{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:HV3HSZ7K2KVY3HSUJRHIGNQRT7","short_pith_number":"pith:HV3HSZ7K","schema_version":"1.0","canonical_sha256":"3d767967ead2ab8d9e544c4e8336119ffa748e195aeefbe76ae61d92ca364fb8","source":{"kind":"arxiv","id":"1510.05477","version":1},"attestation_state":"computed","paper":{"title":"Accelerometer based Activity Classification with Variational Inference on Sticky HDP-SLDS","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Koray Ozcan, Mehmet Emin Basbug, Senem Velipasalar","submitted_at":"2015-10-19T13:58:37Z","abstract_excerpt":"As part of daily monitoring of human activities, wearable sensors and devices are becoming increasingly popular sources of data. With the advent of smartphones equipped with acceloremeter, gyroscope and camera; it is now possible to develop activity classification platforms everyone can use conveniently. In this paper, we propose a fast inference method for an unsupervised non-parametric time series model namely variational inference for sticky HDP-SLDS(Hierarchical Dirichlet Process Switching Linear Dynamical System). We show that the proposed algorithm can differentiate various indoor activi"},"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":"1510.05477","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2015-10-19T13:58:37Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"ae585fb188a81260abe0c23c87ffd4edb77ea7822ec3f92617a71d474b9690b3","abstract_canon_sha256":"982e56a6b243e3e108529876598d1dbf279e5b06b388ef5114938beb525def2f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:29:52.257755Z","signature_b64":"3H81u/as8sYUidHi+8RI2jG3X38tzF1RCbB3ts6I20vFd1h5vpCVUG7rnko/wn1PVi1kWg8zQVLFOEpPJ2pmDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3d767967ead2ab8d9e544c4e8336119ffa748e195aeefbe76ae61d92ca364fb8","last_reissued_at":"2026-05-18T01:29:52.257261Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:29:52.257261Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Accelerometer based Activity Classification with Variational Inference on Sticky HDP-SLDS","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Koray Ozcan, Mehmet Emin Basbug, Senem Velipasalar","submitted_at":"2015-10-19T13:58:37Z","abstract_excerpt":"As part of daily monitoring of human activities, wearable sensors and devices are becoming increasingly popular sources of data. With the advent of smartphones equipped with acceloremeter, gyroscope and camera; it is now possible to develop activity classification platforms everyone can use conveniently. In this paper, we propose a fast inference method for an unsupervised non-parametric time series model namely variational inference for sticky HDP-SLDS(Hierarchical Dirichlet Process Switching Linear Dynamical System). We show that the proposed algorithm can differentiate various indoor activi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1510.05477","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":"1510.05477","created_at":"2026-05-18T01:29:52.257356+00:00"},{"alias_kind":"arxiv_version","alias_value":"1510.05477v1","created_at":"2026-05-18T01:29:52.257356+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1510.05477","created_at":"2026-05-18T01:29:52.257356+00:00"},{"alias_kind":"pith_short_12","alias_value":"HV3HSZ7K2KVY","created_at":"2026-05-18T12:29:25.134429+00:00"},{"alias_kind":"pith_short_16","alias_value":"HV3HSZ7K2KVY3HSU","created_at":"2026-05-18T12:29:25.134429+00:00"},{"alias_kind":"pith_short_8","alias_value":"HV3HSZ7K","created_at":"2026-05-18T12:29:25.134429+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/HV3HSZ7K2KVY3HSUJRHIGNQRT7","json":"https://pith.science/pith/HV3HSZ7K2KVY3HSUJRHIGNQRT7.json","graph_json":"https://pith.science/api/pith-number/HV3HSZ7K2KVY3HSUJRHIGNQRT7/graph.json","events_json":"https://pith.science/api/pith-number/HV3HSZ7K2KVY3HSUJRHIGNQRT7/events.json","paper":"https://pith.science/paper/HV3HSZ7K"},"agent_actions":{"view_html":"https://pith.science/pith/HV3HSZ7K2KVY3HSUJRHIGNQRT7","download_json":"https://pith.science/pith/HV3HSZ7K2KVY3HSUJRHIGNQRT7.json","view_paper":"https://pith.science/paper/HV3HSZ7K","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1510.05477&json=true","fetch_graph":"https://pith.science/api/pith-number/HV3HSZ7K2KVY3HSUJRHIGNQRT7/graph.json","fetch_events":"https://pith.science/api/pith-number/HV3HSZ7K2KVY3HSUJRHIGNQRT7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HV3HSZ7K2KVY3HSUJRHIGNQRT7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HV3HSZ7K2KVY3HSUJRHIGNQRT7/action/storage_attestation","attest_author":"https://pith.science/pith/HV3HSZ7K2KVY3HSUJRHIGNQRT7/action/author_attestation","sign_citation":"https://pith.science/pith/HV3HSZ7K2KVY3HSUJRHIGNQRT7/action/citation_signature","submit_replication":"https://pith.science/pith/HV3HSZ7K2KVY3HSUJRHIGNQRT7/action/replication_record"}},"created_at":"2026-05-18T01:29:52.257356+00:00","updated_at":"2026-05-18T01:29:52.257356+00:00"}