{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2010:CBNUKUZONHGEWYFGTNY5ZVOIPS","short_pith_number":"pith:CBNUKUZO","canonical_record":{"source":{"id":"1009.3896","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2010-09-20T17:35:35Z","cross_cats_sorted":[],"title_canon_sha256":"b3b877ab54e55d2c9ca0b81b77ad77cdfac9d8322f25320792ecd43802d6ad51","abstract_canon_sha256":"c0ab938b5117345707810e965bb97251487baa17ec4463240b979e73dada4580"},"schema_version":"1.0"},"canonical_sha256":"105b45532e69cc4b60a69b71dcd5c87c9ed67582a1b42252d00f79dc48e6ee3d","source":{"kind":"arxiv","id":"1009.3896","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1009.3896","created_at":"2026-05-18T03:40:03Z"},{"alias_kind":"arxiv_version","alias_value":"1009.3896v2","created_at":"2026-05-18T03:40:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1009.3896","created_at":"2026-05-18T03:40:03Z"},{"alias_kind":"pith_short_12","alias_value":"CBNUKUZONHGE","created_at":"2026-05-18T12:26:05Z"},{"alias_kind":"pith_short_16","alias_value":"CBNUKUZONHGEWYFG","created_at":"2026-05-18T12:26:05Z"},{"alias_kind":"pith_short_8","alias_value":"CBNUKUZO","created_at":"2026-05-18T12:26:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2010:CBNUKUZONHGEWYFGTNY5ZVOIPS","target":"record","payload":{"canonical_record":{"source":{"id":"1009.3896","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2010-09-20T17:35:35Z","cross_cats_sorted":[],"title_canon_sha256":"b3b877ab54e55d2c9ca0b81b77ad77cdfac9d8322f25320792ecd43802d6ad51","abstract_canon_sha256":"c0ab938b5117345707810e965bb97251487baa17ec4463240b979e73dada4580"},"schema_version":"1.0"},"canonical_sha256":"105b45532e69cc4b60a69b71dcd5c87c9ed67582a1b42252d00f79dc48e6ee3d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:40:03.620021Z","signature_b64":"9d8RnrwG4zHBDHYIChK/duG+w263pb9u5InajdJmGVGfYVpgnRNPeN+ZsQitgQI+UNQvT4Zt+e3SqxVRTOmUAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"105b45532e69cc4b60a69b71dcd5c87c9ed67582a1b42252d00f79dc48e6ee3d","last_reissued_at":"2026-05-18T03:40:03.619264Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:40:03.619264Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1009.3896","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":"2026-05-18T03:40:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"scJt/W2bcmA1hxMfUeFxX6R7PDPFhU4eumHoNlWKb+gc0mKTVh8fdCOAy0KkMNOpbdRjhdBKNuKIi+e8bMMRAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T09:20:27.960481Z"},"content_sha256":"16bd2c53f2d020d3229ad6d8dbe4ea2c158e337c214de3e1b597493b1eadf52f","schema_version":"1.0","event_id":"sha256:16bd2c53f2d020d3229ad6d8dbe4ea2c158e337c214de3e1b597493b1eadf52f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2010:CBNUKUZONHGEWYFGTNY5ZVOIPS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Optimistic Rates for Learning with a Smooth Loss","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Ambuj Tewari, Karthik Sridharan, Nathan Srebro","submitted_at":"2010-09-20T17:35:35Z","abstract_excerpt":"We establish an excess risk bound of O(H R_n^2 + R_n \\sqrt{H L*}) for empirical risk minimization with an H-smooth loss function and a hypothesis class with Rademacher complexity R_n, where L* is the best risk achievable by the hypothesis class. For typical hypothesis classes where R_n = \\sqrt{R/n}, this translates to a learning rate of O(RH/n) in the separable (L*=0) case and O(RH/n + \\sqrt{L^* RH/n}) more generally. We also provide similar guarantees for online and stochastic convex optimization with a smooth non-negative objective."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1009.3896","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":"2026-05-18T03:40:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SxdCQW7Yc3qwIcgT6oiVZJVcm2A+aEWdabIHquGo0unwCziHBmxDO5K2XhcXo21aUJe9C6647BQfgOker4UOCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T09:20:27.960885Z"},"content_sha256":"1e9104bc1b3103e71ca714454353b4fb334869094b20dcc15880e18941a163b5","schema_version":"1.0","event_id":"sha256:1e9104bc1b3103e71ca714454353b4fb334869094b20dcc15880e18941a163b5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CBNUKUZONHGEWYFGTNY5ZVOIPS/bundle.json","state_url":"https://pith.science