{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:PTETPESRIIV7KVABGDAP4BSH2D","short_pith_number":"pith:PTETPESR","canonical_record":{"source":{"id":"1512.04848","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-12-15T16:41:42Z","cross_cats_sorted":["cs.DS","stat.ML"],"title_canon_sha256":"ff538361f1c2283222f160b2d9f28020fc69f8866eba0f06d57175af3e6bc83a","abstract_canon_sha256":"c852a97ef482c3727f2724d6e6544b3d34b841fbc8e52fbf5309023cf914a6ee"},"schema_version":"1.0"},"canonical_sha256":"7cc9379251422bf5540130c0fe0647d0cee6e8a84e932f3b8345b29874febdc4","source":{"kind":"arxiv","id":"1512.04848","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1512.04848","created_at":"2026-05-18T00:54:58Z"},{"alias_kind":"arxiv_version","alias_value":"1512.04848v2","created_at":"2026-05-18T00:54:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1512.04848","created_at":"2026-05-18T00:54:58Z"},{"alias_kind":"pith_short_12","alias_value":"PTETPESRIIV7","created_at":"2026-05-18T12:29:37Z"},{"alias_kind":"pith_short_16","alias_value":"PTETPESRIIV7KVAB","created_at":"2026-05-18T12:29:37Z"},{"alias_kind":"pith_short_8","alias_value":"PTETPESR","created_at":"2026-05-18T12:29:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:PTETPESRIIV7KVABGDAP4BSH2D","target":"record","payload":{"canonical_record":{"source":{"id":"1512.04848","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-12-15T16:41:42Z","cross_cats_sorted":["cs.DS","stat.ML"],"title_canon_sha256":"ff538361f1c2283222f160b2d9f28020fc69f8866eba0f06d57175af3e6bc83a","abstract_canon_sha256":"c852a97ef482c3727f2724d6e6544b3d34b841fbc8e52fbf5309023cf914a6ee"},"schema_version":"1.0"},"canonical_sha256":"7cc9379251422bf5540130c0fe0647d0cee6e8a84e932f3b8345b29874febdc4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:54:58.176332Z","signature_b64":"Ddjn7khBs5uUKwKVCVoGQKPgKxhkWjESzGYlWQ2mzBUWFchIBQepANH5k/sRm9V7j4g8qqrNfOBBze7dDc7UAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7cc9379251422bf5540130c0fe0647d0cee6e8a84e932f3b8345b29874febdc4","last_reissued_at":"2026-05-18T00:54:58.175655Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:54:58.175655Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1512.04848","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":"2026-05-18T00:54:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uFKsZqiDRtcmyJ6eg0bTo+sOobxYBMx3+v0WTXuhUsGCY0SePGK7mWOMNAWPTT83VcDVtPlXCyj9x8z5iWFTBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T11:08:20.626160Z"},"content_sha256":"fbee83fdd870323c613eda5f70c24a70375fda7cafef663788227f0c5734ae65","schema_version":"1.0","event_id":"sha256:fbee83fdd870323c613eda5f70c24a70375fda7cafef663788227f0c5734ae65"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:PTETPESRIIV7KVABGDAP4BSH2D","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Data Driven Resource Allocation for Distributed Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DS","stat.ML"],"primary_cat":"cs.LG","authors_text":"Alex Smola, Colin White, Maria Florina Balcan, Mu Li, Travis Dick, Venkata Krishna Pillutla","submitted_at":"2015-12-15T16:41:42Z","abstract_excerpt":"In distributed machine learning, data is dispatched to multiple machines for processing. Motivated by the fact that similar data points often belong to the same or similar classes, and more generally, classification rules of high accuracy tend to be \"locally simple but globally complex\" (Vapnik & Bottou 1993), we propose data dependent dispatching that takes advantage of such structure. We present an in-depth analysis of this model, providing new algorithms with provable worst-case guarantees, analysis proving existing scalable heuristics perform well in natural non worst-case conditions, and "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1512.04848","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":"2026-05-18T00:54:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C4p+O0GQC9J9zOWCTPXS1YujP9ey7Qa8C9e8HJIbcGDXmFg/S7SLwBHANFNQmp29vCUMLSuHReWMj1Og6+z0CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T11:08:20.626805Z"},"content_sha256":"382e4d15dba98f4eec54898b26479a819e3c3d38af0a31c70d8d3c91d7218f8b","schema_version":"1.0","event_id":"sha256:382e4d15dba98f4eec54898b26479a819e3c3d38af0a31c70d8d3c91d7218f8b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PTETPESRIIV7KVABGDAP4BSH2D/bundle.json","state_url":"https://pith.science