{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:GJAMFOO5P4AUEUBCHQT3Q6RB6J","short_pith_number":"pith:GJAMFOO5","canonical_record":{"source":{"id":"1712.09379","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2017-12-26T19:40:47Z","cross_cats_sorted":["cs.DS","cs.LG","cs.NA","math.NA","stat.ML"],"title_canon_sha256":"c588389dc08147e0ef0677011958ff77299825e3baca646d0978ae6506057c3e","abstract_canon_sha256":"5b6342e31484d8ea539052d59600821332bb5c412805a71da349b622590a8e91"},"schema_version":"1.0"},"canonical_sha256":"3240c2b9dd7f014250223c27b87a21f26976b5688dec0655fb44e9b782e5eaea","source":{"kind":"arxiv","id":"1712.09379","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.09379","created_at":"2026-06-04T19:11:22Z"},{"alias_kind":"arxiv_version","alias_value":"1712.09379v2","created_at":"2026-06-04T19:11:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.09379","created_at":"2026-06-04T19:11:22Z"},{"alias_kind":"pith_short_12","alias_value":"GJAMFOO5P4AU","created_at":"2026-06-04T19:11:22Z"},{"alias_kind":"pith_short_16","alias_value":"GJAMFOO5P4AUEUBC","created_at":"2026-06-04T19:11:22Z"},{"alias_kind":"pith_short_8","alias_value":"GJAMFOO5","created_at":"2026-06-04T19:11:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:GJAMFOO5P4AUEUBCHQT3Q6RB6J","target":"record","payload":{"canonical_record":{"source":{"id":"1712.09379","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2017-12-26T19:40:47Z","cross_cats_sorted":["cs.DS","cs.LG","cs.NA","math.NA","stat.ML"],"title_canon_sha256":"c588389dc08147e0ef0677011958ff77299825e3baca646d0978ae6506057c3e","abstract_canon_sha256":"5b6342e31484d8ea539052d59600821332bb5c412805a71da349b622590a8e91"},"schema_version":"1.0"},"canonical_sha256":"3240c2b9dd7f014250223c27b87a21f26976b5688dec0655fb44e9b782e5eaea","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-04T19:11:22.559133Z","signature_b64":"0hU7iCGLfhi4QU4aOHI0WN4E2i35pyu+SdMw1MQik1j+AcdUgelqXB+RVrRO5j6dosUG24k6gfQXyRzlIEkvCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3240c2b9dd7f014250223c27b87a21f26976b5688dec0655fb44e9b782e5eaea","last_reissued_at":"2026-06-04T19:11:22.558601Z","signature_status":"signed_v1","first_computed_at":"2026-06-04T19:11:22.558601Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1712.09379","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":"2026-06-04T19:11:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jlMvIwh4ctQ2BljqZ8m2wQW8t2XftL9mcQH9ZKtI1xa2MdUnvap3fH/cCvw7l17Io+2LytossohrkX12iHpIAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T19:21:41.743834Z"},"content_sha256":"2f0c60a0a97a28cef2fbac07e9b1751b88832b14e6d134bfffcc8e9e7cddbacc","schema_version":"1.0","event_id":"sha256:2f0c60a0a97a28cef2fbac07e9b1751b88832b14e6d134bfffcc8e9e7cddbacc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:GJAMFOO5P4AUEUBCHQT3Q6RB6J","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"IHT dies hard: Provable accelerated Iterative Hard Thresholding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DS","cs.LG","cs.NA","math.NA","stat.ML"],"primary_cat":"math.OC","authors_text":"Anastasios Kyrillidis, Rajiv Khanna","submitted_at":"2017-12-26T19:40:47Z","abstract_excerpt":"We study --both in theory and practice-- the use of momentum motions in classic iterative hard thresholding (IHT) methods. By simply modifying plain IHT, we investigate its convergence behavior on convex optimization criteria with non-convex constraints, under standard assumptions. In diverse scenaria, we observe that acceleration in IHT leads to significant improvements, compared to state of the art projected gradient descent and Frank-Wolfe variants. As a byproduct of our inspection, we study the impact of selecting the momentum parameter: similar to convex settings, two modes of behavior ar"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.09379","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/1712.09379/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":"2026-06-04T19:11:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AFY0j6D+uCPWg15kEj5ITQbCuJ3UDeYKK86EGjM29pCx275Q+UrzQA2pAtyJNcv+TtFRzSm9dTHDQ4vH4fZQCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T19:21:41.744207Z"},"content_sha256":"980851c8f0566b5ec3eb9c93f48cd4158a9416c6dc43555ae6a3b43a8460b6c9","schema_version":"1.0","event_id":"sha256:980851c8f0566b5ec3eb9c93f48cd4158a9416c6dc43555ae6a3b43a8460b6c9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GJAMFOO5P4AUEUBCHQT3Q6RB6J/bundle.json","state_url":"https://pith.science