{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:7YKHURMKHWP5G33YETJXJPDV4X","short_pith_number":"pith:7YKHURMK","canonical_record":{"source":{"id":"2408.02936","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-06T03:42:38Z","cross_cats_sorted":[],"title_canon_sha256":"12c0d31a6ce201812bee7833c3ac5bb558e5ca0e1bc18652601accdf3fe31ee6","abstract_canon_sha256":"58470dcce248f073b6ef9e57b139d512566614ef547c87897daf979e81478e74"},"schema_version":"1.0"},"canonical_sha256":"fe147a458a3d9fd36f7824d374bc75e5fc47a2472eedc2af76a65c9015d663d3","source":{"kind":"arxiv","id":"2408.02936","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.02936","created_at":"2026-07-05T08:54:16Z"},{"alias_kind":"arxiv_version","alias_value":"2408.02936v2","created_at":"2026-07-05T08:54:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.02936","created_at":"2026-07-05T08:54:16Z"},{"alias_kind":"pith_short_12","alias_value":"7YKHURMKHWP5","created_at":"2026-07-05T08:54:16Z"},{"alias_kind":"pith_short_16","alias_value":"7YKHURMKHWP5G33Y","created_at":"2026-07-05T08:54:16Z"},{"alias_kind":"pith_short_8","alias_value":"7YKHURMK","created_at":"2026-07-05T08:54:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:7YKHURMKHWP5G33YETJXJPDV4X","target":"record","payload":{"canonical_record":{"source":{"id":"2408.02936","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-06T03:42:38Z","cross_cats_sorted":[],"title_canon_sha256":"12c0d31a6ce201812bee7833c3ac5bb558e5ca0e1bc18652601accdf3fe31ee6","abstract_canon_sha256":"58470dcce248f073b6ef9e57b139d512566614ef547c87897daf979e81478e74"},"schema_version":"1.0"},"canonical_sha256":"fe147a458a3d9fd36f7824d374bc75e5fc47a2472eedc2af76a65c9015d663d3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:54:16.780182Z","signature_b64":"SeHDzDMmUo14CtbmeWR8BXd/uCOqfPw61ywBXaCmekqu5rv52rG6LU1NOwyvGuzFLcwGyYf14K7DoObeYuIHCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fe147a458a3d9fd36f7824d374bc75e5fc47a2472eedc2af76a65c9015d663d3","last_reissued_at":"2026-07-05T08:54:16.779793Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:54:16.779793Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.02936","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":"2026-07-05T08:54:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"B+CTCsUFm2RysmI5V08asdVRknq+RXxf1EFeooyNxnuGt30rzJNHUcYShx4Xd9QcXbqYow6EVwnxBEw9EGBlAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T19:03:01.731400Z"},"content_sha256":"f73855f8b2f5c4c8d33d8624f6dde972db2c69b4a5b1eee364e5263b0f3d4466","schema_version":"1.0","event_id":"sha256:f73855f8b2f5c4c8d33d8624f6dde972db2c69b4a5b1eee364e5263b0f3d4466"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:7YKHURMKHWP5G33YETJXJPDV4X","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Achieving More with Less: A Tensor-Optimization-Powered Ensemble Method","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Fangyuan Xie, Feiping Nie, Jinghui Yuan, Rong Wang, Weijin Jiang, Yuan Yuan, Zhe Cao","submitted_at":"2024-08-06T03:42:38Z","abstract_excerpt":"Ensemble learning is a method that leverages weak learners to produce a strong learner. However, obtaining a large number of base learners requires substantial time and computational resources. Therefore, it is meaningful to study how to achieve the performance typically obtained with many base learners using only a few. We argue that to achieve this, it is essential to enhance both classification performance and generalization ability during the ensemble process. To increase model accuracy, each weak base learner needs to be more efficiently integrated. It is observed that different base lear"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.02936","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/2408.02936/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":"2026-07-05T08:54:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lc9OfR1y5/j5hOAvKjgBRe9T6BGzmEATFrTagn0bdioTrPjPsJO275zJM0Z7dK5yN3gMGWHO59uk/NNHYEWkCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T19:03:01.732364Z"},"content_sha256":"3318564c20df14772c0fb9347084c30fcc4f4725d4b62011436dc39722f7669f","schema_version":"1.0","event_id":"sha256:3318564c20df14772c0fb9347084c30fcc4f4725d4b62011436dc39722f7669f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7YKHURMKHWP5G33YETJXJPDV4X/bundle.json","state_url":"https://