{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2011:EPYXP7C3UIRSIZDOKBEWJXSGAW","short_pith_number":"pith:EPYXP7C3","canonical_record":{"source":{"id":"1106.6024","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2011-06-29T18:53:46Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"5bfdba21c56128c8a3d46a15597358683ba739a312da176a37baa8b0142f11af","abstract_canon_sha256":"aee60979e9577629795c0620d5bb90ec9c885f30a8dbccd195438053367bc98e"},"schema_version":"1.0"},"canonical_sha256":"23f177fc5ba22324646e504964de4605b1caf5253d2f9fcd7bd5d400b6828d4d","source":{"kind":"arxiv","id":"1106.6024","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1106.6024","created_at":"2026-05-18T04:19:04Z"},{"alias_kind":"arxiv_version","alias_value":"1106.6024v1","created_at":"2026-05-18T04:19:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1106.6024","created_at":"2026-05-18T04:19:04Z"},{"alias_kind":"pith_short_12","alias_value":"EPYXP7C3UIRS","created_at":"2026-05-18T12:26:28Z"},{"alias_kind":"pith_short_16","alias_value":"EPYXP7C3UIRSIZDO","created_at":"2026-05-18T12:26:28Z"},{"alias_kind":"pith_short_8","alias_value":"EPYXP7C3","created_at":"2026-05-18T12:26:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2011:EPYXP7C3UIRSIZDOKBEWJXSGAW","target":"record","payload":{"canonical_record":{"source":{"id":"1106.6024","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2011-06-29T18:53:46Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"5bfdba21c56128c8a3d46a15597358683ba739a312da176a37baa8b0142f11af","abstract_canon_sha256":"aee60979e9577629795c0620d5bb90ec9c885f30a8dbccd195438053367bc98e"},"schema_version":"1.0"},"canonical_sha256":"23f177fc5ba22324646e504964de4605b1caf5253d2f9fcd7bd5d400b6828d4d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:19:04.677939Z","signature_b64":"7aMVMgLZgilfv3tSr8aAZzejdZWE6WG1sJxZ6bXxybpR8rqtNMY3TXooeGs1rSnEJz2nIhawZrMg6VhVpI0XCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"23f177fc5ba22324646e504964de4605b1caf5253d2f9fcd7bd5d400b6828d4d","last_reissued_at":"2026-05-18T04:19:04.677537Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:19:04.677537Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1106.6024","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":"2026-05-18T04:19:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"k397wXTlT73JuUVEnausHp5idmJiWgNEY6JI/yP4fS2CPXayBH7cX5UxPsDIquzSbzSdiU9+F8FqBl5Ec63TCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T18:00:51.165622Z"},"content_sha256":"d8de30348178519810ad957af9a978c9c77dc4a4e19ad0008548c63e28c4aa5c","schema_version":"1.0","event_id":"sha256:d8de30348178519810ad957af9a978c9c77dc4a4e19ad0008548c63e28c4aa5c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2011:EPYXP7C3UIRSIZDOKBEWJXSGAW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"The Rate of Convergence of AdaBoost","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"math.OC","authors_text":"Cynthia Rudin, Indraneel Mukherjee, Robert E. Schapire","submitted_at":"2011-06-29T18:53:46Z","abstract_excerpt":"The AdaBoost algorithm was designed to combine many \"weak\" hypotheses that perform slightly better than random guessing into a \"strong\" hypothesis that has very low error. We study the rate at which AdaBoost iteratively converges to the minimum of the \"exponential loss.\" Unlike previous work, our proofs do not require a weak-learning assumption, nor do they require that minimizers of the exponential loss are finite. Our first result shows that at iteration $t$, the exponential loss of AdaBoost's computed parameter vector will be at most $\\epsilon$ more than that of any parameter vector of $\\el"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1106.6024","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":"2026-05-18T04:19:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"asT6Q+J1OCDPt1bl8p9nlimtRwF33jWKp6JnjWsnKtC3GYouuBO6E0HSceqhEj9Ic9lDX6If5hZmDlDUl+yRDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T18:00:51.166358Z"},"content_sha256":"2b6355e11431bb1033ecd62ac98fbf7ad36cea21de57af7677dc6c30680a2b36","schema_version":"1.0","event_id":"sha256:2b6355e11431bb1033ecd62ac98fbf7ad36cea21de57af7677dc6c30680a2b36"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EPYXP7C3UIRSIZDOKBEWJXSGAW/bundle.json","state_url":"https