{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:6OU4HM2DNEITJSFHZPYHMBFEBO","short_pith_number":"pith:6OU4HM2D","canonical_record":{"source":{"id":"1611.01590","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2016-11-05T02:51:24Z","cross_cats_sorted":[],"title_canon_sha256":"b0a99d398c6a71e43a72d5a82e21e53b37b7489f0ef48f180a10209e0f33b15e","abstract_canon_sha256":"1b85fc9ccbdd76da01cf2e2ab545cf2be2ec0cc2754b6c8b03e210c830271859"},"schema_version":"1.0"},"canonical_sha256":"f3a9c3b343691134c8a7cbf07604a40b89f8565ebbd67ea49c01227f64fc19ae","source":{"kind":"arxiv","id":"1611.01590","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.01590","created_at":"2026-05-18T00:52:49Z"},{"alias_kind":"arxiv_version","alias_value":"1611.01590v3","created_at":"2026-05-18T00:52:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.01590","created_at":"2026-05-18T00:52:49Z"},{"alias_kind":"pith_short_12","alias_value":"6OU4HM2DNEIT","created_at":"2026-05-18T12:30:01Z"},{"alias_kind":"pith_short_16","alias_value":"6OU4HM2DNEITJSFH","created_at":"2026-05-18T12:30:01Z"},{"alias_kind":"pith_short_8","alias_value":"6OU4HM2D","created_at":"2026-05-18T12:30:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:6OU4HM2DNEITJSFHZPYHMBFEBO","target":"record","payload":{"canonical_record":{"source":{"id":"1611.01590","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2016-11-05T02:51:24Z","cross_cats_sorted":[],"title_canon_sha256":"b0a99d398c6a71e43a72d5a82e21e53b37b7489f0ef48f180a10209e0f33b15e","abstract_canon_sha256":"1b85fc9ccbdd76da01cf2e2ab545cf2be2ec0cc2754b6c8b03e210c830271859"},"schema_version":"1.0"},"canonical_sha256":"f3a9c3b343691134c8a7cbf07604a40b89f8565ebbd67ea49c01227f64fc19ae","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:52:49.407790Z","signature_b64":"XIbKTijlZyndswF/cGz/ROcPAqXQF9Mckcd9xHPiX2cQZtgGMMrqZiqUMdAbI/OyTuy7sN4c4/qRiRNWRW+ZAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f3a9c3b343691134c8a7cbf07604a40b89f8565ebbd67ea49c01227f64fc19ae","last_reissued_at":"2026-05-18T00:52:49.407153Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:52:49.407153Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1611.01590","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:52:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sA3qSJbGNgYWwMw0KghMWlu4zjDTmxQdvNGcTroVwxAUrf2L9kvS6mj0vamJsz60m85ByELS3Y5xML+mMiFIAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-04T20:52:04.623204Z"},"content_sha256":"60ab7d0439a6cc40cec9cd15daa69b11a8f6bafa1aca321e8d9b00ff114316e1","schema_version":"1.0","event_id":"sha256:60ab7d0439a6cc40cec9cd15daa69b11a8f6bafa1aca321e8d9b00ff114316e1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:6OU4HM2DNEITJSFHZPYHMBFEBO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Alternating Direction Method of Multipliers for Sparse Convolutional Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NE","authors_text":"Christian Gagn\\'e, Farkhondeh Kiaee, Mahdieh Abbasi","submitted_at":"2016-11-05T02:51:24Z","abstract_excerpt":"The storage and computation requirements of Convolutional Neural Networks (CNNs) can be prohibitive for exploiting these models over low-power or embedded devices. This paper reduces the computational complexity of the CNNs by minimizing an objective function, including the recognition loss that is augmented with a sparsity-promoting penalty term. The sparsity structure of the network is identified using the Alternating Direction Method of Multipliers (ADMM), which is widely used in large optimization problems. This method alternates between promoting the sparsity of the network and optimizing"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.01590","kind":"arxiv","version":3},"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":"2026-05-18T00:52:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iz2wNGXwJ8JyQmiYPUOkOFdd1Cu4HtDJhsaRbGCbFa48CjX8CS+eVNeGMrIijIdtwddY6qz7brQY5/nRkt2WCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-04T20:52:04.623564Z"},"content_sha256":"8f11451f67714b447a07536d60604bddd30e4af0b7d3cec2b99551e90ecec1c0","schema_version":"1.0","event_id":"sha256:8f11451f67714b447a07536d60604bddd30e4af0b7d3cec2b99551e90ecec1c0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6OU4HM2DNEITJSFHZPYHMBFEBO/bundle.json","state_url":"https://pith.science