/pith/CBNUKUZONHGEWYFGTNY5ZVOIPS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CBNUKUZONHGEWYFGTNY5ZVOIPS/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":"2026-06-01T09:20:27Z","links":{"resolver":"https://pith.science/pith/CBNUKUZONHGEWYFGTNY5ZVOIPS","bundle":"https://pith.science/pith/CBNUKUZONHGEWYFGTNY5ZVOIPS/bundle.json","state":"https://pith.science/pith/CBNUKUZONHGEWYFGTNY5ZVOIPS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CBNUKUZONHGEWYFGTNY5ZVOIPS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2010:CBNUKUZONHGEWYFGTNY5ZVOIPS","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":"c0ab938b5117345707810e965bb97251487baa17ec4463240b979e73dada4580","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2010-09-20T17:35:35Z","title_canon_sha256":"b3b877ab54e55d2c9ca0b81b77ad77cdfac9d8322f25320792ecd43802d6ad51"},"schema_version":"1.0","source":{"id":"1009.3896","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1009.3896","created_at":"2026-05-18T03:40:03Z"},{"alias_kind":"arxiv_version","alias_value":"1009.3896v2","created_at":"2026-05-18T03:40:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1009.3896","created_at":"2026-05-18T03:40:03Z"},{"alias_kind":"pith_short_12","alias_value":"CBNUKUZONHGE","created_at":"2026-05-18T12:26:05Z"},{"alias_kind":"pith_short_16","alias_value":"CBNUKUZONHGEWYFG","created_at":"2026-05-18T12:26:05Z"},{"alias_kind":"pith_short_8","alias_value":"CBNUKUZO","created_at":"2026-05-18T12:26:05Z"}],"graph_snapshots":[{"event_id":"sha256:1e9104bc1b3103e71ca714454353b4fb334869094b20dcc15880e18941a163b5","target":"graph","created_at":"2026-05-18T03:40:03Z","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 establish an excess risk bound of O(H R_n^2 + R_n \\sqrt{H L*}) for empirical risk minimization with an H-smooth loss function and a hypothesis class with Rademacher complexity R_n, where L* is the best risk achievable by the hypothesis class. For typical hypothesis classes where R_n = \\sqrt{R/n}, this translates to a learning rate of O(RH/n) in the separable (L*=0) case and O(RH/n + \\sqrt{L^* RH/n}) more generally. We also provide similar guarantees for online and stochastic convex optimization with a smooth non-negative objective.","authors_text":"Ambuj Tewari, Karthik Sridharan, Nathan Srebro","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2010-09-20T17:35:35Z","title":"Optimistic Rates for Learning with a Smooth Loss"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1009.3896","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":"sha256:16bd2c53f2d020d3229ad6d8dbe4ea2c158e337c214de3e1b597493b1eadf52f","target":"record","created_at":"2026-05-18T03:40:03Z","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":"c0ab938b5117345707810e965bb97251487baa17ec4463240b979e73dada4580","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2010-09-20T17:35:35Z","title_canon_sha256":"b3b877ab54e55d2c9ca0b81b77ad77cdfac9d8322f25320792ecd43802d6ad51"},"schema_version":"1.0","source":{"id":"1009.3896","kind":"arxiv","version":2}},"canonical_sha256":"105b45532e69cc4b60a69b71dcd5c87c9ed67582a1b42252d00f79dc48e6ee3d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"105b45532e69cc4b60a69b71dcd5c87c9ed67582a1b42252d00f79dc48e6ee3d","first_computed_at":"2026-05-18T03:40:03.619264Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:40:03.619264Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9d8RnrwG4zHBDHYIChK/duG+w263pb9u5InajdJmGVGfYVpgnRNPeN+ZsQitgQI+UNQvT4Zt+e3SqxVRTOmUAg==","signature_status":"signed_v1","signed_at":"2026-05-18T03:40:03.620021Z","signed_message":"canonical_sha256_bytes"},"source_id":"1009.3896","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:16bd2c53f2d020d3229ad6d8dbe4ea2c158e337c214de3e1b597493b1eadf52f","sha256:1e9104bc1b3103e71ca714454353b4fb334869094b20dcc15880e18941a163b5"],"state_sha256":"77bea1bab94ed889b841a994df5e9cdd3f836f2d36b5098724b73785fbf650b5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UmsL8Z6LlGaxjs3S93cNfxTuuAq5m3lt1Pk6x9ERGO6XM3w1IWg8LN3RtWqCw4YMtQTdNXzUGc6f6YdJb2pMCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T09:20:27.962767Z","bundle_sha256":"7ff4231cd4ca9874d863e09409a28c4294aab731731dec7b645b8ba44841c832"}}