{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:4VKUYZBJQRPK3FR5SHA7AJ6HMK","short_pith_number":"pith:4VKUYZBJ","canonical_record":{"source":{"id":"1905.03381","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-08T22:36:37Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"067a51a88fb32ead6528eb310ecda909fb70b1d5f8e6677bed9384e9b38ff304","abstract_canon_sha256":"bb491cf0d465970c6dbf0eae0c13ccf2c5fc7d4231d4b0e8c417e350a444ef05"},"schema_version":"1.0"},"canonical_sha256":"e5554c6429845ead963d91c1f027c762843a664c15ad3d45804179854abf6c9e","source":{"kind":"arxiv","id":"1905.03381","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.03381","created_at":"2026-05-17T23:46:40Z"},{"alias_kind":"arxiv_version","alias_value":"1905.03381v1","created_at":"2026-05-17T23:46:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.03381","created_at":"2026-05-17T23:46:40Z"},{"alias_kind":"pith_short_12","alias_value":"4VKUYZBJQRPK","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"4VKUYZBJQRPK3FR5","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"4VKUYZBJ","created_at":"2026-05-18T12:33:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:4VKUYZBJQRPK3FR5SHA7AJ6HMK","target":"record","payload":{"canonical_record":{"source":{"id":"1905.03381","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-08T22:36:37Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"067a51a88fb32ead6528eb310ecda909fb70b1d5f8e6677bed9384e9b38ff304","abstract_canon_sha256":"bb491cf0d465970c6dbf0eae0c13ccf2c5fc7d4231d4b0e8c417e350a444ef05"},"schema_version":"1.0"},"canonical_sha256":"e5554c6429845ead963d91c1f027c762843a664c15ad3d45804179854abf6c9e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:46:40.168242Z","signature_b64":"2LVMerdc2IJdjzI3hqPJ/a+yN4G8Uf4+Z3hbPw42GoJKqyRsUqudqi/+9x+5gpdnf6oPn1bjr6dOlYeRKb0lDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e5554c6429845ead963d91c1f027c762843a664c15ad3d45804179854abf6c9e","last_reissued_at":"2026-05-17T23:46:40.167259Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:46:40.167259Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1905.03381","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":"2026-05-17T23:46:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"S/GH9844P+LlwznMAH/S8AwcQBdbHrEUcH0sZaTvaxMjyv8zJ3/UPfP2ss6DEFqsq8UJssIGPnwbNnEW3J1NCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T19:30:31.891060Z"},"content_sha256":"69c1e0baa7052ccdb7d8fc508d671665687abc5f4ad6c2563af854961a85da90","schema_version":"1.0","event_id":"sha256:69c1e0baa7052ccdb7d8fc508d671665687abc5f4ad6c2563af854961a85da90"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:4VKUYZBJQRPK3FR5SHA7AJ6HMK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"AutoAssist: A Framework to Accelerate Training of Deep Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"cs.LG","authors_text":"Hsiang-Fu Yu, Inderjit S. Dhillon, Jiong Zhang","submitted_at":"2019-05-08T22:36:37Z","abstract_excerpt":"Deep neural networks have yielded superior performance in many applications; however, the gradient computation in a deep model with millions of instances lead to a lengthy training process even with modern GPU/TPU hardware acceleration. In this paper, we propose AutoAssist, a simple framework to accelerate training of a deep neural network. Typically, as the training procedure evolves, the amount of improvement in the current model by a stochastic gradient update on each instance varies dynamically. In AutoAssist, we utilize this fact and design a simple instance shrinking operation, which is "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.03381","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":"2026-05-17T23:46:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yfroRnMJVaRQk5Xu0oO9+jCKRNA6v4TezCTOhgnSHUqnqj6Nus+YUzP95oQ2MDu3XMqRpihSlDuJswmpyStpDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-24T19:30:31.891421Z"},"content_sha256":"ee0f5fbe8bfbd50b5e9316ebf9c9ab4268055fbbbd4f6fa1538d0d3421337b06","schema_version":"1.0","event_id":"sha256:ee0f5fbe8bfbd50b5e9316ebf9c9ab4268055fbbbd4f6fa1538d0d3421337b06"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4VKUYZBJQRPK3FR5SHA7AJ6HMK/bundle.json","state_url":"