{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:JX7OYSXCVLDTLPGMLPZS6W4PQL","short_pith_number":"pith:JX7OYSXC","canonical_record":{"source":{"id":"1906.08654","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-20T14:17:33Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"14136c96ed0a49a3f9ac96ad30e8448ee4056b0d66ec28ac7f1c3367fd615193","abstract_canon_sha256":"9ff9cc4db45d60868c9d09b60bafa9c662f699aaac13c918b40379eb9e2433ae"},"schema_version":"1.0"},"canonical_sha256":"4dfeec4ae2aac735bccc5bf32f5b8f82fdcdc9d94fb3499365a175f35ec93bf7","source":{"kind":"arxiv","id":"1906.08654","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.08654","created_at":"2026-05-17T23:42:49Z"},{"alias_kind":"arxiv_version","alias_value":"1906.08654v1","created_at":"2026-05-17T23:42:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.08654","created_at":"2026-05-17T23:42:49Z"},{"alias_kind":"pith_short_12","alias_value":"JX7OYSXCVLDT","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"JX7OYSXCVLDTLPGM","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"JX7OYSXC","created_at":"2026-05-18T12:33:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:JX7OYSXCVLDTLPGMLPZS6W4PQL","target":"record","payload":{"canonical_record":{"source":{"id":"1906.08654","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-20T14:17:33Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"14136c96ed0a49a3f9ac96ad30e8448ee4056b0d66ec28ac7f1c3367fd615193","abstract_canon_sha256":"9ff9cc4db45d60868c9d09b60bafa9c662f699aaac13c918b40379eb9e2433ae"},"schema_version":"1.0"},"canonical_sha256":"4dfeec4ae2aac735bccc5bf32f5b8f82fdcdc9d94fb3499365a175f35ec93bf7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:42:49.966638Z","signature_b64":"YIaTtmNftD/puwdgyJ4TuJkuIzRbagGlScV4pjnvt/KjNnlCAQZDZ4lO9DvGzEMrP76GyTDDZKgl83VBp7tfAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4dfeec4ae2aac735bccc5bf32f5b8f82fdcdc9d94fb3499365a175f35ec93bf7","last_reissued_at":"2026-05-17T23:42:49.966221Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:42:49.966221Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.08654","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":"2026-05-17T23:42:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gxaVNGhL/508ze/+oZGDimMb5zq4zRmWzWLJZ19nkNajHg/E7OJ86Qy5d+LWT6ynpA/mM+etff5CKJKIUgs4DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T15:24:16.713699Z"},"content_sha256":"129c2b50eff191fe9a472ed4e3ce657a311bdfe9adea254b0f535e490e210276","schema_version":"1.0","event_id":"sha256:129c2b50eff191fe9a472ed4e3ce657a311bdfe9adea254b0f535e490e210276"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:JX7OYSXCVLDTLPGMLPZS6W4PQL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ID3 Learns Juntas for Smoothed Product Distributions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Alon Brutzkus, Amit Daniely, Eran Malach","submitted_at":"2019-06-20T14:17:33Z","abstract_excerpt":"In recent years, there are many attempts to understand popular heuristics. An example of such a heuristic algorithm is the ID3 algorithm for learning decision trees. This algorithm is commonly used in practice, but there are very few theoretical works studying its behavior. In this paper, we analyze the ID3 algorithm, when the target function is a $k$-Junta, a function that depends on $k$ out of $n$ variables of the input. We prove that when $k = \\log n$, the ID3 algorithm learns in polynomial time $k$-Juntas, in the smoothed analysis model of Kalai & Teng. That is, we show a learnability resu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.08654","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":"2026-05-17T23:42:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3idxt5OJtvRaao30FTW3QqY6MSlqXDoS8o4lQM0xFXYlERlx1K2ArcXmAZEI4sFQcSs2cRQFup0pnqw5ln6ABg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T15:24:16.714184Z"},"content_sha256":"97e174cd5a0efeb3f92e3f83ddd411cd52f14eeed689dd960755bbb4f11c4ae9","schema_version":"1.0","event_id":"sha256:97e174cd5a0efeb3f92e3f83ddd411cd52f14eeed689dd960755bbb4f11c4ae9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JX7OYSXCVLDTLPGMLPZS6W4PQL/bundle.json","state_url":"https://pith.science/pith/JX7OYSXCVLDTLPGMLPZS6W4PQL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JX7OYSXCVLDTLPGMLPZS6W4PQL/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":"2026-05-25T15:24:16Z","links":{"resolver":"https://pith.science/pith/JX7OYSXCVLDTLPGMLPZS6W4PQL","bundle":"https://pith.science/pith/JX7OYSXCVLDTLPGMLPZS6W4PQL/bundle.json","state":"https://pith.science/pith/JX7OYSXCVLDTLPGMLPZS6W4PQL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JX7OYSXCVLDTLPGMLPZS6W4PQL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:JX7OYSXCVLDTLPGMLPZS6W4PQL","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":"9ff9cc4db45d60868c9d09b60bafa9c662f699aaac13c918b40379eb9e2433ae","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-20T14:17:33Z","title_canon_sha256":"14136c96ed0a49a3f9ac96ad30e8448ee4056b0d66ec28ac7f1c3367fd615193"},"schema_version":"1.0","source":{"id":"1906.08654","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.08654","created_at":"2026-05-17T23:42:49Z"},{"alias_kind":"arxiv_version","alias_value":"1906.08654v1","created_at":"2026-05-17T23:42:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.08654","created_at":"2026-05-17T23:42:49Z"},{"alias_kind":"pith_short_12","alias_value":"JX7OYSXCVLDT","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"JX7OYSXCVLDTLPGM","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"JX7OYSXC","created_at":"2026-05-18T12:33:21Z"}],"graph_snapshots":[{"event_id":"sha256:97e174cd5a0efeb3f92e3f83ddd411cd52f14eeed689dd960755bbb4f11c4ae9","target":"graph","created_at":"2026-05-17T23:42:49Z","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":"In recent years, there are many attempts to understand popular heuristics. An example of such a heuristic algorithm is the ID3 algorithm for learning decision trees. This algorithm is commonly used in practice, but there are very few theoretical works studying its behavior. In this paper, we analyze the ID3 algorithm, when the target function is a $k$-Junta, a function that depends on $k$ out of $n$ variables of the input. We prove that when $k = \\log n$, the ID3 algorithm learns in polynomial time $k$-Juntas, in the smoothed analysis model of Kalai & Teng. That is, we show a learnability resu","authors_text":"Alon Brutzkus, Amit Daniely, Eran Malach","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-20T14:17:33Z","title":"ID3 Learns Juntas for Smoothed Product Distributions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.08654","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":"sha256:129c2b50eff191fe9a472ed4e3ce657a311bdfe9adea254b0f535e490e210276","target":"record","created_at":"2026-05-17T23:42:49Z","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":"9ff9cc4db45d60868c9d09b60bafa9c662f699aaac13c918b40379eb9e2433ae","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-06-20T14:17:33Z","title_canon_sha256":"14136c96ed0a49a3f9ac96ad30e8448ee4056b0d66ec28ac7f1c3367fd615193"},"schema_version":"1.0","source":{"id":"1906.08654","kind":"arxiv","version":1}},"canonical_sha256":"4dfeec4ae2aac735bccc5bf32f5b8f82fdcdc9d94fb3499365a175f35ec93bf7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4dfeec4ae2aac735bccc5bf32f5b8f82fdcdc9d94fb3499365a175f35ec93bf7","first_computed_at":"2026-05-17T23:42:49.966221Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:42:49.966221Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YIaTtmNftD/puwdgyJ4TuJkuIzRbagGlScV4pjnvt/KjNnlCAQZDZ4lO9DvGzEMrP76GyTDDZKgl83VBp7tfAA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:42:49.966638Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.08654","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:129c2b50eff191fe9a472ed4e3ce657a311bdfe9adea254b0f535e490e210276","sha256:97e174cd5a0efeb3f92e3f83ddd411cd52f14eeed689dd960755bbb4f11c4ae9"],"state_sha256":"edba33ac023cd6df1a87f61283476f777449df872dd9d3f01f46b8bc7c9f21e4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q14ZMGcROPlJbjF6+2y4uultK8RCCm1g2gWSXsdzS1o3nRDo8+Xyo5FZ0zzTtehBHwXvBTJ+3Jxq8gvO2C1fDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T15:24:16.717253Z","bundle_sha256":"8789a1f448dd812635af068c2d3896d9593910ea3623362d2662dc08aa737b20"}}