{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:RBUID2WJIIS6CI66BI4EZXAW5I","short_pith_number":"pith:RBUID2WJ","canonical_record":{"source":{"id":"1703.02570","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2017-03-07T19:47:22Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"05299cd7ac5d5f442f6265c8ff2e808fbf8af145548aa4ec6bc1acd977771130","abstract_canon_sha256":"29b7aed64fc8a681009767894ff3bd7658ae052d6f24695b04978a3849471510"},"schema_version":"1.0"},"canonical_sha256":"886881eac94225e123de0a384cdc16ea201854b9c75a4099560d86edafb2c0ea","source":{"kind":"arxiv","id":"1703.02570","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.02570","created_at":"2026-05-18T00:49:06Z"},{"alias_kind":"arxiv_version","alias_value":"1703.02570v1","created_at":"2026-05-18T00:49:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.02570","created_at":"2026-05-18T00:49:06Z"},{"alias_kind":"pith_short_12","alias_value":"RBUID2WJIIS6","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_16","alias_value":"RBUID2WJIIS6CI66","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_8","alias_value":"RBUID2WJ","created_at":"2026-05-18T12:31:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:RBUID2WJIIS6CI66BI4EZXAW5I","target":"record","payload":{"canonical_record":{"source":{"id":"1703.02570","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2017-03-07T19:47:22Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"05299cd7ac5d5f442f6265c8ff2e808fbf8af145548aa4ec6bc1acd977771130","abstract_canon_sha256":"29b7aed64fc8a681009767894ff3bd7658ae052d6f24695b04978a3849471510"},"schema_version":"1.0"},"canonical_sha256":"886881eac94225e123de0a384cdc16ea201854b9c75a4099560d86edafb2c0ea","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:49:06.128216Z","signature_b64":"5ThBeymQuWDVsgDWShWCCeqFHc34KuUCyxwbE4ZQ416OLm54DOJYZB61CONsl2rnRyJKQudbhjkFXYhdYqbyAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"886881eac94225e123de0a384cdc16ea201854b9c75a4099560d86edafb2c0ea","last_reissued_at":"2026-05-18T00:49:06.127804Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:49:06.127804Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1703.02570","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":"2026-05-18T00:49:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BRHJiKD9IsyLDrN9BUSI6vbeiJZad2iX4fliCOoJ6HJdaH/eq5p53eXOe9XVo9yTbqgx42HDRqfBWQYlskJHBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T19:20:41.649890Z"},"content_sha256":"3fc31b6195cba5bab780473c44b1b70c01b1ea574b068d3ff1c267cab300f415","schema_version":"1.0","event_id":"sha256:3fc31b6195cba5bab780473c44b1b70c01b1ea574b068d3ff1c267cab300f415"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:RBUID2WJIIS6CI66BI4EZXAW5I","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Regularising Non-linear Models Using Feature Side-information","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Alexandros Kalousis, Amina Mollaysa, Pablo Strasser","submitted_at":"2017-03-07T19:47:22Z","abstract_excerpt":"Very often features come with their own vectorial descriptions which provide detailed information about their properties. We refer to these vectorial descriptions as feature side-information. In the standard learning scenario, input is represented as a vector of features and the feature side-information is most often ignored or used only for feature selection prior to model fitting. We believe that feature side-information which carries information about features intrinsic property will help improve model prediction if used in a proper way during learning process. In this paper, we propose a f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.02570","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":"2026-05-18T00:49:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"igomc5x3ntQNQlWa8bZOmKZaRKL74fdtpKj1edwUQioCDx+0mfh3adxg1+0JyUepTNFuFhatxvc0wfhDEM3YBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T19:20:41.650603Z"},"content_sha256":"4f9aaa88c1acf2be3946e73f32d72e6a550e4cc3e40e177315f172d64ab78738","schema_version":"1.0","event_id":"sha256:4f9aaa88c1acf2be3946e73f32d72e6a550e4cc3e40e177315f172d64ab78738"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RBUID2WJIIS6CI66BI4EZXAW5I/bundle.json","state_url":"https://pith.science/pith