://pith.science/pith/EPYXP7C3UIRSIZDOKBEWJXSGAW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EPYXP7C3UIRSIZDOKBEWJXSGAW/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":"2026-06-08T18:00:51Z","links":{"resolver":"https://pith.science/pith/EPYXP7C3UIRSIZDOKBEWJXSGAW","bundle":"https://pith.science/pith/EPYXP7C3UIRSIZDOKBEWJXSGAW/bundle.json","state":"https://pith.science/pith/EPYXP7C3UIRSIZDOKBEWJXSGAW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EPYXP7C3UIRSIZDOKBEWJXSGAW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2011:EPYXP7C3UIRSIZDOKBEWJXSGAW","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":"aee60979e9577629795c0620d5bb90ec9c885f30a8dbccd195438053367bc98e","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2011-06-29T18:53:46Z","title_canon_sha256":"5bfdba21c56128c8a3d46a15597358683ba739a312da176a37baa8b0142f11af"},"schema_version":"1.0","source":{"id":"1106.6024","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1106.6024","created_at":"2026-05-18T04:19:04Z"},{"alias_kind":"arxiv_version","alias_value":"1106.6024v1","created_at":"2026-05-18T04:19:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1106.6024","created_at":"2026-05-18T04:19:04Z"},{"alias_kind":"pith_short_12","alias_value":"EPYXP7C3UIRS","created_at":"2026-05-18T12:26:28Z"},{"alias_kind":"pith_short_16","alias_value":"EPYXP7C3UIRSIZDO","created_at":"2026-05-18T12:26:28Z"},{"alias_kind":"pith_short_8","alias_value":"EPYXP7C3","created_at":"2026-05-18T12:26:28Z"}],"graph_snapshots":[{"event_id":"sha256:2b6355e11431bb1033ecd62ac98fbf7ad36cea21de57af7677dc6c30680a2b36","target":"graph","created_at":"2026-05-18T04:19:04Z","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":"The AdaBoost algorithm was designed to combine many \"weak\" hypotheses that perform slightly better than random guessing into a \"strong\" hypothesis that has very low error. We study the rate at which AdaBoost iteratively converges to the minimum of the \"exponential loss.\" Unlike previous work, our proofs do not require a weak-learning assumption, nor do they require that minimizers of the exponential loss are finite. Our first result shows that at iteration $t$, the exponential loss of AdaBoost's computed parameter vector will be at most $\\epsilon$ more than that of any parameter vector of $\\el","authors_text":"Cynthia Rudin, Indraneel Mukherjee, Robert E. Schapire","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2011-06-29T18:53:46Z","title":"The Rate of Convergence of AdaBoost"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1106.6024","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:d8de30348178519810ad957af9a978c9c77dc4a4e19ad0008548c63e28c4aa5c","target":"record","created_at":"2026-05-18T04:19:04Z","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":"aee60979e9577629795c0620d5bb90ec9c885f30a8dbccd195438053367bc98e","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2011-06-29T18:53:46Z","title_canon_sha256":"5bfdba21c56128c8a3d46a15597358683ba739a312da176a37baa8b0142f11af"},"schema_version":"1.0","source":{"id":"1106.6024","kind":"arxiv","version":1}},"canonical_sha256":"23f177fc5ba22324646e504964de4605b1caf5253d2f9fcd7bd5d400b6828d4d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"23f177fc5ba22324646e504964de4605b1caf5253d2f9fcd7bd5d400b6828d4d","first_computed_at":"2026-05-18T04:19:04.677537Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T04:19:04.677537Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7aMVMgLZgilfv3tSr8aAZzejdZWE6WG1sJxZ6bXxybpR8rqtNMY3TXooeGs1rSnEJz2nIhawZrMg6VhVpI0XCw==","signature_status":"signed_v1","signed_at":"2026-05-18T04:19:04.677939Z","signed_message":"canonical_sha256_bytes"},"source_id":"1106.6024","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d8de30348178519810ad957af9a978c9c77dc4a4e19ad0008548c63e28c4aa5c","sha256:2b6355e11431bb1033ecd62ac98fbf7ad36cea21de57af7677dc6c30680a2b36"],"state_sha256":"6d3e3fcddb0a4d0e5100a088af540ac354438f798088acb722c1abc95eca1bf4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d8/drLAmp0DnWSmA6uQc1oDMjviKd2r7qeIqPiRpAZvbSPHWBFP/9frw+hVTVyyKNXzXvGPtEN1V1XDZUWVmCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-08T18:00:51.170419Z","bundle_sha256":"86bb92a1b614011388f9e905b00ae0258966cd38ead8792921bc295183851e20"}}