{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:LI7DPSLASBBPZA3I5DJSXYRHFX","short_pith_number":"pith:LI7DPSLA","canonical_record":{"source":{"id":"1911.03827","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-10T02:01:20Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"a1ac9d68f0c7d7414287d1c78e7c4d1020e89a7c6dce1cd34134428451eac05e","abstract_canon_sha256":"aba6ff2b0e6bcbc883bf71e309e4dfe19716f4f192ba28f473b01d0ea1522456"},"schema_version":"1.0"},"canonical_sha256":"5a3e37c9609042fc8368e8d32be2272dc340d5782758b0cf25d6df58714f4fee","source":{"kind":"arxiv","id":"1911.03827","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.03827","created_at":"2026-07-05T00:35:34Z"},{"alias_kind":"arxiv_version","alias_value":"1911.03827v2","created_at":"2026-07-05T00:35:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.03827","created_at":"2026-07-05T00:35:34Z"},{"alias_kind":"pith_short_12","alias_value":"LI7DPSLASBBP","created_at":"2026-07-05T00:35:34Z"},{"alias_kind":"pith_short_16","alias_value":"LI7DPSLASBBPZA3I","created_at":"2026-07-05T00:35:34Z"},{"alias_kind":"pith_short_8","alias_value":"LI7DPSLA","created_at":"2026-07-05T00:35:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:LI7DPSLASBBPZA3I5DJSXYRHFX","target":"record","payload":{"canonical_record":{"source":{"id":"1911.03827","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-10T02:01:20Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"a1ac9d68f0c7d7414287d1c78e7c4d1020e89a7c6dce1cd34134428451eac05e","abstract_canon_sha256":"aba6ff2b0e6bcbc883bf71e309e4dfe19716f4f192ba28f473b01d0ea1522456"},"schema_version":"1.0"},"canonical_sha256":"5a3e37c9609042fc8368e8d32be2272dc340d5782758b0cf25d6df58714f4fee","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:35:34.230551Z","signature_b64":"eVVsijGCT+Be4fjPbEJgU2/IWlCLMKRLk1ElWhtDnAUzs5JSn00AxyEok5o84by9rf4RIZpWS8Hj/0cMmd1XDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5a3e37c9609042fc8368e8d32be2272dc340d5782758b0cf25d6df58714f4fee","last_reissued_at":"2026-07-05T00:35:34.230127Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:35:34.230127Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1911.03827","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:35:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"adK+3HXtzdFyCqwegPnQC8vgxjNJ1a1MftSzTE6ztXZS8xEVtrK0flN7om0GIoLwTQ8qYGsGRQu4bQIOFJ7fDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T22:00:13.311242Z"},"content_sha256":"77102dd994d2796abe7324e1727a70dd53c2491bd8c98cd211c2e0a85f90457e","schema_version":"1.0","event_id":"sha256:77102dd994d2796abe7324e1727a70dd53c2491bd8c98cd211c2e0a85f90457e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:LI7DPSLASBBPZA3I5DJSXYRHFX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Online Optimization with Predictions and Non-convex Losses","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Adam Wierman, Gautam Goel, Yiheng Lin","submitted_at":"2019-11-10T02:01:20Z","abstract_excerpt":"We study online optimization in a setting where an online learner seeks to optimize a per-round hitting cost, which may be non-convex, while incurring a movement cost when changing actions between rounds. We ask: \\textit{under what general conditions is it possible for an online learner to leverage predictions of future cost functions in order to achieve near-optimal costs?} Prior work has provided near-optimal online algorithms for specific combinations of assumptions about hitting and switching costs, but no general results are known. In this work, we give two general sufficient conditions t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.03827","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1911.03827/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T00:35:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3ZDgYYkv5PoozV+39biGg324riz6gu+7j01Iuu9y8DAZ8rvoS5ImndT728DAyEYWTpk4SWPM+E+ZsxBsIjZACg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T22:00:13.312214Z"},"content_sha256":"f3d1b312011b9cf391368d40decd5df69b0d02cbc88a0941c1388908e21aee61","schema_version":"1.0","event_id":"sha256:f3d1b312011b9cf391368d40decd5df69b0d02cbc88a0941c1388908e21aee61"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LI7DPSLASBBPZA3I5DJSXYRHFX/bundle.json","state_url":"https://pith.science/pith/LI7DPSLASBBPZA3I5