{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2010:JUWECMPEF3VZCWI3OQOUUS7E23","short_pith_number":"pith:JUWECMPE","canonical_record":{"source":{"id":"1005.3681","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2010-05-20T12:39:56Z","cross_cats_sorted":[],"title_canon_sha256":"4347800ee0daae35463921fc3e084525f061399a445c88a553d7c11a7504dc02","abstract_canon_sha256":"157d34eefce427f2cf7938588b309f724d9fed56ce93b814fbef60961583eb89"},"schema_version":"1.0"},"canonical_sha256":"4d2c4131e42eeb91591b741d4a4be4d6e5c375f2fcd26c7df3264cc5f47e1a10","source":{"kind":"arxiv","id":"1005.3681","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1005.3681","created_at":"2026-05-18T04:42:44Z"},{"alias_kind":"arxiv_version","alias_value":"1005.3681v2","created_at":"2026-05-18T04:42:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1005.3681","created_at":"2026-05-18T04:42:44Z"},{"alias_kind":"pith_short_12","alias_value":"JUWECMPEF3VZ","created_at":"2026-05-18T12:26:09Z"},{"alias_kind":"pith_short_16","alias_value":"JUWECMPEF3VZCWI3","created_at":"2026-05-18T12:26:09Z"},{"alias_kind":"pith_short_8","alias_value":"JUWECMPE","created_at":"2026-05-18T12:26:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2010:JUWECMPEF3VZCWI3OQOUUS7E23","target":"record","payload":{"canonical_record":{"source":{"id":"1005.3681","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2010-05-20T12:39:56Z","cross_cats_sorted":[],"title_canon_sha256":"4347800ee0daae35463921fc3e084525f061399a445c88a553d7c11a7504dc02","abstract_canon_sha256":"157d34eefce427f2cf7938588b309f724d9fed56ce93b814fbef60961583eb89"},"schema_version":"1.0"},"canonical_sha256":"4d2c4131e42eeb91591b741d4a4be4d6e5c375f2fcd26c7df3264cc5f47e1a10","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:42:44.438043Z","signature_b64":"Nf6R+QKzOHqXGDNsPByISAS/R8K/YHeNMJhrjOBtUc30FsjvlViKhfw+KDLReTCIIEu1SMSiz1yN1d9z/5f+BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4d2c4131e42eeb91591b741d4a4be4d6e5c375f2fcd26c7df3264cc5f47e1a10","last_reissued_at":"2026-05-18T04:42:44.437290Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:42:44.437290Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1005.3681","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T04:42:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Uy5O1xNIIpildxlNuQt1zw0Laq7Wbx+7tIZRYNQlqTl+PgM5E0NUJNZ/NPS4af/goLE4NT4yY5QzvP44jD6mAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T14:36:30.977714Z"},"content_sha256":"e3b8aaaab50e8955e71b5867ad3199fee91eb079f45cdf780934b4342d6df225","schema_version":"1.0","event_id":"sha256:e3b8aaaab50e8955e71b5867ad3199fee91eb079f45cdf780934b4342d6df225"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2010:JUWECMPEF3VZCWI3OQOUUS7E23","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Kernel-Based Halfspaces with the Zero-One Loss","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Karthik Sridharan, Ohad Shamir, Shai Shalev-Shwartz","submitted_at":"2010-05-20T12:39:56Z","abstract_excerpt":"We describe and analyze a new algorithm for agnostically learning kernel-based halfspaces with respect to the \\emph{zero-one} loss function. Unlike most previous formulations which rely on surrogate convex loss functions (e.g. hinge-loss in SVM and log-loss in logistic regression), we provide finite time/sample guarantees with respect to the more natural zero-one loss function. The proposed algorithm can learn kernel-based halfspaces in worst-case time $\\poly(\\exp(L\\log(L/\\epsilon)))$, for $\\emph{any}$ distribution, where $L$ is a Lipschitz constant (which can be thought of as the reciprocal o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1005.3681","kind":"arxiv","version":2},"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":"2026-05-18T04:42:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"huF/VvJZG1a8ytpLM5qYPRN0TceRj3NYl3zhzuGMRlmVcekutzusHCrWeZZA7iyPhg/2uLyTReU+yc3NcTp3Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T14:36:30.978065Z"},"content_sha256":"15059884839fcf033df235a176d6d35b3641e580d6ec1195a1aeac2b47053d75","schema_version":"1.0","event_id":"sha256:15059884839fcf033df235a176d6d35b3641e580d6ec1195a1aeac2b47053d75"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JUWECMPEF3VZCWI3OQOUUS7E23/bundle.json","state_url":"https://pith.science/pith/JUWECMPEF3VZCWI3OQOUUS7E23/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JUWECMPEF3VZCWI3OQOUUS7E23/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":"2026-05-29T14:36:30Z","links":{"resolver":"https://pith.science/pith/JUWECMPEF3VZCWI3OQOUUS7E23","bundle":"https://pith.science/pith/JUWECMPEF3VZCWI3OQOUUS7E23/bundle.json","state":"https://pith.science/pith/JUWECMPEF3VZCWI3OQOUUS7E23/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JUWECMPEF3VZCWI3OQOUUS7E23/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2010:JUWECMPEF3VZCWI3OQOUUS7E23","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":"157d34eefce427f2cf7938588b309f724d9fed56ce93b814fbef60961583eb89","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2010-05-20T12:39:56Z","title_canon_sha256":"4347800ee0daae35463921fc3e084525f061399a445c88a553d7c11a7504dc02"},"schema_version":"1.0","source":{"id":"1005.3681","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1005.3681","created_at":"2026-05-18T04:42:44Z"},{"alias_kind":"arxiv_version","alias_value":"1005.3681v2","created_at":"2026-05-18T04:42:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1005.3681","created_at":"2026-05-18T04:42:44Z"},{"alias_kind":"pith_short_12","alias_value":"JUWECMPEF3VZ","created_at":"2026-05-18T12:26:09Z"},{"alias_kind":"pith_short_16","alias_value":"JUWECMPEF3VZCWI3","created_at":"2026-05-18T12:26:09Z"},{"alias_kind":"pith_short_8","alias_value":"JUWECMPE","created_at":"2026-05-18T12:26:09Z"}],"graph_snapshots":[{"event_id":"sha256:15059884839fcf033df235a176d6d35b3641e580d6ec1195a1aeac2b47053d75","target":"graph","created_at":"2026-05-18T04:42:44Z","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":"We describe and analyze a new algorithm for agnostically learning kernel-based halfspaces with respect to the \\emph{zero-one} loss function. Unlike most previous formulations which rely on surrogate convex loss functions (e.g. hinge-loss in SVM and log-loss in logistic regression), we provide finite time/sample guarantees with respect to the more natural zero-one loss function. The proposed algorithm can learn kernel-based halfspaces in worst-case time $\\poly(\\exp(L\\log(L/\\epsilon)))$, for $\\emph{any}$ distribution, where $L$ is a Lipschitz constant (which can be thought of as the reciprocal o","authors_text":"Karthik Sridharan, Ohad Shamir, Shai Shalev-Shwartz","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2010-05-20T12:39:56Z","title":"Learning Kernel-Based Halfspaces with the Zero-One Loss"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1005.3681","kind":"arxiv","version":2},"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:e3b8aaaab50e8955e71b5867ad3199fee91eb079f45cdf780934b4342d6df225","target":"record","created_at":"2026-05-18T04:42:44Z","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":"157d34eefce427f2cf7938588b309f724d9fed56ce93b814fbef60961583eb89","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2010-05-20T12:39:56Z","title_canon_sha256":"4347800ee0daae35463921fc3e084525f061399a445c88a553d7c11a7504dc02"},"schema_version":"1.0","source":{"id":"1005.3681","kind":"arxiv","version":2}},"canonical_sha256":"4d2c4131e42eeb91591b741d4a4be4d6e5c375f2fcd26c7df3264cc5f47e1a10","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4d2c4131e42eeb91591b741d4a4be4d6e5c375f2fcd26c7df3264cc5f47e1a10","first_computed_at":"2026-05-18T04:42:44.437290Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T04:42:44.437290Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Nf6R+QKzOHqXGDNsPByISAS/R8K/YHeNMJhrjOBtUc30FsjvlViKhfw+KDLReTCIIEu1SMSiz1yN1d9z/5f+BQ==","signature_status":"signed_v1","signed_at":"2026-05-18T04:42:44.438043Z","signed_message":"canonical_sha256_bytes"},"source_id":"1005.3681","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e3b8aaaab50e8955e71b5867ad3199fee91eb079f45cdf780934b4342d6df225","sha256:15059884839fcf033df235a176d6d35b3641e580d6ec1195a1aeac2b47053d75"],"state_sha256":"67272e51cd96ab9a7b8e789b33ff7ccdbefcba5e7faa93940f6ae7a700f7c57d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0NYRG4LIqzMoocal7/Sg9k5IiCMaSt++sKDeY/upSrT9FHAGI6nzirGGT3c3/qOAk37e6favjot0MBdPsiJoDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-29T14:36:30.980351Z","bundle_sha256":"14791284b0d1f9ffb347ef016de200866b32954158aaa291b3f9e177e7539540"}}