{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:TFBQ3KXX2QFNK5IEHPRRSBHOSH","short_pith_number":"pith:TFBQ3KXX","canonical_record":{"source":{"id":"1502.03805","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NA","submitted_at":"2015-02-12T20:50:06Z","cross_cats_sorted":["cs.IT","math.IT"],"title_canon_sha256":"c782d384f273c4212fba02613fd001231e7fe416df42b8220e20d693311cde6f","abstract_canon_sha256":"ebc4e73e6d87091dda42247e919a764e3ce2e901c9b3c83a6a6f302069a3c36a"},"schema_version":"1.0"},"canonical_sha256":"99430daaf7d40ad575043be31904ee91da533f898b636c5517e6ae4b73802e82","source":{"kind":"arxiv","id":"1502.03805","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1502.03805","created_at":"2026-05-18T02:27:08Z"},{"alias_kind":"arxiv_version","alias_value":"1502.03805v1","created_at":"2026-05-18T02:27:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1502.03805","created_at":"2026-05-18T02:27:08Z"},{"alias_kind":"pith_short_12","alias_value":"TFBQ3KXX2QFN","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_16","alias_value":"TFBQ3KXX2QFNK5IE","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_8","alias_value":"TFBQ3KXX","created_at":"2026-05-18T12:29:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:TFBQ3KXX2QFNK5IEHPRRSBHOSH","target":"record","payload":{"canonical_record":{"source":{"id":"1502.03805","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NA","submitted_at":"2015-02-12T20:50:06Z","cross_cats_sorted":["cs.IT","math.IT"],"title_canon_sha256":"c782d384f273c4212fba02613fd001231e7fe416df42b8220e20d693311cde6f","abstract_canon_sha256":"ebc4e73e6d87091dda42247e919a764e3ce2e901c9b3c83a6a6f302069a3c36a"},"schema_version":"1.0"},"canonical_sha256":"99430daaf7d40ad575043be31904ee91da533f898b636c5517e6ae4b73802e82","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:27:08.797428Z","signature_b64":"5EXjA5WJlRQu3NZJyyJGCyxJbg/KH/tS+EIiAgWPPBEMusatzrQQrAXeVqLByaJSNZSdPMORyET6n34z6LD5AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"99430daaf7d40ad575043be31904ee91da533f898b636c5517e6ae4b73802e82","last_reissued_at":"2026-05-18T02:27:08.796609Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:27:08.796609Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1502.03805","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":"2026-05-18T02:27:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AOj77YnoJOy4G1/+Jb8rcwpMLaDPOnM8LDwvnzdM87k2ZLgD9MFq7APBfJLGoKV9wqWT/8gNYd0Nsx1uM4foAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T16:10:52.622542Z"},"content_sha256":"ea62b6b854a635e2cf1df4417ea7cca0a304f163ebdfafaac1d7726c69661abe","schema_version":"1.0","event_id":"sha256:ea62b6b854a635e2cf1df4417ea7cca0a304f163ebdfafaac1d7726c69661abe"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:TFBQ3KXX2QFNK5IEHPRRSBHOSH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"eOMP: Finding Sparser Representation by Recursively Orthonormalizing the Remaining Atoms","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IT","math.IT"],"primary_cat":"cs.NA","authors_text":"Yao Wang, Yuanyi Xue","submitted_at":"2015-02-12T20:50:06Z","abstract_excerpt":"Greedy algorithms for minimizing L0-norm of sparse decomposition have profound application impact on many signal processing problems. In the sparse coding setup, given the observations $\\mathrm{y}$ and the redundant dictionary $\\mathbf{\\Phi}$, one would seek the most sparse coefficient (signal) $\\mathrm{x}$ with a constraint on approximation fidelity. In this work, we propose a greedy algorithm based on the classic orthogonal matching pursuit (OMP) with improved sparsity on $\\mathrm{x}$ and better recovery rate, which we name as eOMP. The key ingredient of the eOMP is recursively performing on"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1502.03805","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":"2026-05-18T02:27:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Zy4dk2KLvLdQlinvz6ijYHKshU+wnUJwj0TSaLXegMm97G0nB5WglP4u9ZnnDPFHZ8/50KGhDebRWWMdkM05AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T16:10:52.623026Z"},"content_sha256":"231113500a7b7f87187ed84c4e355c65beaa0409ce10d37d45fc29ddac34d14f","schema_version":"1.0","event_id":"sha256:231113500a7b7f87187ed84c4e355c65beaa0409ce10d37d45fc29ddac34d14f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TFBQ3KXX2QFNK5IEHPRRSBHOSH/bundle.json","state_url":"https://pith.science/pith/TFBQ3KXX2QFNK5IEHPRRSBHOSH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TFBQ3KXX2QFNK5IEHPRRSBHOSH/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":"2026-05-25T16:10:52Z","links":{"resolver":"https://pith.science/pith/TFBQ3KXX2QFNK5IEHPRRSBHOSH","bundle":"https://pith.science/pith/TFBQ3KXX2QFNK5IEHPRRSBHOSH/bundle.json","state":"https://pith.science/pith/TFBQ3KXX2QFNK5IEHPRRSBHOSH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TFBQ3KXX2QFNK5IEHPRRSBHOSH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:TFBQ3KXX2QFNK5IEHPRRSBHOSH","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":"ebc4e73e6d87091dda42247e919a764e3ce2e901c9b3c83a6a6f302069a3c36a","cross_cats_sorted":["cs.IT","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NA","submitted_at":"2015-02-12T20:50:06Z","title_canon_sha256":"c782d384f273c4212fba02613fd001231e7fe416df42b8220e20d693311cde6f"},"schema_version":"1.0","source":{"id":"1502.03805","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1502.03805","created_at":"2026-05-18T02:27:08Z"},{"alias_kind":"arxiv_version","alias_value":"1502.03805v1","created_at":"2026-05-18T02:27:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1502.03805","created_at":"2026-05-18T02:27:08Z"},{"alias_kind":"pith_short_12","alias_value":"TFBQ3KXX2QFN","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_16","alias_value":"TFBQ3KXX2QFNK5IE","created_at":"2026-05-18T12:29:42Z"},{"alias_kind":"pith_short_8","alias_value":"TFBQ3KXX","created_at":"2026-05-18T12:29:42Z"}],"graph_snapshots":[{"event_id":"sha256:231113500a7b7f87187ed84c4e355c65beaa0409ce10d37d45fc29ddac34d14f","target":"graph","created_at":"2026-05-18T02:27:08Z","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":"Greedy algorithms for minimizing L0-norm of sparse decomposition have profound application impact on many signal processing problems. In the sparse coding setup, given the observations $\\mathrm{y}$ and the redundant dictionary $\\mathbf{\\Phi}$, one would seek the most sparse coefficient (signal) $\\mathrm{x}$ with a constraint on approximation fidelity. In this work, we propose a greedy algorithm based on the classic orthogonal matching pursuit (OMP) with improved sparsity on $\\mathrm{x}$ and better recovery rate, which we name as eOMP. The key ingredient of the eOMP is recursively performing on","authors_text":"Yao Wang, Yuanyi Xue","cross_cats":["cs.IT","math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NA","submitted_at":"2015-02-12T20:50:06Z","title":"eOMP: Finding Sparser Representation by Recursively Orthonormalizing the Remaining Atoms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1502.03805","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:ea62b6b854a635e2cf1df4417ea7cca0a304f163ebdfafaac1d7726c69661abe","target":"record","created_at":"2026-05-18T02:27:08Z","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":"ebc4e73e6d87091dda42247e919a764e3ce2e901c9b3c83a6a6f302069a3c36a","cross_cats_sorted":["cs.IT","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NA","submitted_at":"2015-02-12T20:50:06Z","title_canon_sha256":"c782d384f273c4212fba02613fd001231e7fe416df42b8220e20d693311cde6f"},"schema_version":"1.0","source":{"id":"1502.03805","kind":"arxiv","version":1}},"canonical_sha256":"99430daaf7d40ad575043be31904ee91da533f898b636c5517e6ae4b73802e82","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"99430daaf7d40ad575043be31904ee91da533f898b636c5517e6ae4b73802e82","first_computed_at":"2026-05-18T02:27:08.796609Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:27:08.796609Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5EXjA5WJlRQu3NZJyyJGCyxJbg/KH/tS+EIiAgWPPBEMusatzrQQrAXeVqLByaJSNZSdPMORyET6n34z6LD5AQ==","signature_status":"signed_v1","signed_at":"2026-05-18T02:27:08.797428Z","signed_message":"canonical_sha256_bytes"},"source_id":"1502.03805","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ea62b6b854a635e2cf1df4417ea7cca0a304f163ebdfafaac1d7726c69661abe","sha256:231113500a7b7f87187ed84c4e355c65beaa0409ce10d37d45fc29ddac34d14f"],"state_sha256":"7ff37482c6e29979f0229856d5e03dd9940d2466fd114f22497dd27b4b3ca282"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XcHKyt9lCqtaliScao0LzosIe2zvSEhijbE8HnuBHPhZSN6MdCZl0xLChK0q+ijmTrUdIt5csqyJ0gUymDRnCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T16:10:52.626374Z","bundle_sha256":"fb05852218bb1455521f37fdf2959e0433b982387a192abdb181146630d4f6f7"}}