{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:Y7YA5VZYKEENS2HFZ7FEHUIJIJ","short_pith_number":"pith:Y7YA5VZY","canonical_record":{"source":{"id":"1706.04964","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-15T16:59:07Z","cross_cats_sorted":[],"title_canon_sha256":"2f8e42b08b28a704875dec0c77623a1ffa4aacca983eec23a083a69ab0747cb9","abstract_canon_sha256":"3813eb4877a50bde4c68b9eed2d3cfa690ebec786d937beb3fa9b46bc6c354ba"},"schema_version":"1.0"},"canonical_sha256":"c7f00ed7385108d968e5cfca43d1094279fc890435351a7ebb0ed606a3d115e1","source":{"kind":"arxiv","id":"1706.04964","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1706.04964","created_at":"2026-05-18T00:13:15Z"},{"alias_kind":"arxiv_version","alias_value":"1706.04964v4","created_at":"2026-05-18T00:13:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.04964","created_at":"2026-05-18T00:13:15Z"},{"alias_kind":"pith_short_12","alias_value":"Y7YA5VZYKEEN","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"Y7YA5VZYKEENS2HF","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"Y7YA5VZY","created_at":"2026-05-18T12:31:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:Y7YA5VZYKEENS2HFZ7FEHUIJIJ","target":"record","payload":{"canonical_record":{"source":{"id":"1706.04964","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-15T16:59:07Z","cross_cats_sorted":[],"title_canon_sha256":"2f8e42b08b28a704875dec0c77623a1ffa4aacca983eec23a083a69ab0747cb9","abstract_canon_sha256":"3813eb4877a50bde4c68b9eed2d3cfa690ebec786d937beb3fa9b46bc6c354ba"},"schema_version":"1.0"},"canonical_sha256":"c7f00ed7385108d968e5cfca43d1094279fc890435351a7ebb0ed606a3d115e1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:13:15.694407Z","signature_b64":"I1C7mnclxeZcfgbbCV/qFS/LLcODCAxsEYIw/CyCQ6/V6QmH4/aUPhJ+IlRw1WKywCig9yOt+FTmHRCsvupdCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c7f00ed7385108d968e5cfca43d1094279fc890435351a7ebb0ed606a3d115e1","last_reissued_at":"2026-05-18T00:13:15.693729Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:13:15.693729Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1706.04964","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:13:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"io3u15NR/UbTnR1yScEFfPQmrn8HUZ7QAGshwlAt+X67M9Ip5tyYkeVWxde1pK7fiHFP8PH13JSSa1T9hwoBDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T03:52:03.308764Z"},"content_sha256":"e3a64cf9b05f67eb5b03811dd35ea0bc5b94b69c4256efca5cfebad99c73fe02","schema_version":"1.0","event_id":"sha256:e3a64cf9b05f67eb5b03811dd35ea0bc5b94b69c4256efca5cfebad99c73fe02"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:Y7YA5VZYKEENS2HFZ7FEHUIJIJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Deep ResNet Blocks Sequentially using Boosting Theory","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Furong Huang, John Langford, Jordan Ash, Robert Schapire","submitted_at":"2017-06-15T16:59:07Z","abstract_excerpt":"Deep neural networks are known to be difficult to train due to the instability of back-propagation. A deep \\emph{residual network} (ResNet) with identity loops remedies this by stabilizing gradient computations. We prove a boosting theory for the ResNet architecture. We construct $T$ weak module classifiers, each contains two of the $T$ layers, such that the combined strong learner is a ResNet. Therefore, we introduce an alternative Deep ResNet training algorithm, \\emph{BoostResNet}, which is particularly suitable in non-differentiable architectures. Our proposed algorithm merely requires a se"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.04964","kind":"arxiv","version":4},"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":"2026-05-18T00:13:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"po0NQSRCE0jRK8xcJ9X0swQV6qDANls5l2mvwJgcyn+6xV5t+KefZPnhLowBNsbLE8WfPI120UVDYVe5nHrkDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T03:52:03.309418Z"},"content_sha256":"a72d8f2425ec1e0a4861e221d20f074f699dc273f57c056d0f0ef2cc4125c0ba","schema_version":"1.0","event_id":"sha256:a72d8f2425ec1e0a4861e221d20f074f699dc273f57c056d0f0ef2cc4125c0ba"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Y7YA5VZYKEENS2HFZ7FEHUIJIJ/bundle.json","state_url":"https://pith.science