{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:EMYJBRDEBWULVIUKV3NKFJUA2N","short_pith_number":"pith:EMYJBRDE","canonical_record":{"source":{"id":"2211.06780","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-11-13T01:19:06Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"b8eb7b866313e80d4496470dd8da510fe05dbf9f18ae0d6cdba65ab4824fbe55","abstract_canon_sha256":"bc9c379add837c32f515f0a9841d959ac45a07c05f15ed2efd829d04f1a1c9a6"},"schema_version":"1.0"},"canonical_sha256":"233090c4640da8baa28aaedaa2a680d35b877e734d8515aafb365ad94677ad57","source":{"kind":"arxiv","id":"2211.06780","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.06780","created_at":"2026-07-05T05:15:45Z"},{"alias_kind":"arxiv_version","alias_value":"2211.06780v1","created_at":"2026-07-05T05:15:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.06780","created_at":"2026-07-05T05:15:45Z"},{"alias_kind":"pith_short_12","alias_value":"EMYJBRDEBWUL","created_at":"2026-07-05T05:15:45Z"},{"alias_kind":"pith_short_16","alias_value":"EMYJBRDEBWULVIUK","created_at":"2026-07-05T05:15:45Z"},{"alias_kind":"pith_short_8","alias_value":"EMYJBRDE","created_at":"2026-07-05T05:15:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:EMYJBRDEBWULVIUKV3NKFJUA2N","target":"record","payload":{"canonical_record":{"source":{"id":"2211.06780","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-11-13T01:19:06Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"b8eb7b866313e80d4496470dd8da510fe05dbf9f18ae0d6cdba65ab4824fbe55","abstract_canon_sha256":"bc9c379add837c32f515f0a9841d959ac45a07c05f15ed2efd829d04f1a1c9a6"},"schema_version":"1.0"},"canonical_sha256":"233090c4640da8baa28aaedaa2a680d35b877e734d8515aafb365ad94677ad57","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:15:45.424500Z","signature_b64":"VB7RE+63v3imyzpw5MlTzyfSCEEbiUN2of1PoGePuf8XGksyjAI/V6vRHa2Ycg1WHFqaW+dQI6WonhsZci04Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"233090c4640da8baa28aaedaa2a680d35b877e734d8515aafb365ad94677ad57","last_reissued_at":"2026-07-05T05:15:45.424021Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:15:45.424021Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2211.06780","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":"2026-07-05T05:15:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SZUTk5xbpS8ENccSRIyOcyFSpPArgWthAoO5W72FHrEWSDnp4KfWipwmZk3ZEE9D1kNdRnSYSeTONGntsGekCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T18:03:12.853943Z"},"content_sha256":"5ee16ef26fb1c06af9f004af8e59efd6c2e12132e2b78468118f9f349b268f6a","schema_version":"1.0","event_id":"sha256:5ee16ef26fb1c06af9f004af8e59efd6c2e12132e2b78468118f9f349b268f6a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:EMYJBRDEBWULVIUKV3NKFJUA2N","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Inv-SENnet: Invariant Self Expression Network for clustering under biased data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Aria Masoomi, Ashish Singh, Ashutosh Singh, Deniz Erdogmus, Erik Learned-Miller, Tales Imbiriba","submitted_at":"2022-11-13T01:19:06Z","abstract_excerpt":"Subspace clustering algorithms are used for understanding the cluster structure that explains the dataset well. These methods are extensively used for data-exploration tasks in various areas of Natural Sciences. However, most of these methods fail to handle unwanted biases in datasets. For datasets where a data sample represents multiple attributes, naively applying any clustering approach can result in undesired output. To this end, we propose a novel framework for jointly removing unwanted attributes (biases) while learning to cluster data points in individual subspaces. Assuming we have inf"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.06780","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/2211.06780/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":"2026-07-05T05:15:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rmfWGozKIS13Hu+dk4JQMdLXhZps+mRsa5hIIw+3aSUBswq3TvNLyJmE4CmfcOjRRjotMyHTViohjgzemv7pCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T18:03:12.854268Z"},"content_sha256":"9989cc3c98b80dd4e70f80a96d8655519f01e2f48312b7426cadd9d0f39e13f2","schema_version":"1.0","event_id":"sha256:9989cc3c98b80dd4e70f80a96d8655519f01e2f48312b7426cadd9d0f39e13f2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EMYJBRDEBWULVIUKV3NKFJUA2N/bundle.json","state_url":"https://pith