{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:GOWJWQBVWXNDWOUDWX4FQAGEQ7","short_pith_number":"pith:GOWJWQBV","canonical_record":{"source":{"id":"1805.04754","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-05-12T17:58:24Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"5b96cc4b9c5206dac3cbf8cd56481f5fd927ea6f1836d8a24daba2592b27c966","abstract_canon_sha256":"d66de08a55e6643f4b29e0a9e710b59ca81b006fabb7f8f649ae21f516d2886b"},"schema_version":"1.0"},"canonical_sha256":"33ac9b4035b5da3b3a83b5f85800c487dc3ae63f21deafedde6ac4921d073d6d","source":{"kind":"arxiv","id":"1805.04754","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.04754","created_at":"2026-05-18T00:16:04Z"},{"alias_kind":"arxiv_version","alias_value":"1805.04754v1","created_at":"2026-05-18T00:16:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.04754","created_at":"2026-05-18T00:16:04Z"},{"alias_kind":"pith_short_12","alias_value":"GOWJWQBVWXND","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"GOWJWQBVWXNDWOUD","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"GOWJWQBV","created_at":"2026-05-18T12:32:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:GOWJWQBVWXNDWOUDWX4FQAGEQ7","target":"record","payload":{"canonical_record":{"source":{"id":"1805.04754","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-05-12T17:58:24Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"5b96cc4b9c5206dac3cbf8cd56481f5fd927ea6f1836d8a24daba2592b27c966","abstract_canon_sha256":"d66de08a55e6643f4b29e0a9e710b59ca81b006fabb7f8f649ae21f516d2886b"},"schema_version":"1.0"},"canonical_sha256":"33ac9b4035b5da3b3a83b5f85800c487dc3ae63f21deafedde6ac4921d073d6d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:16:04.655468Z","signature_b64":"6VFgEBX+i8knZqAu0BhwBZkZSUTbNY++CvjfCotJRiPqCOf+hEkZNEGPSiM2tlde3P/b94X1crwP79wBH+sHAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"33ac9b4035b5da3b3a83b5f85800c487dc3ae63f21deafedde6ac4921d073d6d","last_reissued_at":"2026-05-18T00:16:04.654934Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:16:04.654934Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1805.04754","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":"2026-05-18T00:16:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QhsvYCRVRQqtuk8pyLRvNru7EoW4jslC+aoun6v3JK5Q4JqmrSi6RwqFlicy4X3fby43wY9Q9h4PF0XDSfzXBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T05:57:06.204441Z"},"content_sha256":"d23d241dd26cb6535cf24741a61c4b69a26c822feb1cd1958f7773607c853806","schema_version":"1.0","event_id":"sha256:d23d241dd26cb6535cf24741a61c4b69a26c822feb1cd1958f7773607c853806"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:GOWJWQBVWXNDWOUDWX4FQAGEQ7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Incremental Learning Framework Using Cloud Computing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Jitin Kapila, Kumarjit Pathak, Nikit Gawande, Prabhukiran G","submitted_at":"2018-05-12T17:58:24Z","abstract_excerpt":"High volume of data, perceived as either challenge or opportunity. Deep learning architecture demands high volume of data to effectively back propagate and train the weights without bias. At the same time, large volume of data demands higher capacity of the machine where it could be executed seamlessly. Budding data scientist along with many research professionals face frequent disconnection issue with cloud computing framework (working without dedicated connection) due to free subscription to the platform. Similar issues also visible while working on local computer where computer may run out "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.04754","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":"2026-05-18T00:16:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0WXn5wN5SjV66aybCNy6c70KaeeLdV2Mq//ejCcXuBF3/LKz/UJGko/C2GdrPWeKJKHPEsfwI8ndQHsZFYM1AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T05:57:06.205040Z"},"content_sha256":"2dd2edf0eb6ef1853553485a3ecfc1d3b23f00252cbb37010a1699216616cefc","schema_version":"1.0","event_id":"sha256:2dd2edf0eb6ef1853553485a3ecfc1d3b23f00252cbb37010a1699216616cefc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GOWJWQBVWXNDWOUDWX4FQAGEQ7/bundle.json","state_url":"https://