{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2011:6UYT6VJCFY6X7ZI4ML2ULWJN77","short_pith_number":"pith:6UYT6VJC","schema_version":"1.0","canonical_sha256":"f5313f55222e3d7fe51c62f545d92dffde18a3c400aae0e706421638d7dd8d12","source":{"kind":"arxiv","id":"1103.4487","version":1},"attestation_state":"computed","paper":{"title":"Handwritten Digit Recognition with a Committee of Deep Neural Nets on GPUs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CV","cs.NE"],"primary_cat":"cs.LG","authors_text":"Dan C. Cire\\c{s}an, J\\\"urgen Schmidhuber, Luca M. Gambardella, Ueli Meier","submitted_at":"2011-03-23T10:38:50Z","abstract_excerpt":"The competitive MNIST handwritten digit recognition benchmark has a long history of broken records since 1998. The most recent substantial improvement by others dates back 7 years (error rate 0.4%) . Recently we were able to significantly improve this result, using graphics cards to greatly speed up training of simple but deep MLPs, which achieved 0.35%, outperforming all the previous more complex methods. Here we report another substantial improvement: 0.31% obtained using a committee of MLPs."},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1103.4487","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2011-03-23T10:38:50Z","cross_cats_sorted":["cs.AI","cs.CV","cs.NE"],"title_canon_sha256":"e01fc4d01a957dd78f80e17116fded3744fd94d89cb522bef7b496c3f75cdfae","abstract_canon_sha256":"bfc85c75fde8797e7f6efee5191fd8247d34590a9dd1c5b3dd2d1c36316b3094"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:26:01.933255Z","signature_b64":"CvqpglzXygE2jzTd9Tc8NFlD5V65qWGI+Vev92dQh228LSSYRaVhSiz4/poIYWqL0/26nlwCWq1HW6xhpppvCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f5313f55222e3d7fe51c62f545d92dffde18a3c400aae0e706421638d7dd8d12","last_reissued_at":"2026-05-18T04:26:01.932804Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:26:01.932804Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Handwritten Digit Recognition with a Committee of Deep Neural Nets on GPUs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CV","cs.NE"],"primary_cat":"cs.LG","authors_text":"Dan C. Cire\\c{s}an, J\\\"urgen Schmidhuber, Luca M. Gambardella, Ueli Meier","submitted_at":"2011-03-23T10:38:50Z","abstract_excerpt":"The competitive MNIST handwritten digit recognition benchmark has a long history of broken records since 1998. The most recent substantial improvement by others dates back 7 years (error rate 0.4%) . Recently we were able to significantly improve this result, using graphics cards to greatly speed up training of simple but deep MLPs, which achieved 0.35%, outperforming all the previous more complex methods. Here we report another substantial improvement: 0.31% obtained using a committee of MLPs."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1103.4487","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1103.4487","created_at":"2026-05-18T04:26:01.932883+00:00"},{"alias_kind":"arxiv_version","alias_value":"1103.4487v1","created_at":"2026-05-18T04:26:01.932883+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1103.4487","created_at":"2026-05-18T04:26:01.932883+00:00"},{"alias_kind":"pith_short_12","alias_value":"6UYT6VJCFY6X","created_at":"2026-05-18T12:26:22.705136+00:00"},{"alias_kind":"pith_short_16","alias_value":"6UYT6VJCFY6X7ZI4","created_at":"2026-05-18T12:26:22.705136+00:00"},{"alias_kind":"pith_short_8","alias_value":"6UYT6VJC","created_at":"2026-05-18T12:26:22.705136+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/6UYT6VJCFY6X7ZI4ML2ULWJN77","json":"https://pith.science/pith/6UYT6VJCFY6X7ZI4ML2ULWJN77.json","graph_json":"https://pith.science/api/pith-number/6UYT6VJCFY6X7ZI4ML2ULWJN77/graph.json","events_json":"https://pith.science/api/pith-number/6UYT6VJCFY6X7ZI4ML2ULWJN77/events.json","paper":"https://pith.science/paper/6UYT6VJC"},"agent_actions":{"view_html":"https://pith.science/pith/6UYT6VJCFY6X7ZI4ML2ULWJN77","download_json":"https://pith.science/pith/6UYT6VJCFY6X7ZI4ML2ULWJN77.json","view_paper":"https://pith.science/paper/6UYT6VJC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1103.4487&json=true","fetch_graph":"https://pith.science/api/pith-number/6UYT6VJCFY6X7ZI4ML2ULWJN77/graph.json","fetch_events":"https://pith.science/api/pith-number/6UYT6VJCFY6X7ZI4ML2ULWJN77/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6UYT6VJCFY6X7ZI4ML2ULWJN77/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6UYT6VJCFY6X7ZI4ML2ULWJN77/action/storage_attestation","attest_author":"https://pith.science/pith/6UYT6VJCFY6X7ZI4ML2ULWJN77/action/author_attestation","sign_citation":"https://pith.science/pith/6UYT6VJCFY6X7ZI4ML2ULWJN77/action/citation_signature","submit_replication":"https://pith.science/pith/6UYT6VJCFY6X7ZI4ML2ULWJN77/action/replication_record"}},"created_at":"2026-05-18T04:26:01.932883+00:00","updated_at":"2026-05-18T04:26:01.932883+00:00"}