/pith/GJAMFOO5P4AUEUBCHQT3Q6RB6J/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GJAMFOO5P4AUEUBCHQT3Q6RB6J/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":"2026-06-06T19:21:41Z","links":{"resolver":"https://pith.science/pith/GJAMFOO5P4AUEUBCHQT3Q6RB6J","bundle":"https://pith.science/pith/GJAMFOO5P4AUEUBCHQT3Q6RB6J/bundle.json","state":"https://pith.science/pith/GJAMFOO5P4AUEUBCHQT3Q6RB6J/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GJAMFOO5P4AUEUBCHQT3Q6RB6J/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:GJAMFOO5P4AUEUBCHQT3Q6RB6J","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":"5b6342e31484d8ea539052d59600821332bb5c412805a71da349b622590a8e91","cross_cats_sorted":["cs.DS","cs.LG","cs.NA","math.NA","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2017-12-26T19:40:47Z","title_canon_sha256":"c588389dc08147e0ef0677011958ff77299825e3baca646d0978ae6506057c3e"},"schema_version":"1.0","source":{"id":"1712.09379","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.09379","created_at":"2026-06-04T19:11:22Z"},{"alias_kind":"arxiv_version","alias_value":"1712.09379v2","created_at":"2026-06-04T19:11:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.09379","created_at":"2026-06-04T19:11:22Z"},{"alias_kind":"pith_short_12","alias_value":"GJAMFOO5P4AU","created_at":"2026-06-04T19:11:22Z"},{"alias_kind":"pith_short_16","alias_value":"GJAMFOO5P4AUEUBC","created_at":"2026-06-04T19:11:22Z"},{"alias_kind":"pith_short_8","alias_value":"GJAMFOO5","created_at":"2026-06-04T19:11:22Z"}],"graph_snapshots":[{"event_id":"sha256:980851c8f0566b5ec3eb9c93f48cd4158a9416c6dc43555ae6a3b43a8460b6c9","target":"graph","created_at":"2026-06-04T19:11:22Z","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/1712.09379/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We study --both in theory and practice-- the use of momentum motions in classic iterative hard thresholding (IHT) methods. By simply modifying plain IHT, we investigate its convergence behavior on convex optimization criteria with non-convex constraints, under standard assumptions. In diverse scenaria, we observe that acceleration in IHT leads to significant improvements, compared to state of the art projected gradient descent and Frank-Wolfe variants. As a byproduct of our inspection, we study the impact of selecting the momentum parameter: similar to convex settings, two modes of behavior ar","authors_text":"Anastasios Kyrillidis, Rajiv Khanna","cross_cats":["cs.DS","cs.LG","cs.NA","math.NA","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2017-12-26T19:40:47Z","title":"IHT dies hard: Provable accelerated Iterative Hard Thresholding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.09379","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":"sha256:2f0c60a0a97a28cef2fbac07e9b1751b88832b14e6d134bfffcc8e9e7cddbacc","target":"record","created_at":"2026-06-04T19:11:22Z","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":"5b6342e31484d8ea539052d59600821332bb5c412805a71da349b622590a8e91","cross_cats_sorted":["cs.DS","cs.LG","cs.NA","math.NA","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2017-12-26T19:40:47Z","title_canon_sha256":"c588389dc08147e0ef0677011958ff77299825e3baca646d0978ae6506057c3e"},"schema_version":"1.0","source":{"id":"1712.09379","kind":"arxiv","version":2}},"canonical_sha256":"3240c2b9dd7f014250223c27b87a21f26976b5688dec0655fb44e9b782e5eaea","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3240c2b9dd7f014250223c27b87a21f26976b5688dec0655fb44e9b782e5eaea","first_computed_at":"2026-06-04T19:11:22.558601Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-04T19:11:22.558601Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0hU7iCGLfhi4QU4aOHI0WN4E2i35pyu+SdMw1MQik1j+AcdUgelqXB+RVrRO5j6dosUG24k6gfQXyRzlIEkvCA==","signature_status":"signed_v1","signed_at":"2026-06-04T19:11:22.559133Z","signed_message":"canonical_sha256_bytes"},"source_id":"1712.09379","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2f0c60a0a97a28cef2fbac07e9b1751b88832b14e6d134bfffcc8e9e7cddbacc","sha256:980851c8f0566b5ec3eb9c93f48cd4158a9416c6dc43555ae6a3b43a8460b6c9"],"state_sha256":"db35fd954d4fe3b37d7f77d1913e583f7d71907e6a2682ea59e151abc1f2068a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UJo2kHh7Jp4ZaEL9iwfoAHxaLfays43jLPOPJ+i0RrV4i6StHrYFrE9LUuwWPVAbcTkXmZBmSF+r7eDeeOU8CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T19:21:41.747671Z","bundle_sha256":"eb4952adce6979e23a044f6a5ab93d02001741b6564669f85e28212decb96d63"}}