{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:5WFTR5M3RR6NRBAWUAE4Z6YG4O","short_pith_number":"pith:5WFTR5M3","schema_version":"1.0","canonical_sha256":"ed8b38f59b8c7cd88416a009ccfb06e3a91e9c99742f20e3f415f40f90efc1c3","source":{"kind":"arxiv","id":"1810.02722","version":2},"attestation_state":"computed","paper":{"title":"Balanced Allocation with Random Walk Based Sampling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DM","cs.DS"],"primary_cat":"math.PR","authors_text":"Dengwang Tang, Vijay G. Subramanian","submitted_at":"2018-10-05T14:39:45Z","abstract_excerpt":"In the standard ball-in-bins experiment, a well-known scheme is to sample $d$ bins independently and uniformly at random and put the ball into the least loaded bin. It can be shown that this scheme yields a maximum load of $\\log\\log n/\\log d+O(1)$ with high probability.\n  Subsequent work analyzed the model when at each time, $d$ bins are sampled through some correlated or non-uniform way. However, the case when the sampling for different balls are correlated are rarely investigated. In this paper we propose three schemes for the ball-in-bins allocation problem. We assume that there is an under"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1810.02722","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.PR","submitted_at":"2018-10-05T14:39:45Z","cross_cats_sorted":["cs.DM","cs.DS"],"title_canon_sha256":"f1b1ffef35d922a4aa1f2ee8562f895b0db8443f23925587afbbaa043d202fe2","abstract_canon_sha256":"11b7c9d429b873830e2e0fdc704b95a6faf98fa889bea3e4c2c7f4dfd5560997"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:03:36.411893Z","signature_b64":"bTsY82UDjnnKcoRO7tdP0iHnBFjK5rkH985ZVnORf12d0gRvP0C1RE0iuUaTkgrHd6iUnHl81c3y+Fsau5qKAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ed8b38f59b8c7cd88416a009ccfb06e3a91e9c99742f20e3f415f40f90efc1c3","last_reissued_at":"2026-05-18T00:03:36.411273Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:03:36.411273Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Balanced Allocation with Random Walk Based Sampling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DM","cs.DS"],"primary_cat":"math.PR","authors_text":"Dengwang Tang, Vijay G. Subramanian","submitted_at":"2018-10-05T14:39:45Z","abstract_excerpt":"In the standard ball-in-bins experiment, a well-known scheme is to sample $d$ bins independently and uniformly at random and put the ball into the least loaded bin. It can be shown that this scheme yields a maximum load of $\\log\\log n/\\log d+O(1)$ with high probability.\n  Subsequent work analyzed the model when at each time, $d$ bins are sampled through some correlated or non-uniform way. However, the case when the sampling for different balls are correlated are rarely investigated. In this paper we propose three schemes for the ball-in-bins allocation problem. We assume that there is an under"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.02722","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":""},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1810.02722","created_at":"2026-05-18T00:03:36.411373+00:00"},{"alias_kind":"arxiv_version","alias_value":"1810.02722v2","created_at":"2026-05-18T00:03:36.411373+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.02722","created_at":"2026-05-18T00:03:36.411373+00:00"},{"alias_kind":"pith_short_12","alias_value":"5WFTR5M3RR6N","created_at":"2026-05-18T12:32:08.215937+00:00"},{"alias_kind":"pith_short_16","alias_value":"5WFTR5M3RR6NRBAW","created_at":"2026-05-18T12:32:08.215937+00:00"},{"alias_kind":"pith_short_8","alias_value":"5WFTR5M3","created_at":"2026-05-18T12:32:08.215937+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/5WFTR5M3RR6NRBAWUAE4Z6YG4O","json":"https://pith.science/pith/5WFTR5M3RR6NRBAWUAE4Z6YG4O.json","graph_json":"https://pith.science/api/pith-number/5WFTR5M3RR6NRBAWUAE4Z6YG4O/graph.json","events_json":"https://pith.science/api/pith-number/5WFTR5M3RR6NRBAWUAE4Z6YG4O/events.json","paper":"https://pith.science/paper/5WFTR5M3"},"agent_actions":{"view_html":"https://pith.science/pith/5WFTR5M3RR6NRBAWUAE4Z6YG4O","download_json":"https://pith.science/pith/5WFTR5M3RR6NRBAWUAE4Z6YG4O.json","view_paper":"https://pith.science/paper/5WFTR5M3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1810.02722&json=true","fetch_graph":"https://pith.science/api/pith-number/5WFTR5M3RR6NRBAWUAE4Z6YG4O/graph.json","fetch_events":"https://pith.science/api/pith-number/5WFTR5M3RR6NRBAWUAE4Z6YG4O/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5WFTR5M3RR6NRBAWUAE4Z6YG4O/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5WFTR5M3RR6NRBAWUAE4Z6YG4O/action/storage_attestation","attest_author":"https://pith.science/pith/5WFTR5M3RR6NRBAWUAE4Z6YG4O/action/author_attestation","sign_citation":"https://pith.science/pith/5WFTR5M3RR6NRBAWUAE4Z6YG4O/action/citation_signature","submit_replication":"https://pith.science/pith/5WFTR5M3RR6NRBAWUAE4Z6YG4O/action/replication_record"}},"created_at":"2026-05-18T00:03:36.411373+00:00","updated_at":"2026-05-18T00:03:36.411373+00:00"}