{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:S2RPNLXURAZ54X7S3XXHAUMCB7","short_pith_number":"pith:S2RPNLXU","canonical_record":{"source":{"id":"1912.10804","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-12-11T10:00:31Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"dc568067e2dba87b61bdd323ada623fcc4b1835bbd65233490a46e494a2d8c55","abstract_canon_sha256":"56200e6b8177e50005ff2662bf2d3ae1ba879d9f4bbf53a9b2550c5542dbbf1e"},"schema_version":"1.0"},"canonical_sha256":"96a2f6aef48833de5ff2ddee7051820ff6a7106e00b7f02ebed6cb68411d5759","source":{"kind":"arxiv","id":"1912.10804","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.10804","created_at":"2026-07-05T00:28:02Z"},{"alias_kind":"arxiv_version","alias_value":"1912.10804v1","created_at":"2026-07-05T00:28:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.10804","created_at":"2026-07-05T00:28:02Z"},{"alias_kind":"pith_short_12","alias_value":"S2RPNLXURAZ5","created_at":"2026-07-05T00:28:02Z"},{"alias_kind":"pith_short_16","alias_value":"S2RPNLXURAZ54X7S","created_at":"2026-07-05T00:28:02Z"},{"alias_kind":"pith_short_8","alias_value":"S2RPNLXU","created_at":"2026-07-05T00:28:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:S2RPNLXURAZ54X7S3XXHAUMCB7","target":"record","payload":{"canonical_record":{"source":{"id":"1912.10804","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-12-11T10:00:31Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"dc568067e2dba87b61bdd323ada623fcc4b1835bbd65233490a46e494a2d8c55","abstract_canon_sha256":"56200e6b8177e50005ff2662bf2d3ae1ba879d9f4bbf53a9b2550c5542dbbf1e"},"schema_version":"1.0"},"canonical_sha256":"96a2f6aef48833de5ff2ddee7051820ff6a7106e00b7f02ebed6cb68411d5759","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:28:02.805395Z","signature_b64":"8/IfenRF9uyWiSpf3PznukoCu9jn/umEw1s3nS+N5el2E8mNVEybTN4uvxOfw00C7gfV+6Yn6qGSgS4TsHqDBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"96a2f6aef48833de5ff2ddee7051820ff6a7106e00b7f02ebed6cb68411d5759","last_reissued_at":"2026-07-05T00:28:02.804852Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:28:02.804852Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1912.10804","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":"2026-07-05T00:28:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lb09F5jmG2rqmWfJ4dZcdrBrFmLR4/we2Jsq144wLCkcQ1l3OqmHiwbtHZo6kMqOsZ+Mmi+Ue7Asc4skuclrCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T20:52:04.443320Z"},"content_sha256":"6a8d6c4fac7989eaa1a4435e0e8c0f6fae02f29822f65331772f021018e87851","schema_version":"1.0","event_id":"sha256:6a8d6c4fac7989eaa1a4435e0e8c0f6fae02f29822f65331772f021018e87851"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:S2RPNLXURAZ54X7S3XXHAUMCB7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Row-Sparse Discriminative Deep Dictionary Learning for Hyperspectral Image Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"eess.IV","authors_text":"Angshul Majumdar, Vanika Singhal","submitted_at":"2019-12-11T10:00:31Z","abstract_excerpt":"In recent studies in hyperspectral imaging, biometrics and energy analytics, the framework of deep dictionary learning has shown promise. Deep dictionary learning outperforms other traditional deep learning tools when training data is limited; therefore hyperspectral imaging is one such example that benefits from this framework. Most of the prior studies were based on the unsupervised formulation; and in all cases, the training algorithm was greedy and hence sub-optimal. This is the first work that shows how to learn the deep dictionary learning problem in a joint fashion. Moreover, we propose"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.10804","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1912.10804/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":"2026-07-05T00:28:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6cBpxBUAtGveSwHeTqhqV67bXfGiHMvSu2bxVD1trm+fhtIsGrHqhxm7QOCB6LKK6OY5kqEO2MOAoVwtLvOfDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T20:52:04.443813Z"},"content_sha256":"139ed48c337a8dc8c868943bb546db8bad54e9982d77867e118dff07f1c53221","schema_version":"1.0","event_id":"sha256:139ed48c337a8dc8c868943bb546db8bad54e9982d77867e118dff07f1c53221"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/S2RPNLXURAZ54X7S3XXHAUMCB7/bundle.json","state_url":"https