{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:BT6TIZPIVOH6VVI52E6E277N4V","short_pith_number":"pith:BT6TIZPI","canonical_record":{"source":{"id":"1610.02757","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-10-10T02:52:21Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"0149a646806b681d13577897104bc89f69e3faf0af683301f30174f0da9d8c98","abstract_canon_sha256":"da294235d2fd2fb383266fe1052ddf26d18cf97177eed0e4d2dea0f5b0fb44a2"},"schema_version":"1.0"},"canonical_sha256":"0cfd3465e8ab8fead51dd13c4d7fede56899e26b1bf0645819200ca39d8dc362","source":{"kind":"arxiv","id":"1610.02757","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1610.02757","created_at":"2026-05-18T01:02:50Z"},{"alias_kind":"arxiv_version","alias_value":"1610.02757v1","created_at":"2026-05-18T01:02:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1610.02757","created_at":"2026-05-18T01:02:50Z"},{"alias_kind":"pith_short_12","alias_value":"BT6TIZPIVOH6","created_at":"2026-05-18T12:30:09Z"},{"alias_kind":"pith_short_16","alias_value":"BT6TIZPIVOH6VVI5","created_at":"2026-05-18T12:30:09Z"},{"alias_kind":"pith_short_8","alias_value":"BT6TIZPI","created_at":"2026-05-18T12:30:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:BT6TIZPIVOH6VVI52E6E277N4V","target":"record","payload":{"canonical_record":{"source":{"id":"1610.02757","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-10-10T02:52:21Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"0149a646806b681d13577897104bc89f69e3faf0af683301f30174f0da9d8c98","abstract_canon_sha256":"da294235d2fd2fb383266fe1052ddf26d18cf97177eed0e4d2dea0f5b0fb44a2"},"schema_version":"1.0"},"canonical_sha256":"0cfd3465e8ab8fead51dd13c4d7fede56899e26b1bf0645819200ca39d8dc362","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:02:50.812743Z","signature_b64":"OaorI4qXrClkukgTe3uEiWfV/+nToxcCvJDzrvZBX5+Hv97P8H7uQR4z9F5siXk1YWqud5XZjh4QXZhkQCwcBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0cfd3465e8ab8fead51dd13c4d7fede56899e26b1bf0645819200ca39d8dc362","last_reissued_at":"2026-05-18T01:02:50.812080Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:02:50.812080Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1610.02757","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:02:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BPy3/unlHYZ2WVFZBrPZItGf9kDffbDdmC8FMHgFA27iniMv5csrWkIT7TGClkUuyj2ykwrTKc1In7naYFl3CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-22T22:46:47.986538Z"},"content_sha256":"e67a7065dcb52d6c171d17131335ae574c4353989f4e5629243434d6a823ba1d","schema_version":"1.0","event_id":"sha256:e67a7065dcb52d6c171d17131335ae574c4353989f4e5629243434d6a823ba1d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:BT6TIZPIVOH6VVI52E6E277N4V","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Dataiku's Solution to SPHERE's Activity Recognition Challenge","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Leo Dreyfus-Schmidt, Marc Beillevaire, Maxime Voisin, Pierre Gutierrez, Samuel Ronsin","submitted_at":"2016-10-10T02:52:21Z","abstract_excerpt":"Our team won the second prize of the Safe Aging with SPHERE Challenge organized by SPHERE, in conjunction with ECML-PKDD and Driven Data. The goal of the competition was to recognize activities performed by humans, using sensor data. This paper presents our solution. It is based on a rich pre-processing and state of the art machine learning methods. From the raw train data, we generate a synthetic train set with the same statistical characteristics as the test set. We then perform feature engineering. The machine learning modeling part is based on stacking weak learners through a grid searched"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1610.02757","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:02:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IikbNkOBwUaW1GVo3WZfpqptkzQGYRt2lApvSIwaXLK8bLYv6P2jhbmsoJmqqbI3Qk1lX5UNTrKXBpIohzsYCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-22T22:46:47.986896Z"},"content_sha256":"37d8a298790f9fb98260e961839892deb8b056cb8f9b6d9244213927a3ae314b","schema_version":"1.0","event_id":"sha256:37d8a298790f9fb98260e961839892deb8b056cb8f9b6d9244213927a3ae314b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BT6TIZPIVOH6VVI52E6E277N4V/bundle.json","state_url":"https://pith.science/pith