{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:FKRI6HVCYOSSANVUGYW7IXSR56","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":"b87784c28abd8376df98ae3b6dc9e46b1061733bc6661e27c00a4ec7e64e1bef","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2019-03-07T15:46:20Z","title_canon_sha256":"3617f3065446af448e5c68b4cdbef75c8796a664cefa8692e9808df8d969714f"},"schema_version":"1.0","source":{"id":"1903.03003","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.03003","created_at":"2026-07-05T00:55:56Z"},{"alias_kind":"arxiv_version","alias_value":"1903.03003v5","created_at":"2026-07-05T00:55:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.03003","created_at":"2026-07-05T00:55:56Z"},{"alias_kind":"pith_short_12","alias_value":"FKRI6HVCYOSS","created_at":"2026-07-05T00:55:56Z"},{"alias_kind":"pith_short_16","alias_value":"FKRI6HVCYOSSANVU","created_at":"2026-07-05T00:55:56Z"},{"alias_kind":"pith_short_8","alias_value":"FKRI6HVC","created_at":"2026-07-05T00:55:56Z"}],"graph_snapshots":[{"event_id":"sha256:a14b66e31b51beb2dd3c55ff22c7f47e081fbd9625a0a54bc7ec324807a6c23e","target":"graph","created_at":"2026-07-05T00:55:56Z","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/1903.03003/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Dynamic Time Warping (DTW) is a well-known similarity measure for time series. The standard dynamic programming approach to compute the DTW distance of two length-$n$ time series, however, requires~$O(n^2)$ time, which is often too slow for real-world applications. Therefore, many heuristics have been proposed to speed up the DTW computation. These are often based on lower bounding techniques, approximating the DTW distance, or considering special input data such as binary or piecewise constant time series. In this paper, we present a first exact algorithm to compute the DTW distance of two ru","authors_text":"Brijnesh Jain, Maciej Rymar, Mathias Weller, Vincent Froese","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2019-03-07T15:46:20Z","title":"Fast Exact Dynamic Time Warping on Run-Length Encoded Time Series"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.03003","kind":"arxiv","version":5},"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":"sha256:4b7e7a66b95bb1d077160539b3a928167a6aba304c84ab4bf8edc7e55f0632d9","target":"record","created_at":"2026-07-05T00:55:56Z","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":"b87784c28abd8376df98ae3b6dc9e46b1061733bc6661e27c00a4ec7e64e1bef","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2019-03-07T15:46:20Z","title_canon_sha256":"3617f3065446af448e5c68b4cdbef75c8796a664cefa8692e9808df8d969714f"},"schema_version":"1.0","source":{"id":"1903.03003","kind":"arxiv","version":5}},"canonical_sha256":"2aa28f1ea2c3a52036b4362df45e51efbcad9510b40f3f7874179416042232a7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2aa28f1ea2c3a52036b4362df45e51efbcad9510b40f3f7874179416042232a7","first_computed_at":"2026-07-05T00:55:56.583486Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:55:56.583486Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qVJKHIYgbr55JjZnz3mAat3wILEN/FQG+t3e6S8sLpM/ppx4LO3EYtH2b76L9bu1bUSno+h5rsV+lEPmcjUgDg==","signature_status":"signed_v1","signed_at":"2026-07-05T00:55:56.583952Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.03003","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4b7e7a66b95bb1d077160539b3a928167a6aba304c84ab4bf8edc7e55f0632d9","sha256:a14b66e31b51beb2dd3c55ff22c7f47e081fbd9625a0a54bc7ec324807a6c23e"],"state_sha256":"d3426ce39d959f995ae0f30778080a62c7ff4a875023c765a3c419d1e614fcc2"}