{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:UCFHU65Z4KUKBK4HLCSFGJ6FS5","short_pith_number":"pith:UCFHU65Z","canonical_record":{"source":{"id":"1910.00270","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-10-01T09:27:33Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"94b3f096afe08f3a1150b502d39d9a361878ced44a6b92e5ebe3fe651e24f176","abstract_canon_sha256":"8c5b65593b4c21e30e2375f90df8ceadc8d3248225b46c21db762405a8922fac"},"schema_version":"1.0"},"canonical_sha256":"a08a7a7bb9e2a8a0ab8758a45327c59758ec67e8a1ec4107d69c4e87e5d896dc","source":{"kind":"arxiv","id":"1910.00270","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.00270","created_at":"2026-07-05T01:17:58Z"},{"alias_kind":"arxiv_version","alias_value":"1910.00270v4","created_at":"2026-07-05T01:17:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.00270","created_at":"2026-07-05T01:17:58Z"},{"alias_kind":"pith_short_12","alias_value":"UCFHU65Z4KUK","created_at":"2026-07-05T01:17:58Z"},{"alias_kind":"pith_short_16","alias_value":"UCFHU65Z4KUKBK4H","created_at":"2026-07-05T01:17:58Z"},{"alias_kind":"pith_short_8","alias_value":"UCFHU65Z","created_at":"2026-07-05T01:17:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:UCFHU65Z4KUKBK4HLCSFGJ6FS5","target":"record","payload":{"canonical_record":{"source":{"id":"1910.00270","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-10-01T09:27:33Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"94b3f096afe08f3a1150b502d39d9a361878ced44a6b92e5ebe3fe651e24f176","abstract_canon_sha256":"8c5b65593b4c21e30e2375f90df8ceadc8d3248225b46c21db762405a8922fac"},"schema_version":"1.0"},"canonical_sha256":"a08a7a7bb9e2a8a0ab8758a45327c59758ec67e8a1ec4107d69c4e87e5d896dc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:17:58.194216Z","signature_b64":"3Dm+HJN1Jzsp97VhjxWtUCI0q1ETVy4o9CAZUhhHtTxQMs3FZn39vWnWEd27tp+7tDFel2EnBMVmbhsepi4SBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a08a7a7bb9e2a8a0ab8758a45327c59758ec67e8a1ec4107d69c4e87e5d896dc","last_reissued_at":"2026-07-05T01:17:58.193819Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:17:58.193819Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1910.00270","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:17:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ycafnt3hFX9addAfdVnnF2Z0jBfcCp5bKnrHIivxwZm7okUCe46InZrhJRIUN4uKE+yaXenr5FbNW4uEKkT5CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:54:39.035065Z"},"content_sha256":"bdf1dd47e30dba0ae0b566ebb3261759a9679b8e6a41669c2883aa99d1f8b509","schema_version":"1.0","event_id":"sha256:bdf1dd47e30dba0ae0b566ebb3261759a9679b8e6a41669c2883aa99d1f8b509"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:UCFHU65Z4KUKBK4HLCSFGJ6FS5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Robust Learning with the Hilbert-Schmidt Independence Criterion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Daniel Greenfeld, Uri Shalit","submitted_at":"2019-10-01T09:27:33Z","abstract_excerpt":"We investigate the use of a non-parametric independence measure, the Hilbert-Schmidt Independence Criterion (HSIC), as a loss-function for learning robust regression and classification models. This loss-function encourages learning models where the distribution of the residuals between the label and the model prediction is statistically independent of the distribution of the instances themselves. This loss-function was first proposed by Mooij et al. (2009) in the context of learning causal graphs. We adapt it to the task of learning for unsupervised covariate shift: learning on a source domain"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.00270","kind":"arxiv","version":4},"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/1910.00270/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":"2026-07-05T01:17:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CPhuEDVdp5/MAEUwGWOhyh1Zun0sHGEorY6J6V7zC7I4ZNL2RtCip+KdfJxv1IwPpPgd/528MHdzffXRk55qDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:54:39.035590Z"},"content_sha256":"0b8f2b939cd123577cc2044c6fdf71bb737bcce2c36ed16a26f623b6a2c8f0cc","schema_version":"1.0","event_id":"sha256:0b8f2b939cd123577cc2044c6fdf71bb737bcce2c36ed16a26f623b6a2c8f0cc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UCFHU65Z4KUKBK4HLCSFGJ6FS5/bundle.json","state_url":"https://pith.science/