/BT6TIZPIVOH6VVI52E6E277N4V/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BT6TIZPIVOH6VVI52E6E277N4V/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-22T22:46:47Z","links":{"resolver":"https://pith.science/pith/BT6TIZPIVOH6VVI52E6E277N4V","bundle":"https://pith.science/pith/BT6TIZPIVOH6VVI52E6E277N4V/bundle.json","state":"https://pith.science/pith/BT6TIZPIVOH6VVI52E6E277N4V/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BT6TIZPIVOH6VVI52E6E277N4V/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:BT6TIZPIVOH6VVI52E6E277N4V","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":"da294235d2fd2fb383266fe1052ddf26d18cf97177eed0e4d2dea0f5b0fb44a2","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-10-10T02:52:21Z","title_canon_sha256":"0149a646806b681d13577897104bc89f69e3faf0af683301f30174f0da9d8c98"},"schema_version":"1.0","source":{"id":"1610.02757","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1610.02757","created_at":"2026-05-18T01:02:50Z"},{"alias_kind":"arxiv_version","alias_value":"1610.02757v1","created_at":"2026-05-18T01:02:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1610.02757","created_at":"2026-05-18T01:02:50Z"},{"alias_kind":"pith_short_12","alias_value":"BT6TIZPIVOH6","created_at":"2026-05-18T12:30:09Z"},{"alias_kind":"pith_short_16","alias_value":"BT6TIZPIVOH6VVI5","created_at":"2026-05-18T12:30:09Z"},{"alias_kind":"pith_short_8","alias_value":"BT6TIZPI","created_at":"2026-05-18T12:30:09Z"}],"graph_snapshots":[{"event_id":"sha256:37d8a298790f9fb98260e961839892deb8b056cb8f9b6d9244213927a3ae314b","target":"graph","created_at":"2026-05-18T01:02:50Z","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":"Our team won the second prize of the Safe Aging with SPHERE Challenge organized by SPHERE, in conjunction with ECML-PKDD and Driven Data. The goal of the competition was to recognize activities performed by humans, using sensor data. This paper presents our solution. It is based on a rich pre-processing and state of the art machine learning methods. From the raw train data, we generate a synthetic train set with the same statistical characteristics as the test set. We then perform feature engineering. The machine learning modeling part is based on stacking weak learners through a grid searched","authors_text":"Leo Dreyfus-Schmidt, Marc Beillevaire, Maxime Voisin, Pierre Gutierrez, Samuel Ronsin","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-10-10T02:52:21Z","title":"Dataiku's Solution to SPHERE's Activity Recognition Challenge"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1610.02757","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:e67a7065dcb52d6c171d17131335ae574c4353989f4e5629243434d6a823ba1d","target":"record","created_at":"2026-05-18T01:02:50Z","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":"da294235d2fd2fb383266fe1052ddf26d18cf97177eed0e4d2dea0f5b0fb44a2","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-10-10T02:52:21Z","title_canon_sha256":"0149a646806b681d13577897104bc89f69e3faf0af683301f30174f0da9d8c98"},"schema_version":"1.0","source":{"id":"1610.02757","kind":"arxiv","version":1}},"canonical_sha256":"0cfd3465e8ab8fead51dd13c4d7fede56899e26b1bf0645819200ca39d8dc362","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0cfd3465e8ab8fead51dd13c4d7fede56899e26b1bf0645819200ca39d8dc362","first_computed_at":"2026-05-18T01:02:50.812080Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:02:50.812080Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"OaorI4qXrClkukgTe3uEiWfV/+nToxcCvJDzrvZBX5+Hv97P8H7uQR4z9F5siXk1YWqud5XZjh4QXZhkQCwcBA==","signature_status":"signed_v1","signed_at":"2026-05-18T01:02:50.812743Z","signed_message":"canonical_sha256_bytes"},"source_id":"1610.02757","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e67a7065dcb52d6c171d17131335ae574c4353989f4e5629243434d6a823ba1d","sha256:37d8a298790f9fb98260e961839892deb8b056cb8f9b6d9244213927a3ae314b"],"state_sha256":"e6219ecbda5bb1e23d16b0daea2e1ed637e461caf91e2d21e01d777a60bc490d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FHidDGnkPWaxaDS8Myr1vxdNZfkKd9uhAOCtlWLpeF7fU1gcwNPhgbc8hS6v/PiN5rOj9PRQsEnM6KhkBoZzCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-22T22:46:47.988955Z","bundle_sha256":"b42db890d4332760c0f4fc2178ac17b0484692f7d35fcabdd31f803d5549d775"}}