkopf, David Balduzzi, Krikamol Muandet","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2013-01-10T13:29:17Z","title":"Domain Generalization via Invariant Feature Representation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1301.2115","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":"sha256:3b704eae7ee45b6e6854290c31669b3411de9297f99494b0d957c1f71f23d11f","target":"record","created_at":"2026-05-18T03:36:47Z","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":"479baf00219404762e682d67ef07f39627029448617f2d1d92971f2191c5ec6d","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2013-01-10T13:29:17Z","title_canon_sha256":"003d56f1a0d3a8484f6fd569142a5a582627a7171dbce3ef9e7dc84b671da752"},"schema_version":"1.0","source":{"id":"1301.2115","kind":"arxiv","version":1}},"canonical_sha256":"9c9e515e4769edfc16415ece33ccfcfad70cf1c24e86a209f8ec3f789c31a343","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9c9e515e4769edfc16415ece33ccfcfad70cf1c24e86a209f8ec3f789c31a343","first_computed_at":"2026-05-18T03:36:47.454686Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:36:47.454686Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"N+qmMUMpqvGSzDW5uUr2Q4tLZv11/09mylgGWj7NspdyB366aaB6Bl9vO/Fwk7I9lk/PuR3LxwS7sfcm0/VcBA==","signature_status":"signed_v1","signed_at":"2026-05-18T03:36:47.455151Z","signed_message":"canonical_sha256_bytes"},"source_id":"1301.2115","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3b704eae7ee45b6e6854290c31669b3411de9297f99494b0d957c1f71f23d11f","sha256:599f8f950677a30d2a6148a6dc08202205fd80ca1a232153eb535ccf4a86efd5"],"state_sha256":"d334fcf42ea89e98ab96b20f6d69f9942b24d040b106162d03693b127b0fa9f8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W+5RHVNaLoTh1aq+NnrZSJtHYOSQl9LqVlc1ofP28+pO8pdG29wzWe3CDg8JA5zx7BD0hx5h3ZNFI4QZgbGvAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T12:56:31.950492Z","bundle_sha256":"269477f91a80e1062e66bb0257443c7e591d77ebbfcb1ac6b5d1d250fa24ff27"}}