{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:4VUZLCE7U5XRLYQVJ5AOOSJHF7","short_pith_number":"pith:4VUZLCE7","canonical_record":{"source":{"id":"1410.3682","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2014-10-14T13:30:39Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"a892c1a3aa7bc9cf5eb48a1b2b13f2c80e34616408e028f2422febc07c3ea729","abstract_canon_sha256":"0fedd622087400703681f996d3acdfbcab6090fff457484df30ad41f6eb1f233"},"schema_version":"1.0"},"canonical_sha256":"e56995889fa76f15e2154f40e749272fedcddc8c934e4c87d0b5481447d7d961","source":{"kind":"arxiv","id":"1410.3682","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1410.3682","created_at":"2026-05-18T01:41:48Z"},{"alias_kind":"arxiv_version","alias_value":"1410.3682v1","created_at":"2026-05-18T01:41:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1410.3682","created_at":"2026-05-18T01:41:48Z"},{"alias_kind":"pith_short_12","alias_value":"4VUZLCE7U5XR","created_at":"2026-05-18T12:28:14Z"},{"alias_kind":"pith_short_16","alias_value":"4VUZLCE7U5XRLYQV","created_at":"2026-05-18T12:28:14Z"},{"alias_kind":"pith_short_8","alias_value":"4VUZLCE7","created_at":"2026-05-18T12:28:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:4VUZLCE7U5XRLYQVJ5AOOSJHF7","target":"record","payload":{"canonical_record":{"source":{"id":"1410.3682","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2014-10-14T13:30:39Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"a892c1a3aa7bc9cf5eb48a1b2b13f2c80e34616408e028f2422febc07c3ea729","abstract_canon_sha256":"0fedd622087400703681f996d3acdfbcab6090fff457484df30ad41f6eb1f233"},"schema_version":"1.0"},"canonical_sha256":"e56995889fa76f15e2154f40e749272fedcddc8c934e4c87d0b5481447d7d961","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:41:48.553330Z","signature_b64":"6B/BFRbYXC3ELKQoEvsNsX5tTjSr/Byj6iKGfyIIc29i5/UK7MHvQE0Eylh/wydfiZFRf4o87qKyGxmK3BMfDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e56995889fa76f15e2154f40e749272fedcddc8c934e4c87d0b5481447d7d961","last_reissued_at":"2026-05-18T01:41:48.552815Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:41:48.552815Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1410.3682","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":"2026-05-18T01:41:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yt89P3VGSmhXF4ByYFtSQj6rbn5F9OEC/6808HecFstowEG45oL+0iMVTFulIdjzy3xYhpq5cxHOzfM4kkxhAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T07:47:03.380097Z"},"content_sha256":"d1095c33ec9b3bdb9ccb85e36f8b815dbcd4022fd068884d1f962bfa4560e593","schema_version":"1.0","event_id":"sha256:d1095c33ec9b3bdb9ccb85e36f8b815dbcd4022fd068884d1f962bfa4560e593"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:4VUZLCE7U5XRLYQVJ5AOOSJHF7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Greedy Sparsity-Promoting Algorithms for Distributed Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Gerasimos Mileounis, Nicholas Kalouptsidis, Sergios Theodoridis, Symeon Chouvardas","submitted_at":"2014-10-14T13:30:39Z","abstract_excerpt":"This paper focuses on the development of novel greedy techniques for distributed learning under sparsity constraints. Greedy techniques have widely been used in centralized systems due to their low computational requirements and at the same time their relatively good performance in estimating sparse parameter vectors/signals. The paper reports two new algorithms in the context of sparsity--aware learning. In both cases, the goal is first to identify the support set of the unknown signal and then to estimate the non--zero values restricted to the active support set. First, an iterative greedy m"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1410.3682","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":"2026-05-18T01:41:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"56d2wkqJt08Yepo1geOKpUb+WODHkRKNRbImxBcgIZ3C+qqp8gPuqlIpLG7gPhV/WY96jRd7sLFJrFkgBBQhBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T07:47:03.380790Z"},"content_sha256":"d4c81baa729a7e30bd8fe71319d1b1ee1f000eb96beb71a5d6cceb3508e104b3","schema_version":"1.0","event_id":"sha256:d4c81baa729a7e30bd8fe71319d1b1ee1f000eb96beb71a5d6cceb3508e104b3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4VUZLCE7U5XRLYQVJ5AOOSJHF7/bundle.json","state_url":"https://pith.science/pith/4VUZLCE7U5XRLYQVJ5AOOSJHF7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4VUZLCE7U5XRLYQVJ5AOOSJHF7/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":"2026-05-22T07:47:03Z","links":{"resolver":"https://pith.science/pith/4VUZLCE7U5XRLYQVJ5AOOSJHF7","bundle":"https://pith.science/pith/4VUZLCE7U5XRLYQVJ5AOOSJHF7/bundle.json","state":"https://pith.science/pith/4VUZLCE7U5XRLYQVJ5AOOSJHF7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4VUZLCE7U5XRLYQVJ5AOOSJHF7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:4VUZLCE7U5XRLYQVJ5AOOSJHF7","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":"0fedd622087400703681f996d3acdfbcab6090fff457484df30ad41f6eb1f233","cross_cats_sorted":["math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2014-10-14T13:30:39Z","title_canon_sha256":"a892c1a3aa7bc9cf5eb48a1b2b13f2c80e34616408e028f2422febc07c3ea729"},"schema_version":"1.0","source":{"id":"1410.3682","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1410.3682","created_at":"2026-05-18T01:41:48Z"},{"alias_kind":"arxiv_version","alias_value":"1410.3682v1","created_at":"2026-05-18T01:41:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1410.3682","created_at":"2026-05-18T01:41:48Z"},{"alias_kind":"pith_short_12","alias_value":"4VUZLCE7U5XR","created_at":"2026-05-18T12:28:14Z"},{"alias_kind":"pith_short_16","alias_value":"4VUZLCE7U5XRLYQV","created_at":"2026-05-18T12:28:14Z"},{"alias_kind":"pith_short_8","alias_value":"4VUZLCE7","created_at":"2026-05-18T12:28:14Z"}],"graph_snapshots":[{"event_id":"sha256:d4c81baa729a7e30bd8fe71319d1b1ee1f000eb96beb71a5d6cceb3508e104b3","target":"graph","created_at":"2026-05-18T01:41:48Z","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":"This paper focuses on the development of novel greedy techniques for distributed learning under sparsity constraints. Greedy techniques have widely been used in centralized systems due to their low computational requirements and at the same time their relatively good performance in estimating sparse parameter vectors/signals. The paper reports two new algorithms in the context of sparsity--aware learning. In both cases, the goal is first to identify the support set of the unknown signal and then to estimate the non--zero values restricted to the active support set. First, an iterative greedy m","authors_text":"Gerasimos Mileounis, Nicholas Kalouptsidis, Sergios Theodoridis, Symeon Chouvardas","cross_cats":["math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2014-10-14T13:30:39Z","title":"Greedy Sparsity-Promoting Algorithms for Distributed Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1410.3682","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:d1095c33ec9b3bdb9ccb85e36f8b815dbcd4022fd068884d1f962bfa4560e593","target":"record","created_at":"2026-05-18T01:41:48Z","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":"0fedd622087400703681f996d3acdfbcab6090fff457484df30ad41f6eb1f233","cross_cats_sorted":["math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2014-10-14T13:30:39Z","title_canon_sha256":"a892c1a3aa7bc9cf5eb48a1b2b13f2c80e34616408e028f2422febc07c3ea729"},"schema_version":"1.0","source":{"id":"1410.3682","kind":"arxiv","version":1}},"canonical_sha256":"e56995889fa76f15e2154f40e749272fedcddc8c934e4c87d0b5481447d7d961","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e56995889fa76f15e2154f40e749272fedcddc8c934e4c87d0b5481447d7d961","first_computed_at":"2026-05-18T01:41:48.552815Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:41:48.552815Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6B/BFRbYXC3ELKQoEvsNsX5tTjSr/Byj6iKGfyIIc29i5/UK7MHvQE0Eylh/wydfiZFRf4o87qKyGxmK3BMfDg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:41:48.553330Z","signed_message":"canonical_sha256_bytes"},"source_id":"1410.3682","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d1095c33ec9b3bdb9ccb85e36f8b815dbcd4022fd068884d1f962bfa4560e593","sha256:d4c81baa729a7e30bd8fe71319d1b1ee1f000eb96beb71a5d6cceb3508e104b3"],"state_sha256":"c553236c183c09aabaacca817c22ebd4efff7f83171d1a56aa642c4abd014980"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OqIZLbJ9bB8voGQW7f1QUTc+/7hCO3A99Z7Lsh8+H5rJ8JE+6f6diKlU/pVgunoehxNj/Tx4RvpTcjh2tp5eAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-22T07:47:03.384450Z","bundle_sha256":"bf1ef1eb406749929ccbdedf4c775512a11878b28e6ffc9737646050813cdec2"}}