{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:SEEUDSXFCWV4PRF3QS367HSC5R","short_pith_number":"pith:SEEUDSXF","schema_version":"1.0","canonical_sha256":"910941cae515abc7c4bb84b7ef9e42ec6be39754eed8beee2b4133fb6e5bb6fa","source":{"kind":"arxiv","id":"1710.07939","version":1},"attestation_state":"computed","paper":{"title":"Elliptical modeling and pattern analysis for perturbation models and classfication","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ML","authors_text":"Shan Suthaharan, Weining Shen","submitted_at":"2017-10-22T13:56:22Z","abstract_excerpt":"The characteristics (or numerical patterns) of a feature vector in the transform domain of a perturbation model differ significantly from those of its corresponding feature vector in the input domain. These differences - caused by the perturbation techniques used for the transformation of feature patterns - degrade the performance of machine learning techniques in the transform domain. In this paper, we proposed a nonlinear parametric perturbation model that transforms the input feature patterns to a set of elliptical patterns, and studied the performance degradation issues associated with ran"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1710.07939","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-10-22T13:56:22Z","cross_cats_sorted":[],"title_canon_sha256":"7ee5ea619940ea8da3c2ac6a566d2f3f36be4062ba61cadf0f3a97e86caf69f3","abstract_canon_sha256":"8b58673457118c9831e2dbdfc5c89ed396e61978bb42f273dd6e1d25ef0ab2d2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:32:19.370739Z","signature_b64":"SC/wejfhBchaw7hNIqrQaTpmTU+l6ns0pUS2Urqas+U02frL3jqCOqkD9h88tHH1uUOEhBXkla9ij1F/p7H2BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"910941cae515abc7c4bb84b7ef9e42ec6be39754eed8beee2b4133fb6e5bb6fa","last_reissued_at":"2026-05-18T00:32:19.370345Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:32:19.370345Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Elliptical modeling and pattern analysis for perturbation models and classfication","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ML","authors_text":"Shan Suthaharan, Weining Shen","submitted_at":"2017-10-22T13:56:22Z","abstract_excerpt":"The characteristics (or numerical patterns) of a feature vector in the transform domain of a perturbation model differ significantly from those of its corresponding feature vector in the input domain. These differences - caused by the perturbation techniques used for the transformation of feature patterns - degrade the performance of machine learning techniques in the transform domain. In this paper, we proposed a nonlinear parametric perturbation model that transforms the input feature patterns to a set of elliptical patterns, and studied the performance degradation issues associated with ran"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.07939","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1710.07939","created_at":"2026-05-18T00:32:19.370399+00:00"},{"alias_kind":"arxiv_version","alias_value":"1710.07939v1","created_at":"2026-05-18T00:32:19.370399+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.07939","created_at":"2026-05-18T00:32:19.370399+00:00"},{"alias_kind":"pith_short_12","alias_value":"SEEUDSXFCWV4","created_at":"2026-05-18T12:31:43.269735+00:00"},{"alias_kind":"pith_short_16","alias_value":"SEEUDSXFCWV4PRF3","created_at":"2026-05-18T12:31:43.269735+00:00"},{"alias_kind":"pith_short_8","alias_value":"SEEUDSXF","created_at":"2026-05-18T12:31:43.269735+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/SEEUDSXFCWV4PRF3QS367HSC5R","json":"https://pith.science/pith/SEEUDSXFCWV4PRF3QS367HSC5R.json","graph_json":"https://pith.science/api/pith-number/SEEUDSXFCWV4PRF3QS367HSC5R/graph.json","events_json":"https://pith.science/api/pith-number/SEEUDSXFCWV4PRF3QS367HSC5R/events.json","paper":"https://pith.science/paper/SEEUDSXF"},"agent_actions":{"view_html":"https://pith.science/pith/SEEUDSXFCWV4PRF3QS367HSC5R","download_json":"https://pith.science/pith/SEEUDSXFCWV4PRF3QS367HSC5R.json","view_paper":"https://pith.science/paper/SEEUDSXF","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1710.07939&json=true","fetch_graph":"https://pith.science/api/pith-number/SEEUDSXFCWV4PRF3QS367HSC5R/graph.json","fetch_events":"https://pith.science/api/pith-number/SEEUDSXFCWV4PRF3QS367HSC5R/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SEEUDSXFCWV4PRF3QS367HSC5R/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SEEUDSXFCWV4PRF3QS367HSC5R/action/storage_attestation","attest_author":"https://pith.science/pith/SEEUDSXFCWV4PRF3QS367HSC5R/action/author_attestation","sign_citation":"https://pith.science/pith/SEEUDSXFCWV4PRF3QS367HSC5R/action/citation_signature","submit_replication":"https://pith.science/pith/SEEUDSXFCWV4PRF3QS367HSC5R/action/replication_record"}},"created_at":"2026-05-18T00:32:19.370399+00:00","updated_at":"2026-05-18T00:32:19.370399+00:00"}