/pith/PTETPESRIIV7KVABGDAP4BSH2D/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PTETPESRIIV7KVABGDAP4BSH2D/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":"2026-05-25T11:08:20Z","links":{"resolver":"https://pith.science/pith/PTETPESRIIV7KVABGDAP4BSH2D","bundle":"https://pith.science/pith/PTETPESRIIV7KVABGDAP4BSH2D/bundle.json","state":"https://pith.science/pith/PTETPESRIIV7KVABGDAP4BSH2D/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PTETPESRIIV7KVABGDAP4BSH2D/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:PTETPESRIIV7KVABGDAP4BSH2D","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":"c852a97ef482c3727f2724d6e6544b3d34b841fbc8e52fbf5309023cf914a6ee","cross_cats_sorted":["cs.DS","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-12-15T16:41:42Z","title_canon_sha256":"ff538361f1c2283222f160b2d9f28020fc69f8866eba0f06d57175af3e6bc83a"},"schema_version":"1.0","source":{"id":"1512.04848","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1512.04848","created_at":"2026-05-18T00:54:58Z"},{"alias_kind":"arxiv_version","alias_value":"1512.04848v2","created_at":"2026-05-18T00:54:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1512.04848","created_at":"2026-05-18T00:54:58Z"},{"alias_kind":"pith_short_12","alias_value":"PTETPESRIIV7","created_at":"2026-05-18T12:29:37Z"},{"alias_kind":"pith_short_16","alias_value":"PTETPESRIIV7KVAB","created_at":"2026-05-18T12:29:37Z"},{"alias_kind":"pith_short_8","alias_value":"PTETPESR","created_at":"2026-05-18T12:29:37Z"}],"graph_snapshots":[{"event_id":"sha256:382e4d15dba98f4eec54898b26479a819e3c3d38af0a31c70d8d3c91d7218f8b","target":"graph","created_at":"2026-05-18T00:54:58Z","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":"In distributed machine learning, data is dispatched to multiple machines for processing. Motivated by the fact that similar data points often belong to the same or similar classes, and more generally, classification rules of high accuracy tend to be \"locally simple but globally complex\" (Vapnik & Bottou 1993), we propose data dependent dispatching that takes advantage of such structure. We present an in-depth analysis of this model, providing new algorithms with provable worst-case guarantees, analysis proving existing scalable heuristics perform well in natural non worst-case conditions, and ","authors_text":"Alex Smola, Colin White, Maria Florina Balcan, Mu Li, Travis Dick, Venkata Krishna Pillutla","cross_cats":["cs.DS","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-12-15T16:41:42Z","title":"Data Driven Resource Allocation for Distributed Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1512.04848","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:fbee83fdd870323c613eda5f70c24a70375fda7cafef663788227f0c5734ae65","target":"record","created_at":"2026-05-18T00:54:58Z","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":"c852a97ef482c3727f2724d6e6544b3d34b841fbc8e52fbf5309023cf914a6ee","cross_cats_sorted":["cs.DS","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2015-12-15T16:41:42Z","title_canon_sha256":"ff538361f1c2283222f160b2d9f28020fc69f8866eba0f06d57175af3e6bc83a"},"schema_version":"1.0","source":{"id":"1512.04848","kind":"arxiv","version":2}},"canonical_sha256":"7cc9379251422bf5540130c0fe0647d0cee6e8a84e932f3b8345b29874febdc4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7cc9379251422bf5540130c0fe0647d0cee6e8a84e932f3b8345b29874febdc4","first_computed_at":"2026-05-18T00:54:58.175655Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:54:58.175655Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ddjn7khBs5uUKwKVCVoGQKPgKxhkWjESzGYlWQ2mzBUWFchIBQepANH5k/sRm9V7j4g8qqrNfOBBze7dDc7UAw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:54:58.176332Z","signed_message":"canonical_sha256_bytes"},"source_id":"1512.04848","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fbee83fdd870323c613eda5f70c24a70375fda7cafef663788227f0c5734ae65","sha256:382e4d15dba98f4eec54898b26479a819e3c3d38af0a31c70d8d3c91d7218f8b"],"state_sha256":"301255e022389a799e6d485f89788bccc3f1cd6b3a801052d6af42e857fb0a38"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ShmfUOx2/Hxo5CvbYWVeVuGK4SfNCVJQztPOpi3NV5OkpRHlEOwZCx7tAKwt5EoBNsS50/sUvuF+6xBjxWtnCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T11:08:20.631055Z","bundle_sha256":"b2e8ea930c9293cf3e5836c8091123da500be86de8f4e5d9ad9f99bd14581b7b"}}