://pith.science/pith/S2RPNLXURAZ54X7S3XXHAUMCB7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/S2RPNLXURAZ54X7S3XXHAUMCB7/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":"2026-08-03T20:52:04Z","links":{"resolver":"https://pith.science/pith/S2RPNLXURAZ54X7S3XXHAUMCB7","bundle":"https://pith.science/pith/S2RPNLXURAZ54X7S3XXHAUMCB7/bundle.json","state":"https://pith.science/pith/S2RPNLXURAZ54X7S3XXHAUMCB7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/S2RPNLXURAZ54X7S3XXHAUMCB7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:S2RPNLXURAZ54X7S3XXHAUMCB7","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":"56200e6b8177e50005ff2662bf2d3ae1ba879d9f4bbf53a9b2550c5542dbbf1e","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-12-11T10:00:31Z","title_canon_sha256":"dc568067e2dba87b61bdd323ada623fcc4b1835bbd65233490a46e494a2d8c55"},"schema_version":"1.0","source":{"id":"1912.10804","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.10804","created_at":"2026-07-05T00:28:02Z"},{"alias_kind":"arxiv_version","alias_value":"1912.10804v1","created_at":"2026-07-05T00:28:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.10804","created_at":"2026-07-05T00:28:02Z"},{"alias_kind":"pith_short_12","alias_value":"S2RPNLXURAZ5","created_at":"2026-07-05T00:28:02Z"},{"alias_kind":"pith_short_16","alias_value":"S2RPNLXURAZ54X7S","created_at":"2026-07-05T00:28:02Z"},{"alias_kind":"pith_short_8","alias_value":"S2RPNLXU","created_at":"2026-07-05T00:28:02Z"}],"graph_snapshots":[{"event_id":"sha256:139ed48c337a8dc8c868943bb546db8bad54e9982d77867e118dff07f1c53221","target":"graph","created_at":"2026-07-05T00:28:02Z","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/1912.10804/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recent studies in hyperspectral imaging, biometrics and energy analytics, the framework of deep dictionary learning has shown promise. Deep dictionary learning outperforms other traditional deep learning tools when training data is limited; therefore hyperspectral imaging is one such example that benefits from this framework. Most of the prior studies were based on the unsupervised formulation; and in all cases, the training algorithm was greedy and hence sub-optimal. This is the first work that shows how to learn the deep dictionary learning problem in a joint fashion. Moreover, we propose","authors_text":"Angshul Majumdar, Vanika Singhal","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-12-11T10:00:31Z","title":"Row-Sparse Discriminative Deep Dictionary Learning for Hyperspectral Image Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.10804","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":"sha256:6a8d6c4fac7989eaa1a4435e0e8c0f6fae02f29822f65331772f021018e87851","target":"record","created_at":"2026-07-05T00:28:02Z","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":"56200e6b8177e50005ff2662bf2d3ae1ba879d9f4bbf53a9b2550c5542dbbf1e","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-12-11T10:00:31Z","title_canon_sha256":"dc568067e2dba87b61bdd323ada623fcc4b1835bbd65233490a46e494a2d8c55"},"schema_version":"1.0","source":{"id":"1912.10804","kind":"arxiv","version":1}},"canonical_sha256":"96a2f6aef48833de5ff2ddee7051820ff6a7106e00b7f02ebed6cb68411d5759","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"96a2f6aef48833de5ff2ddee7051820ff6a7106e00b7f02ebed6cb68411d5759","first_computed_at":"2026-07-05T00:28:02.804852Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:28:02.804852Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8/IfenRF9uyWiSpf3PznukoCu9jn/umEw1s3nS+N5el2E8mNVEybTN4uvxOfw00C7gfV+6Yn6qGSgS4TsHqDBg==","signature_status":"signed_v1","signed_at":"2026-07-05T00:28:02.805395Z","signed_message":"canonical_sha256_bytes"},"source_id":"1912.10804","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6a8d6c4fac7989eaa1a4435e0e8c0f6fae02f29822f65331772f021018e87851","sha256:139ed48c337a8dc8c868943bb546db8bad54e9982d77867e118dff07f1c53221"],"state_sha256":"c83b5bbe089b3fb3c29cd288697f3bea7a155a7ce5298b940481a071abefdcf8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"luUyeuFll/Fqj1YwpJ/yie8Xr8wE9J05kAQelRGi/rEyP7j/C7GMn1bXP65CnsrCxPo3OssC8OFkolQ/sN+8DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T20:52:04.447418Z","bundle_sha256":"1ab21320aa332f7266d8fb7d1949d00bed9e75d4ab6677cf66041589263a420f"}}