pith.science/pith/7YKHURMKHWP5G33YETJXJPDV4X/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7YKHURMKHWP5G33YETJXJPDV4X/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":"2026-08-19T19:03:01Z","links":{"resolver":"https://pith.science/pith/7YKHURMKHWP5G33YETJXJPDV4X","bundle":"https://pith.science/pith/7YKHURMKHWP5G33YETJXJPDV4X/bundle.json","state":"https://pith.science/pith/7YKHURMKHWP5G33YETJXJPDV4X/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7YKHURMKHWP5G33YETJXJPDV4X/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:7YKHURMKHWP5G33YETJXJPDV4X","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":"58470dcce248f073b6ef9e57b139d512566614ef547c87897daf979e81478e74","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-06T03:42:38Z","title_canon_sha256":"12c0d31a6ce201812bee7833c3ac5bb558e5ca0e1bc18652601accdf3fe31ee6"},"schema_version":"1.0","source":{"id":"2408.02936","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.02936","created_at":"2026-07-05T08:54:16Z"},{"alias_kind":"arxiv_version","alias_value":"2408.02936v2","created_at":"2026-07-05T08:54:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.02936","created_at":"2026-07-05T08:54:16Z"},{"alias_kind":"pith_short_12","alias_value":"7YKHURMKHWP5","created_at":"2026-07-05T08:54:16Z"},{"alias_kind":"pith_short_16","alias_value":"7YKHURMKHWP5G33Y","created_at":"2026-07-05T08:54:16Z"},{"alias_kind":"pith_short_8","alias_value":"7YKHURMK","created_at":"2026-07-05T08:54:16Z"}],"graph_snapshots":[{"event_id":"sha256:3318564c20df14772c0fb9347084c30fcc4f4725d4b62011436dc39722f7669f","target":"graph","created_at":"2026-07-05T08:54:16Z","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/2408.02936/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Ensemble learning is a method that leverages weak learners to produce a strong learner. However, obtaining a large number of base learners requires substantial time and computational resources. Therefore, it is meaningful to study how to achieve the performance typically obtained with many base learners using only a few. We argue that to achieve this, it is essential to enhance both classification performance and generalization ability during the ensemble process. To increase model accuracy, each weak base learner needs to be more efficiently integrated. It is observed that different base lear","authors_text":"Fangyuan Xie, Feiping Nie, Jinghui Yuan, Rong Wang, Weijin Jiang, Yuan Yuan, Zhe Cao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-06T03:42:38Z","title":"Achieving More with Less: A Tensor-Optimization-Powered Ensemble Method"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.02936","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:f73855f8b2f5c4c8d33d8624f6dde972db2c69b4a5b1eee364e5263b0f3d4466","target":"record","created_at":"2026-07-05T08:54:16Z","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":"58470dcce248f073b6ef9e57b139d512566614ef547c87897daf979e81478e74","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-06T03:42:38Z","title_canon_sha256":"12c0d31a6ce201812bee7833c3ac5bb558e5ca0e1bc18652601accdf3fe31ee6"},"schema_version":"1.0","source":{"id":"2408.02936","kind":"arxiv","version":2}},"canonical_sha256":"fe147a458a3d9fd36f7824d374bc75e5fc47a2472eedc2af76a65c9015d663d3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fe147a458a3d9fd36f7824d374bc75e5fc47a2472eedc2af76a65c9015d663d3","first_computed_at":"2026-07-05T08:54:16.779793Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:54:16.779793Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SeHDzDMmUo14CtbmeWR8BXd/uCOqfPw61ywBXaCmekqu5rv52rG6LU1NOwyvGuzFLcwGyYf14K7DoObeYuIHCA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:54:16.780182Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.02936","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f73855f8b2f5c4c8d33d8624f6dde972db2c69b4a5b1eee364e5263b0f3d4466","sha256:3318564c20df14772c0fb9347084c30fcc4f4725d4b62011436dc39722f7669f"],"state_sha256":"d4fcb563e59e2eb8c1cbd6cd80589363587dc6264556d0c51a3cd6c4e3d7eeae"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KU0ORaZX5pu9pft0W+BIcmRRcIOjl01W4vDEcwc/0MbhFz6tJnCigeHyBhb4eQaaF4GFerPqokrJPP9XiioNCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T19:03:01.890038Z","bundle_sha256":"4e1f2d28b4eb418c3a9168a8a0259055f7b3c0534880fa352aea54ad2e9d71a8"}}