/pith/6OU4HM2DNEITJSFHZPYHMBFEBO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6OU4HM2DNEITJSFHZPYHMBFEBO/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":"2026-07-04T20:52:04Z","links":{"resolver":"https://pith.science/pith/6OU4HM2DNEITJSFHZPYHMBFEBO","bundle":"https://pith.science/pith/6OU4HM2DNEITJSFHZPYHMBFEBO/bundle.json","state":"https://pith.science/pith/6OU4HM2DNEITJSFHZPYHMBFEBO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6OU4HM2DNEITJSFHZPYHMBFEBO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:6OU4HM2DNEITJSFHZPYHMBFEBO","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":"1b85fc9ccbdd76da01cf2e2ab545cf2be2ec0cc2754b6c8b03e210c830271859","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2016-11-05T02:51:24Z","title_canon_sha256":"b0a99d398c6a71e43a72d5a82e21e53b37b7489f0ef48f180a10209e0f33b15e"},"schema_version":"1.0","source":{"id":"1611.01590","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.01590","created_at":"2026-05-18T00:52:49Z"},{"alias_kind":"arxiv_version","alias_value":"1611.01590v3","created_at":"2026-05-18T00:52:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.01590","created_at":"2026-05-18T00:52:49Z"},{"alias_kind":"pith_short_12","alias_value":"6OU4HM2DNEIT","created_at":"2026-05-18T12:30:01Z"},{"alias_kind":"pith_short_16","alias_value":"6OU4HM2DNEITJSFH","created_at":"2026-05-18T12:30:01Z"},{"alias_kind":"pith_short_8","alias_value":"6OU4HM2D","created_at":"2026-05-18T12:30:01Z"}],"graph_snapshots":[{"event_id":"sha256:8f11451f67714b447a07536d60604bddd30e4af0b7d3cec2b99551e90ecec1c0","target":"graph","created_at":"2026-05-18T00:52:49Z","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 storage and computation requirements of Convolutional Neural Networks (CNNs) can be prohibitive for exploiting these models over low-power or embedded devices. This paper reduces the computational complexity of the CNNs by minimizing an objective function, including the recognition loss that is augmented with a sparsity-promoting penalty term. The sparsity structure of the network is identified using the Alternating Direction Method of Multipliers (ADMM), which is widely used in large optimization problems. This method alternates between promoting the sparsity of the network and optimizing","authors_text":"Christian Gagn\\'e, Farkhondeh Kiaee, Mahdieh Abbasi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2016-11-05T02:51:24Z","title":"Alternating Direction Method of Multipliers for Sparse Convolutional Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.01590","kind":"arxiv","version":3},"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":"sha256:60ab7d0439a6cc40cec9cd15daa69b11a8f6bafa1aca321e8d9b00ff114316e1","target":"record","created_at":"2026-05-18T00:52:49Z","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":"1b85fc9ccbdd76da01cf2e2ab545cf2be2ec0cc2754b6c8b03e210c830271859","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2016-11-05T02:51:24Z","title_canon_sha256":"b0a99d398c6a71e43a72d5a82e21e53b37b7489f0ef48f180a10209e0f33b15e"},"schema_version":"1.0","source":{"id":"1611.01590","kind":"arxiv","version":3}},"canonical_sha256":"f3a9c3b343691134c8a7cbf07604a40b89f8565ebbd67ea49c01227f64fc19ae","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f3a9c3b343691134c8a7cbf07604a40b89f8565ebbd67ea49c01227f64fc19ae","first_computed_at":"2026-05-18T00:52:49.407153Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:52:49.407153Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XIbKTijlZyndswF/cGz/ROcPAqXQF9Mckcd9xHPiX2cQZtgGMMrqZiqUMdAbI/OyTuy7sN4c4/qRiRNWRW+ZAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:52:49.407790Z","signed_message":"canonical_sha256_bytes"},"source_id":"1611.01590","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:60ab7d0439a6cc40cec9cd15daa69b11a8f6bafa1aca321e8d9b00ff114316e1","sha256:8f11451f67714b447a07536d60604bddd30e4af0b7d3cec2b99551e90ecec1c0"],"state_sha256":"6dc820e108fb99147cdb1820083df32967b07c1b8878582dd0be01a947581f66"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vqYSFGy25v+3D8N3MZkJ0HygTg4kOWK56lnbT7MOOr6B+Hge5NC4Z6yMejZL2jtO6NNkkECrnQcu1iQ/PJkbBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-04T20:52:04.625473Z","bundle_sha256":"03810be050a3a99af1c4d27e0d489c02851bd427e412a00a9885ade8d7a17013"}}