Pith Number

pith:QZ7Z6DF5

pith:2026:QZ7Z6DF52OH6YMKYEGXAZKDXKT

not attested not anchored not stored refs pending

Ensemble Distributionally Robust Bayesian Optimisation with Continuous Context

Denis Derkach, Tigran Ramazyan

A novel algorithm for ensemble distributionally robust Bayesian optimisation stays computationally tractable for continuous contexts and achieves sublinear regret bounds that improve on prior results.

arxiv:2605.07565 v2 · 2026-05-08 · cs.LG · cs.AI · stat.ML

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\usepackage{pith}
\pithnumber{QZ7Z6DF52OH6YMKYEGXAZKDXKT}

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

We propose a novel algorithm for Ensemble Distributionally Robust Bayesian Optimisation that remains computationally tractable while managing continuous context. We obtain theoretical sublinear regret bounds, improving current state-of-the-art results.

C2weakest assumption

The regret analysis and tractability claims rest on unstated assumptions about the ensemble construction, the form of distributional uncertainty, and the surrogate models; these are not detailed in the abstract and could be violated in practice.

C3one line summary

A tractable ensemble distributionally robust Bayesian optimization method achieves improved sublinear regret bounds under context uncertainty.

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-06-24T01:15:03.666735Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

867f9f0cbdd38fec315821ae0ca87754f534744c789fa0f6040b3307e2023b25

Aliases

arxiv: 2605.07565 · arxiv_version: 2605.07565v2 · doi: 10.48550/arxiv.2605.07565 · pith_short_12: QZ7Z6DF52OH6 · pith_short_16: QZ7Z6DF52OH6YMKY · pith_short_8: QZ7Z6DF5

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/QZ7Z6DF52OH6YMKYEGXAZKDXKT \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 867f9f0cbdd38fec315821ae0ca87754f534744c789fa0f6040b3307e2023b25

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "83aa20be39455a3173f79c9c4848e27814ad10009b21de0caa9fd851a12e1c95",
    "cross_cats_sorted": [
      "cs.AI",
      "stat.ML"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-08T10:37:10Z",
    "title_canon_sha256": "55555a59c29a191171681536ddbadc812f8e357c9157a72e6dbfdb16afbd0f52"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.07565",
    "kind": "arxiv",
    "version": 2
  }
}