{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:FS7NOJXQHDAKYEBJHQ27L4BVHS","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":"31529b1dbc8d50f88219b1839638003548098aa17434ef833ba5862f05e7de86","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-06-15T17:19:48Z","title_canon_sha256":"f5cd9c328dd331730b1687c22d152550f6be84ebffc04d8d207e6122aedf0e75"},"schema_version":"1.0","source":{"id":"2306.09293","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.09293","created_at":"2026-07-05T11:21:29Z"},{"alias_kind":"arxiv_version","alias_value":"2306.09293v2","created_at":"2026-07-05T11:21:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.09293","created_at":"2026-07-05T11:21:29Z"},{"alias_kind":"pith_short_12","alias_value":"FS7NOJXQHDAK","created_at":"2026-07-05T11:21:29Z"},{"alias_kind":"pith_short_16","alias_value":"FS7NOJXQHDAKYEBJ","created_at":"2026-07-05T11:21:29Z"},{"alias_kind":"pith_short_8","alias_value":"FS7NOJXQ","created_at":"2026-07-05T11:21:29Z"}],"graph_snapshots":[{"event_id":"sha256:59d66e40c6740cc64892b95092db7fcba2b8aac1c03a925da7a69e7bbb7b9200","target":"graph","created_at":"2026-07-05T11:21:29Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2306.09293/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The training process of neural networks is known to be time-consuming, and having a deep architecture only aggravates the issue. This process consists mostly of matrix operations, among which matrix multiplication is the bottleneck. Several sampling-based techniques have been proposed for speeding up the training time of deep neural networks by approximating the matrix products. These techniques fall under two categories: (i) sampling a subset of nodes in every hidden layer as active at every iteration and (ii) sampling a subset of nodes from the previous layer to approximate the current layer","authors_text":"Abolfazl Asudeh, Rishi Advani, Sana Ebrahimi","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-06-15T17:19:48Z","title":"[Experiments & Analysis] Evaluating the Feasibility of Sampling-Based Techniques for Training Multilayer Perceptrons"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.09293","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":"sha256:0a40d476c47e2622608aef5d156256ff20d1c835d422631a2026e0e3560d353a","target":"record","created_at":"2026-07-05T11:21:29Z","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":"31529b1dbc8d50f88219b1839638003548098aa17434ef833ba5862f05e7de86","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-06-15T17:19:48Z","title_canon_sha256":"f5cd9c328dd331730b1687c22d152550f6be84ebffc04d8d207e6122aedf0e75"},"schema_version":"1.0","source":{"id":"2306.09293","kind":"arxiv","version":2}},"canonical_sha256":"2cbed726f038c0ac10293c35f5f0353cb7bf028a09e7d901440707bf24f20c64","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2cbed726f038c0ac10293c35f5f0353cb7bf028a09e7d901440707bf24f20c64","first_computed_at":"2026-07-05T11:21:29.454590Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:21:29.454590Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7eMR25sbl1tIYqe06drO/IhrzMHbsXwIqcatQCgrNXTY057sjFQLMhvJwIzooTJIz0AUNm3pxlwkPaf2qJ3oCw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:21:29.455074Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.09293","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0a40d476c47e2622608aef5d156256ff20d1c835d422631a2026e0e3560d353a","sha256:59d66e40c6740cc64892b95092db7fcba2b8aac1c03a925da7a69e7bbb7b9200"],"state_sha256":"149eb76430b40269f8ff76fbdda06d179548dbc1bf869986dc57fb493fbc7eda"}