{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:QDHRXCEDVNJ4ORRTNSNZUAHY46","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":"8cdd00c6d96194905ef08ee6e05825bd98d42e34c710a707cf4d755a2f8ff6d1","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-11-10T09:25:12Z","title_canon_sha256":"306ee1224dd44299e2aa4f7bef77b7e33389c9ee4a0a9386e65693813db80355"},"schema_version":"1.0","source":{"id":"1611.03231","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.03231","created_at":"2026-05-18T00:59:40Z"},{"alias_kind":"arxiv_version","alias_value":"1611.03231v1","created_at":"2026-05-18T00:59:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.03231","created_at":"2026-05-18T00:59:40Z"},{"alias_kind":"pith_short_12","alias_value":"QDHRXCEDVNJ4","created_at":"2026-05-18T12:30:39Z"},{"alias_kind":"pith_short_16","alias_value":"QDHRXCEDVNJ4ORRT","created_at":"2026-05-18T12:30:39Z"},{"alias_kind":"pith_short_8","alias_value":"QDHRXCED","created_at":"2026-05-18T12:30:39Z"}],"graph_snapshots":[{"event_id":"sha256:cc76dabdf01ce4030ca31bd5e4ded53f3f9ddb0878b6fbec3e12bf2cd7875af8","target":"graph","created_at":"2026-05-18T00:59:40Z","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":"Direct contextual policy search methods learn to improve policy parameters and simultaneously generalize these parameters to different context or task variables. However, learning from high-dimensional context variables, such as camera images, is still a prominent problem in many real-world tasks. A naive application of unsupervised dimensionality reduction methods to the context variables, such as principal component analysis, is insufficient as task-relevant input may be ignored. In this paper, we propose a contextual policy search method in the model-based relative entropy stochastic search","authors_text":"Gerhard Neumann, Herke van Hoof, Jan Peters, Masashi Sugiyama, Simone Parisi, Voot Tangkaratt","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-11-10T09:25:12Z","title":"Policy Search with High-Dimensional Context Variables"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.03231","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:efd9798a88337bc6870ca577cb21d9e1b63c5e5be35d2cdb75a971b881aeec76","target":"record","created_at":"2026-05-18T00:59:40Z","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":"8cdd00c6d96194905ef08ee6e05825bd98d42e34c710a707cf4d755a2f8ff6d1","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-11-10T09:25:12Z","title_canon_sha256":"306ee1224dd44299e2aa4f7bef77b7e33389c9ee4a0a9386e65693813db80355"},"schema_version":"1.0","source":{"id":"1611.03231","kind":"arxiv","version":1}},"canonical_sha256":"80cf1b8883ab53c746336c9b9a00f8e7874cb52ed034296ac318b660f09234b0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"80cf1b8883ab53c746336c9b9a00f8e7874cb52ed034296ac318b660f09234b0","first_computed_at":"2026-05-18T00:59:40.896980Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:59:40.896980Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IrxTOFO/+YhT0RVBYy1nf/XrXJDUo3NhrJXmjM93TaEr/JgdbQekqIKIWBJ8vRgrSEJ2hDiqrlWHLZyUQ/0KAw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:59:40.897905Z","signed_message":"canonical_sha256_bytes"},"source_id":"1611.03231","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:efd9798a88337bc6870ca577cb21d9e1b63c5e5be35d2cdb75a971b881aeec76","sha256:cc76dabdf01ce4030ca31bd5e4ded53f3f9ddb0878b6fbec3e12bf2cd7875af8"],"state_sha256":"66b3a59c00f945e0ea3940fd5855bcf824f1ea59ffdf5dfd629a131a70bfcaca"}