pith/UCFHU65Z4KUKBK4HLCSFGJ6FS5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UCFHU65Z4KUKBK4HLCSFGJ6FS5/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":"2026-07-07T04:54:39Z","links":{"resolver":"https://pith.science/pith/UCFHU65Z4KUKBK4HLCSFGJ6FS5","bundle":"https://pith.science/pith/UCFHU65Z4KUKBK4HLCSFGJ6FS5/bundle.json","state":"https://pith.science/pith/UCFHU65Z4KUKBK4HLCSFGJ6FS5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UCFHU65Z4KUKBK4HLCSFGJ6FS5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:UCFHU65Z4KUKBK4HLCSFGJ6FS5","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":"8c5b65593b4c21e30e2375f90df8ceadc8d3248225b46c21db762405a8922fac","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-10-01T09:27:33Z","title_canon_sha256":"94b3f096afe08f3a1150b502d39d9a361878ced44a6b92e5ebe3fe651e24f176"},"schema_version":"1.0","source":{"id":"1910.00270","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.00270","created_at":"2026-07-05T01:17:58Z"},{"alias_kind":"arxiv_version","alias_value":"1910.00270v4","created_at":"2026-07-05T01:17:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.00270","created_at":"2026-07-05T01:17:58Z"},{"alias_kind":"pith_short_12","alias_value":"UCFHU65Z4KUK","created_at":"2026-07-05T01:17:58Z"},{"alias_kind":"pith_short_16","alias_value":"UCFHU65Z4KUKBK4H","created_at":"2026-07-05T01:17:58Z"},{"alias_kind":"pith_short_8","alias_value":"UCFHU65Z","created_at":"2026-07-05T01:17:58Z"}],"graph_snapshots":[{"event_id":"sha256:0b8f2b939cd123577cc2044c6fdf71bb737bcce2c36ed16a26f623b6a2c8f0cc","target":"graph","created_at":"2026-07-05T01:17:58Z","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/1910.00270/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We investigate the use of a non-parametric independence measure, the Hilbert-Schmidt Independence Criterion (HSIC), as a loss-function for learning robust regression and classification models. This loss-function encourages learning models where the distribution of the residuals between the label and the model prediction is statistically independent of the distribution of the instances themselves. This loss-function was first proposed by Mooij et al. (2009) in the context of learning causal graphs. We adapt it to the task of learning for unsupervised covariate shift: learning on a source domain","authors_text":"Daniel Greenfeld, Uri Shalit","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-10-01T09:27:33Z","title":"Robust Learning with the Hilbert-Schmidt Independence Criterion"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.00270","kind":"arxiv","version":4},"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:bdf1dd47e30dba0ae0b566ebb3261759a9679b8e6a41669c2883aa99d1f8b509","target":"record","created_at":"2026-07-05T01:17:58Z","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":"8c5b65593b4c21e30e2375f90df8ceadc8d3248225b46c21db762405a8922fac","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-10-01T09:27:33Z","title_canon_sha256":"94b3f096afe08f3a1150b502d39d9a361878ced44a6b92e5ebe3fe651e24f176"},"schema_version":"1.0","source":{"id":"1910.00270","kind":"arxiv","version":4}},"canonical_sha256":"a08a7a7bb9e2a8a0ab8758a45327c59758ec67e8a1ec4107d69c4e87e5d896dc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a08a7a7bb9e2a8a0ab8758a45327c59758ec67e8a1ec4107d69c4e87e5d896dc","first_computed_at":"2026-07-05T01:17:58.193819Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:17:58.193819Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3Dm+HJN1Jzsp97VhjxWtUCI0q1ETVy4o9CAZUhhHtTxQMs3FZn39vWnWEd27tp+7tDFel2EnBMVmbhsepi4SBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:17:58.194216Z","signed_message":"canonical_sha256_bytes"},"source_id":"1910.00270","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bdf1dd47e30dba0ae0b566ebb3261759a9679b8e6a41669c2883aa99d1f8b509","sha256:0b8f2b939cd123577cc2044c6fdf71bb737bcce2c36ed16a26f623b6a2c8f0cc"],"state_sha256":"728c4865dcbe3a34d3eeaa4ab819644cf03fb495a64406f3e7458835de557997"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c14AC1JdbaJ/V5E6U6Ebp8IhrrR7EpAbBQ4+yQz6DQsxhKszKWyKxSmdEMnssxt5o0lYXl6V31/q9lr0OHo7BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T04:54:39.037952Z","bundle_sha256":"c3ea82b83fa568cc6d1e63dedacc59ff5e2d4ad1e9f31ab1fbb6cfc17d0c492a"}}