/RBUID2WJIIS6CI66BI4EZXAW5I/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RBUID2WJIIS6CI66BI4EZXAW5I/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":"2026-06-09T19:20:41Z","links":{"resolver":"https://pith.science/pith/RBUID2WJIIS6CI66BI4EZXAW5I","bundle":"https://pith.science/pith/RBUID2WJIIS6CI66BI4EZXAW5I/bundle.json","state":"https://pith.science/pith/RBUID2WJIIS6CI66BI4EZXAW5I/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RBUID2WJIIS6CI66BI4EZXAW5I/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:RBUID2WJIIS6CI66BI4EZXAW5I","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":"29b7aed64fc8a681009767894ff3bd7658ae052d6f24695b04978a3849471510","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2017-03-07T19:47:22Z","title_canon_sha256":"05299cd7ac5d5f442f6265c8ff2e808fbf8af145548aa4ec6bc1acd977771130"},"schema_version":"1.0","source":{"id":"1703.02570","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.02570","created_at":"2026-05-18T00:49:06Z"},{"alias_kind":"arxiv_version","alias_value":"1703.02570v1","created_at":"2026-05-18T00:49:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.02570","created_at":"2026-05-18T00:49:06Z"},{"alias_kind":"pith_short_12","alias_value":"RBUID2WJIIS6","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_16","alias_value":"RBUID2WJIIS6CI66","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_8","alias_value":"RBUID2WJ","created_at":"2026-05-18T12:31:39Z"}],"graph_snapshots":[{"event_id":"sha256:4f9aaa88c1acf2be3946e73f32d72e6a550e4cc3e40e177315f172d64ab78738","target":"graph","created_at":"2026-05-18T00:49:06Z","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":"Very often features come with their own vectorial descriptions which provide detailed information about their properties. We refer to these vectorial descriptions as feature side-information. In the standard learning scenario, input is represented as a vector of features and the feature side-information is most often ignored or used only for feature selection prior to model fitting. We believe that feature side-information which carries information about features intrinsic property will help improve model prediction if used in a proper way during learning process. In this paper, we propose a f","authors_text":"Alexandros Kalousis, Amina Mollaysa, Pablo Strasser","cross_cats":["stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2017-03-07T19:47:22Z","title":"Regularising Non-linear Models Using Feature Side-information"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.02570","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":"sha256:3fc31b6195cba5bab780473c44b1b70c01b1ea574b068d3ff1c267cab300f415","target":"record","created_at":"2026-05-18T00:49:06Z","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":"29b7aed64fc8a681009767894ff3bd7658ae052d6f24695b04978a3849471510","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2017-03-07T19:47:22Z","title_canon_sha256":"05299cd7ac5d5f442f6265c8ff2e808fbf8af145548aa4ec6bc1acd977771130"},"schema_version":"1.0","source":{"id":"1703.02570","kind":"arxiv","version":1}},"canonical_sha256":"886881eac94225e123de0a384cdc16ea201854b9c75a4099560d86edafb2c0ea","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"886881eac94225e123de0a384cdc16ea201854b9c75a4099560d86edafb2c0ea","first_computed_at":"2026-05-18T00:49:06.127804Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:49:06.127804Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5ThBeymQuWDVsgDWShWCCeqFHc34KuUCyxwbE4ZQ416OLm54DOJYZB61CONsl2rnRyJKQudbhjkFXYhdYqbyAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:49:06.128216Z","signed_message":"canonical_sha256_bytes"},"source_id":"1703.02570","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3fc31b6195cba5bab780473c44b1b70c01b1ea574b068d3ff1c267cab300f415","sha256:4f9aaa88c1acf2be3946e73f32d72e6a550e4cc3e40e177315f172d64ab78738"],"state_sha256":"0545b16120fb14b1929672b8d454303853f5b33ddf0b06f2d3345febdc8f6e7a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ila8+6AtQraD5Ra6FV0OU1pj7hdpDK8YpqJy12ADT96NJXYmhNo51XRyHw0NoSBpHRtGfee3Gi1I2rzkbyrHDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-09T19:20:41.654876Z","bundle_sha256":"983207763294a18dfee514bf295efd755bf67b40513c4882e71be260a4f63022"}}