DJSXYRHFX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LI7DPSLASBBPZA3I5DJSXYRHFX/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":"2026-08-17T22:00:13Z","links":{"resolver":"https://pith.science/pith/LI7DPSLASBBPZA3I5DJSXYRHFX","bundle":"https://pith.science/pith/LI7DPSLASBBPZA3I5DJSXYRHFX/bundle.json","state":"https://pith.science/pith/LI7DPSLASBBPZA3I5DJSXYRHFX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LI7DPSLASBBPZA3I5DJSXYRHFX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:LI7DPSLASBBPZA3I5DJSXYRHFX","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":"aba6ff2b0e6bcbc883bf71e309e4dfe19716f4f192ba28f473b01d0ea1522456","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-10T02:01:20Z","title_canon_sha256":"a1ac9d68f0c7d7414287d1c78e7c4d1020e89a7c6dce1cd34134428451eac05e"},"schema_version":"1.0","source":{"id":"1911.03827","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.03827","created_at":"2026-07-05T00:35:34Z"},{"alias_kind":"arxiv_version","alias_value":"1911.03827v2","created_at":"2026-07-05T00:35:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.03827","created_at":"2026-07-05T00:35:34Z"},{"alias_kind":"pith_short_12","alias_value":"LI7DPSLASBBP","created_at":"2026-07-05T00:35:34Z"},{"alias_kind":"pith_short_16","alias_value":"LI7DPSLASBBPZA3I","created_at":"2026-07-05T00:35:34Z"},{"alias_kind":"pith_short_8","alias_value":"LI7DPSLA","created_at":"2026-07-05T00:35:34Z"}],"graph_snapshots":[{"event_id":"sha256:f3d1b312011b9cf391368d40decd5df69b0d02cbc88a0941c1388908e21aee61","target":"graph","created_at":"2026-07-05T00:35:34Z","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/1911.03827/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We study online optimization in a setting where an online learner seeks to optimize a per-round hitting cost, which may be non-convex, while incurring a movement cost when changing actions between rounds. We ask: \\textit{under what general conditions is it possible for an online learner to leverage predictions of future cost functions in order to achieve near-optimal costs?} Prior work has provided near-optimal online algorithms for specific combinations of assumptions about hitting and switching costs, but no general results are known. In this work, we give two general sufficient conditions t","authors_text":"Adam Wierman, Gautam Goel, Yiheng Lin","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-10T02:01:20Z","title":"Online Optimization with Predictions and Non-convex Losses"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.03827","kind":"arxiv","version":2},"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":"sha256:77102dd994d2796abe7324e1727a70dd53c2491bd8c98cd211c2e0a85f90457e","target":"record","created_at":"2026-07-05T00:35:34Z","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":"aba6ff2b0e6bcbc883bf71e309e4dfe19716f4f192ba28f473b01d0ea1522456","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-11-10T02:01:20Z","title_canon_sha256":"a1ac9d68f0c7d7414287d1c78e7c4d1020e89a7c6dce1cd34134428451eac05e"},"schema_version":"1.0","source":{"id":"1911.03827","kind":"arxiv","version":2}},"canonical_sha256":"5a3e37c9609042fc8368e8d32be2272dc340d5782758b0cf25d6df58714f4fee","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5a3e37c9609042fc8368e8d32be2272dc340d5782758b0cf25d6df58714f4fee","first_computed_at":"2026-07-05T00:35:34.230127Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:35:34.230127Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eVVsijGCT+Be4fjPbEJgU2/IWlCLMKRLk1ElWhtDnAUzs5JSn00AxyEok5o84by9rf4RIZpWS8Hj/0cMmd1XDw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:35:34.230551Z","signed_message":"canonical_sha256_bytes"},"source_id":"1911.03827","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:77102dd994d2796abe7324e1727a70dd53c2491bd8c98cd211c2e0a85f90457e","sha256:f3d1b312011b9cf391368d40decd5df69b0d02cbc88a0941c1388908e21aee61"],"state_sha256":"acae1a72329d79814919a712e54ab3b27c2107119712ebaeb939571393586887"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"amN7h3XB4qMN+HDwEmRAza0UMU38XEHqXxZ2GBSvseVMPIvGGA0gV7TtJpAhV/yO9xDcquEcR9UL+0KW/+b7BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T22:00:13.318957Z","bundle_sha256":"63861eb8395fc591eb9666e9900d75e34ecd724ca8b2cca54bfdd0304821032f"}}