pith.science/pith/GOWJWQBVWXNDWOUDWX4FQAGEQ7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GOWJWQBVWXNDWOUDWX4FQAGEQ7/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":"2026-06-07T05:57:06Z","links":{"resolver":"https://pith.science/pith/GOWJWQBVWXNDWOUDWX4FQAGEQ7","bundle":"https://pith.science/pith/GOWJWQBVWXNDWOUDWX4FQAGEQ7/bundle.json","state":"https://pith.science/pith/GOWJWQBVWXNDWOUDWX4FQAGEQ7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GOWJWQBVWXNDWOUDWX4FQAGEQ7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:GOWJWQBVWXNDWOUDWX4FQAGEQ7","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":"d66de08a55e6643f4b29e0a9e710b59ca81b006fabb7f8f649ae21f516d2886b","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-05-12T17:58:24Z","title_canon_sha256":"5b96cc4b9c5206dac3cbf8cd56481f5fd927ea6f1836d8a24daba2592b27c966"},"schema_version":"1.0","source":{"id":"1805.04754","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.04754","created_at":"2026-05-18T00:16:04Z"},{"alias_kind":"arxiv_version","alias_value":"1805.04754v1","created_at":"2026-05-18T00:16:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.04754","created_at":"2026-05-18T00:16:04Z"},{"alias_kind":"pith_short_12","alias_value":"GOWJWQBVWXND","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"GOWJWQBVWXNDWOUD","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"GOWJWQBV","created_at":"2026-05-18T12:32:25Z"}],"graph_snapshots":[{"event_id":"sha256:2dd2edf0eb6ef1853553485a3ecfc1d3b23f00252cbb37010a1699216616cefc","target":"graph","created_at":"2026-05-18T00:16:04Z","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":"High volume of data, perceived as either challenge or opportunity. Deep learning architecture demands high volume of data to effectively back propagate and train the weights without bias. At the same time, large volume of data demands higher capacity of the machine where it could be executed seamlessly. Budding data scientist along with many research professionals face frequent disconnection issue with cloud computing framework (working without dedicated connection) due to free subscription to the platform. Similar issues also visible while working on local computer where computer may run out ","authors_text":"Jitin Kapila, Kumarjit Pathak, Nikit Gawande, Prabhukiran G","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-05-12T17:58:24Z","title":"Incremental Learning Framework Using Cloud Computing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.04754","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:d23d241dd26cb6535cf24741a61c4b69a26c822feb1cd1958f7773607c853806","target":"record","created_at":"2026-05-18T00:16:04Z","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":"d66de08a55e6643f4b29e0a9e710b59ca81b006fabb7f8f649ae21f516d2886b","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-05-12T17:58:24Z","title_canon_sha256":"5b96cc4b9c5206dac3cbf8cd56481f5fd927ea6f1836d8a24daba2592b27c966"},"schema_version":"1.0","source":{"id":"1805.04754","kind":"arxiv","version":1}},"canonical_sha256":"33ac9b4035b5da3b3a83b5f85800c487dc3ae63f21deafedde6ac4921d073d6d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"33ac9b4035b5da3b3a83b5f85800c487dc3ae63f21deafedde6ac4921d073d6d","first_computed_at":"2026-05-18T00:16:04.654934Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:16:04.654934Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6VFgEBX+i8knZqAu0BhwBZkZSUTbNY++CvjfCotJRiPqCOf+hEkZNEGPSiM2tlde3P/b94X1crwP79wBH+sHAA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:16:04.655468Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.04754","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d23d241dd26cb6535cf24741a61c4b69a26c822feb1cd1958f7773607c853806","sha256:2dd2edf0eb6ef1853553485a3ecfc1d3b23f00252cbb37010a1699216616cefc"],"state_sha256":"74530cac4f2fa12ca03404f85836a50f093bd95ae86704a69cd14baff957e51c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eduZUfWLKATaNKFP7WwYY3odf7YWJjYvjRoa7SfKbL6FKEqD3isZ7NEccpekyZEwirTmG17RRAZyy7TfTVkCBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T05:57:06.208869Z","bundle_sha256":"93f0f7784f9e7339cafbf8b26bc4edfb7a2a7da563e9216f9c9bf10169ad29f9"}}