https://pith.science/pith/4VKUYZBJQRPK3FR5SHA7AJ6HMK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4VKUYZBJQRPK3FR5SHA7AJ6HMK/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":"2026-06-24T19:30:31Z","links":{"resolver":"https://pith.science/pith/4VKUYZBJQRPK3FR5SHA7AJ6HMK","bundle":"https://pith.science/pith/4VKUYZBJQRPK3FR5SHA7AJ6HMK/bundle.json","state":"https://pith.science/pith/4VKUYZBJQRPK3FR5SHA7AJ6HMK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4VKUYZBJQRPK3FR5SHA7AJ6HMK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:4VKUYZBJQRPK3FR5SHA7AJ6HMK","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":"bb491cf0d465970c6dbf0eae0c13ccf2c5fc7d4231d4b0e8c417e350a444ef05","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-08T22:36:37Z","title_canon_sha256":"067a51a88fb32ead6528eb310ecda909fb70b1d5f8e6677bed9384e9b38ff304"},"schema_version":"1.0","source":{"id":"1905.03381","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.03381","created_at":"2026-05-17T23:46:40Z"},{"alias_kind":"arxiv_version","alias_value":"1905.03381v1","created_at":"2026-05-17T23:46:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.03381","created_at":"2026-05-17T23:46:40Z"},{"alias_kind":"pith_short_12","alias_value":"4VKUYZBJQRPK","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"4VKUYZBJQRPK3FR5","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"4VKUYZBJ","created_at":"2026-05-18T12:33:10Z"}],"graph_snapshots":[{"event_id":"sha256:ee0f5fbe8bfbd50b5e9316ebf9c9ab4268055fbbbd4f6fa1538d0d3421337b06","target":"graph","created_at":"2026-05-17T23:46:40Z","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":"Deep neural networks have yielded superior performance in many applications; however, the gradient computation in a deep model with millions of instances lead to a lengthy training process even with modern GPU/TPU hardware acceleration. In this paper, we propose AutoAssist, a simple framework to accelerate training of a deep neural network. Typically, as the training procedure evolves, the amount of improvement in the current model by a stochastic gradient update on each instance varies dynamically. In AutoAssist, we utilize this fact and design a simple instance shrinking operation, which is ","authors_text":"Hsiang-Fu Yu, Inderjit S. Dhillon, Jiong Zhang","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-08T22:36:37Z","title":"AutoAssist: A Framework to Accelerate Training of Deep Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.03381","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":"sha256:69c1e0baa7052ccdb7d8fc508d671665687abc5f4ad6c2563af854961a85da90","target":"record","created_at":"2026-05-17T23:46:40Z","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":"bb491cf0d465970c6dbf0eae0c13ccf2c5fc7d4231d4b0e8c417e350a444ef05","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-08T22:36:37Z","title_canon_sha256":"067a51a88fb32ead6528eb310ecda909fb70b1d5f8e6677bed9384e9b38ff304"},"schema_version":"1.0","source":{"id":"1905.03381","kind":"arxiv","version":1}},"canonical_sha256":"e5554c6429845ead963d91c1f027c762843a664c15ad3d45804179854abf6c9e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e5554c6429845ead963d91c1f027c762843a664c15ad3d45804179854abf6c9e","first_computed_at":"2026-05-17T23:46:40.167259Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:46:40.167259Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2LVMerdc2IJdjzI3hqPJ/a+yN4G8Uf4+Z3hbPw42GoJKqyRsUqudqi/+9x+5gpdnf6oPn1bjr6dOlYeRKb0lDw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:46:40.168242Z","signed_message":"canonical_sha256_bytes"},"source_id":"1905.03381","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:69c1e0baa7052ccdb7d8fc508d671665687abc5f4ad6c2563af854961a85da90","sha256:ee0f5fbe8bfbd50b5e9316ebf9c9ab4268055fbbbd4f6fa1538d0d3421337b06"],"state_sha256":"ab81818351ff702de8e46e6ef0e0642221a3b93fcb758fd5d8b18b000777e3f0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"08m/nUk24JyoonA49nyRgGneVWef/ZrCmnlBFHc+5v+BAfROtY5ElS8WpkSHSqeXTSD7XjMyESnlojkeeqy8Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-24T19:30:31.893375Z","bundle_sha256":"2c5e87ca8d0b8b22d2768626283927dee19cc86ec1063d7f091972f287243e44"}}