{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:V3HG2P7MSQRYMODM4UAQYLBOXD","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":"ea72a59d4af33c349909f4840442ca881fb3a7b9fae6423b8ea7dc782e7267c0","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-01-08T19:02:44Z","title_canon_sha256":"c8d870f23b2302327252cd36490179263148d335f6b3239d97076bd3c805cc47"},"schema_version":"1.0","source":{"id":"1801.02642","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.02642","created_at":"2026-05-18T00:25:15Z"},{"alias_kind":"arxiv_version","alias_value":"1801.02642v3","created_at":"2026-05-18T00:25:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.02642","created_at":"2026-05-18T00:25:15Z"},{"alias_kind":"pith_short_12","alias_value":"V3HG2P7MSQRY","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"V3HG2P7MSQRYMODM","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"V3HG2P7M","created_at":"2026-05-18T12:32:56Z"}],"graph_snapshots":[{"event_id":"sha256:fd494578d63d5808b6a403844bfe6c98110bb4de6960993212acda4f06f3acb5","target":"graph","created_at":"2026-05-18T00:25:15Z","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":"Despite all the success that deep neural networks have seen in classifying certain datasets, the challenge of finding optimal solutions that generalize still remains. In this paper, we propose the Boundary Optimizing Network (BON), a new approach to generalization for deep neural networks when used for supervised learning. Given a classification network, we propose to use a collaborative generative network that produces new synthetic data points in the form of perturbations of original data points. In this way, we create a data support around each original data point which prevents decision bo","authors_text":"Akshay Pai, Marco Singh","cross_cats":["cs.CV","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-01-08T19:02:44Z","title":"Boundary Optimizing Network (BON)"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.02642","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:e4b6ec77f4600f9f211471baa08dbf5a865b7f26ab3bf22d0f7c41e67a693ae6","target":"record","created_at":"2026-05-18T00:25:15Z","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":"ea72a59d4af33c349909f4840442ca881fb3a7b9fae6423b8ea7dc782e7267c0","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-01-08T19:02:44Z","title_canon_sha256":"c8d870f23b2302327252cd36490179263148d335f6b3239d97076bd3c805cc47"},"schema_version":"1.0","source":{"id":"1801.02642","kind":"arxiv","version":3}},"canonical_sha256":"aece6d3fec942386386ce5010c2c2eb8f7f229df2ba074439472504545151fa0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aece6d3fec942386386ce5010c2c2eb8f7f229df2ba074439472504545151fa0","first_computed_at":"2026-05-18T00:25:15.326999Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:25:15.326999Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+8Y2/Sv0ugqe4ELrGYkytZk520jXhYoMPJz3LadjVJ5pF/Y2COvwKS1oas8IBFevmpp01jpfta3MnAJsg60bDg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:25:15.327740Z","signed_message":"canonical_sha256_bytes"},"source_id":"1801.02642","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e4b6ec77f4600f9f211471baa08dbf5a865b7f26ab3bf22d0f7c41e67a693ae6","sha256:fd494578d63d5808b6a403844bfe6c98110bb4de6960993212acda4f06f3acb5"],"state_sha256":"f187f65353daa8567302473067f2611e1c3379ee8abe8929267dd8eb4aae2e97"}