{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:PNV3CCFUZMNLPWIWK2IGRM2YXO","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":"2b97876c2b00f26a31c9360c6973a3fc924fb70c28ad42023e27d223e0554d0e","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-05-31T02:45:55Z","title_canon_sha256":"dac2a6522c79c454fb57af3370bc03f8a653a773e36c66eabaff80c8ed7b3c22"},"schema_version":"1.0","source":{"id":"1705.10924","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1705.10924","created_at":"2026-05-18T00:43:19Z"},{"alias_kind":"arxiv_version","alias_value":"1705.10924v1","created_at":"2026-05-18T00:43:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.10924","created_at":"2026-05-18T00:43:19Z"},{"alias_kind":"pith_short_12","alias_value":"PNV3CCFUZMNL","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_16","alias_value":"PNV3CCFUZMNLPWIW","created_at":"2026-05-18T12:31:37Z"},{"alias_kind":"pith_short_8","alias_value":"PNV3CCFU","created_at":"2026-05-18T12:31:37Z"}],"graph_snapshots":[{"event_id":"sha256:073956dd7c4db19b43db3af5e94641ebb3dbdd7f2c6f80980f5c6a8299faa015","target":"graph","created_at":"2026-05-18T00:43:19Z","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 network (DNN) based approaches hold significant potential for reinforcement learning (RL) and have already shown remarkable gains over state-of-art methods in a number of applications. The effectiveness of DNN methods can be attributed to leveraging the abundance of supervised data to learn value functions, Q-functions, and policy function approximations without the need for feature engineering. Nevertheless, the deployment of DNN-based predictors with very deep architectures can pose an issue due to computational and other resource constraints at test-time in a number of applicati","authors_text":"Feng Nan, Henghui Zhu, Ioannis Paschalidis, Venkatesh Saligrama","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-05-31T02:45:55Z","title":"Sequential Dynamic Decision Making with Deep Neural Nets on a Test-Time Budget"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.10924","kind":"arxiv","version":1},"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:a2c2f7b0a0831f976287d88244c9e5e198f5bacda9e1d326f35cb26db28c31eb","target":"record","created_at":"2026-05-18T00:43:19Z","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":"2b97876c2b00f26a31c9360c6973a3fc924fb70c28ad42023e27d223e0554d0e","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-05-31T02:45:55Z","title_canon_sha256":"dac2a6522c79c454fb57af3370bc03f8a653a773e36c66eabaff80c8ed7b3c22"},"schema_version":"1.0","source":{"id":"1705.10924","kind":"arxiv","version":1}},"canonical_sha256":"7b6bb108b4cb1ab7d916569068b358bbb9c59fc456b6120ac9645d6f4428f832","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7b6bb108b4cb1ab7d916569068b358bbb9c59fc456b6120ac9645d6f4428f832","first_computed_at":"2026-05-18T00:43:19.841722Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:43:19.841722Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5o5sK4TyxYEP1YmI4Tvgt+ZXhe0yrmWgkuEb5i3CEYpHOLRusV/HUrsjeiuqMNyquP+UCkYWoGg7qfBCbXb9Ag==","signature_status":"signed_v1","signed_at":"2026-05-18T00:43:19.842171Z","signed_message":"canonical_sha256_bytes"},"source_id":"1705.10924","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a2c2f7b0a0831f976287d88244c9e5e198f5bacda9e1d326f35cb26db28c31eb","sha256:073956dd7c4db19b43db3af5e94641ebb3dbdd7f2c6f80980f5c6a8299faa015"],"state_sha256":"b59dcbd2cfdf949613034ec6debd177b1415e5a174adb8514bdc7ef33ad6fd4d"}