/pith/Y7YA5VZYKEENS2HFZ7FEHUIJIJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Y7YA5VZYKEENS2HFZ7FEHUIJIJ/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":"2026-05-27T03:52:03Z","links":{"resolver":"https://pith.science/pith/Y7YA5VZYKEENS2HFZ7FEHUIJIJ","bundle":"https://pith.science/pith/Y7YA5VZYKEENS2HFZ7FEHUIJIJ/bundle.json","state":"https://pith.science/pith/Y7YA5VZYKEENS2HFZ7FEHUIJIJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Y7YA5VZYKEENS2HFZ7FEHUIJIJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:Y7YA5VZYKEENS2HFZ7FEHUIJIJ","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":"3813eb4877a50bde4c68b9eed2d3cfa690ebec786d937beb3fa9b46bc6c354ba","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-15T16:59:07Z","title_canon_sha256":"2f8e42b08b28a704875dec0c77623a1ffa4aacca983eec23a083a69ab0747cb9"},"schema_version":"1.0","source":{"id":"1706.04964","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1706.04964","created_at":"2026-05-18T00:13:15Z"},{"alias_kind":"arxiv_version","alias_value":"1706.04964v4","created_at":"2026-05-18T00:13:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.04964","created_at":"2026-05-18T00:13:15Z"},{"alias_kind":"pith_short_12","alias_value":"Y7YA5VZYKEEN","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"Y7YA5VZYKEENS2HF","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"Y7YA5VZY","created_at":"2026-05-18T12:31:56Z"}],"graph_snapshots":[{"event_id":"sha256:a72d8f2425ec1e0a4861e221d20f074f699dc273f57c056d0f0ef2cc4125c0ba","target":"graph","created_at":"2026-05-18T00:13:15Z","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 are known to be difficult to train due to the instability of back-propagation. A deep \\emph{residual network} (ResNet) with identity loops remedies this by stabilizing gradient computations. We prove a boosting theory for the ResNet architecture. We construct $T$ weak module classifiers, each contains two of the $T$ layers, such that the combined strong learner is a ResNet. Therefore, we introduce an alternative Deep ResNet training algorithm, \\emph{BoostResNet}, which is particularly suitable in non-differentiable architectures. Our proposed algorithm merely requires a se","authors_text":"Furong Huang, John Langford, Jordan Ash, Robert Schapire","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-15T16:59:07Z","title":"Learning Deep ResNet Blocks Sequentially using Boosting Theory"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.04964","kind":"arxiv","version":4},"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:e3a64cf9b05f67eb5b03811dd35ea0bc5b94b69c4256efca5cfebad99c73fe02","target":"record","created_at":"2026-05-18T00:13:15Z","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":"3813eb4877a50bde4c68b9eed2d3cfa690ebec786d937beb3fa9b46bc6c354ba","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-15T16:59:07Z","title_canon_sha256":"2f8e42b08b28a704875dec0c77623a1ffa4aacca983eec23a083a69ab0747cb9"},"schema_version":"1.0","source":{"id":"1706.04964","kind":"arxiv","version":4}},"canonical_sha256":"c7f00ed7385108d968e5cfca43d1094279fc890435351a7ebb0ed606a3d115e1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c7f00ed7385108d968e5cfca43d1094279fc890435351a7ebb0ed606a3d115e1","first_computed_at":"2026-05-18T00:13:15.693729Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:13:15.693729Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"I1C7mnclxeZcfgbbCV/qFS/LLcODCAxsEYIw/CyCQ6/V6QmH4/aUPhJ+IlRw1WKywCig9yOt+FTmHRCsvupdCg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:13:15.694407Z","signed_message":"canonical_sha256_bytes"},"source_id":"1706.04964","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e3a64cf9b05f67eb5b03811dd35ea0bc5b94b69c4256efca5cfebad99c73fe02","sha256:a72d8f2425ec1e0a4861e221d20f074f699dc273f57c056d0f0ef2cc4125c0ba"],"state_sha256":"6391e8d86e926115968b16aa74e1cc3c3b2d822b7607279ed5acde8b0e55eee9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VzCjv3h+RPAard4PJWxZy25IXbkeFONRcvPOTtjoWHX5rx4nJlefjwaosxKs75Haayzkzos2XUD6IBmENemDCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T03:52:03.312725Z","bundle_sha256":"2f38a99317b91f95b1587c98c2d6ec4ddd72178df33c1784016a6463b9969e67"}}