.science/pith/EMYJBRDEBWULVIUKV3NKFJUA2N/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EMYJBRDEBWULVIUKV3NKFJUA2N/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":"2026-08-22T18:03:12Z","links":{"resolver":"https://pith.science/pith/EMYJBRDEBWULVIUKV3NKFJUA2N","bundle":"https://pith.science/pith/EMYJBRDEBWULVIUKV3NKFJUA2N/bundle.json","state":"https://pith.science/pith/EMYJBRDEBWULVIUKV3NKFJUA2N/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EMYJBRDEBWULVIUKV3NKFJUA2N/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:EMYJBRDEBWULVIUKV3NKFJUA2N","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":"bc9c379add837c32f515f0a9841d959ac45a07c05f15ed2efd829d04f1a1c9a6","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-11-13T01:19:06Z","title_canon_sha256":"b8eb7b866313e80d4496470dd8da510fe05dbf9f18ae0d6cdba65ab4824fbe55"},"schema_version":"1.0","source":{"id":"2211.06780","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.06780","created_at":"2026-07-05T05:15:45Z"},{"alias_kind":"arxiv_version","alias_value":"2211.06780v1","created_at":"2026-07-05T05:15:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.06780","created_at":"2026-07-05T05:15:45Z"},{"alias_kind":"pith_short_12","alias_value":"EMYJBRDEBWUL","created_at":"2026-07-05T05:15:45Z"},{"alias_kind":"pith_short_16","alias_value":"EMYJBRDEBWULVIUK","created_at":"2026-07-05T05:15:45Z"},{"alias_kind":"pith_short_8","alias_value":"EMYJBRDE","created_at":"2026-07-05T05:15:45Z"}],"graph_snapshots":[{"event_id":"sha256:9989cc3c98b80dd4e70f80a96d8655519f01e2f48312b7426cadd9d0f39e13f2","target":"graph","created_at":"2026-07-05T05:15:45Z","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/2211.06780/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Subspace clustering algorithms are used for understanding the cluster structure that explains the dataset well. These methods are extensively used for data-exploration tasks in various areas of Natural Sciences. However, most of these methods fail to handle unwanted biases in datasets. For datasets where a data sample represents multiple attributes, naively applying any clustering approach can result in undesired output. To this end, we propose a novel framework for jointly removing unwanted attributes (biases) while learning to cluster data points in individual subspaces. Assuming we have inf","authors_text":"Aria Masoomi, Ashish Singh, Ashutosh Singh, Deniz Erdogmus, Erik Learned-Miller, Tales Imbiriba","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-11-13T01:19:06Z","title":"Inv-SENnet: Invariant Self Expression Network for clustering under biased data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.06780","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":"sha256:5ee16ef26fb1c06af9f004af8e59efd6c2e12132e2b78468118f9f349b268f6a","target":"record","created_at":"2026-07-05T05:15:45Z","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":"bc9c379add837c32f515f0a9841d959ac45a07c05f15ed2efd829d04f1a1c9a6","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-11-13T01:19:06Z","title_canon_sha256":"b8eb7b866313e80d4496470dd8da510fe05dbf9f18ae0d6cdba65ab4824fbe55"},"schema_version":"1.0","source":{"id":"2211.06780","kind":"arxiv","version":1}},"canonical_sha256":"233090c4640da8baa28aaedaa2a680d35b877e734d8515aafb365ad94677ad57","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"233090c4640da8baa28aaedaa2a680d35b877e734d8515aafb365ad94677ad57","first_computed_at":"2026-07-05T05:15:45.424021Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:15:45.424021Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VB7RE+63v3imyzpw5MlTzyfSCEEbiUN2of1PoGePuf8XGksyjAI/V6vRHa2Ycg1WHFqaW+dQI6WonhsZci04Aw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:15:45.424500Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.06780","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5ee16ef26fb1c06af9f004af8e59efd6c2e12132e2b78468118f9f349b268f6a","sha256:9989cc3c98b80dd4e70f80a96d8655519f01e2f48312b7426cadd9d0f39e13f2"],"state_sha256":"b39b7d88a4060fad8d38f4ae5eb61297713d202d3738d086e0085332ea6f4e4d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yGb6I+YzfmLFtDmrpk8UV/EckNH63dVVIKW5eL9hd6UgsjpDdGUcMqfFJmjLDZgZs0Ql0Myp+g/Mrarr3e9IAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T18:03:12.857511Z","bundle_sha256":"bf2a69e1fc251cf3f6a1bdb9b52dd960942966508c97fd91c714a6fab28697c1"}}