Pith Number

pith:ICKN7CD7

pith:2026:ICKN7CD7Y5OW4VN4PI2D27Y3H5

not attested not anchored not stored refs resolved

Double Descent and Emergent Smoothing in Model Averaging Prediction

Dandan Jiang, Ke Chen, Xinyu Zhang

Weighted aggregation in high-dimensional model averaging suppresses the double descent risk peak via emergent smoothing.

arxiv:2605.13203 v1 · 2026-05-13 · stat.ME

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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

weighted aggregation simultaneously triggers an emergent smoothing effect that structurally suppresses the localized risk divergence, indicating that strategic weight choice serves as a vital stabilizing mechanism... LaMA achieves superior predictive accuracy in high-dimensional environments.

C2weakest assumption

The exact limiting risk derivation and LaMA criterion rest on a nested model setting together with random matrix theory assumptions on the design matrix and noise distribution that are not fully specified in the provided abstract.

C3one line summary

Model averaging displays double descent with emergent smoothing from strategic weighting, and the LaMA criterion delivers superior out-of-sample accuracy in high-dimensional regression.

References

24 extracted · 24 resolved · 0 Pith anchors

[1] and K OMAKI , F 2023

[2] and L I, K.-C 2014

[3] and L I, K.-C 2017

[4] and M ANDAL , S 2019

[5] B ELKIN , M., H SU , D. and X U, J. (2020). Two models of double descent for weak features. SIAM Journal on Mathematics of Data Science 2 1167–1180 2020

Receipt and verification

First computed	2026-05-18T03:08:48.641019Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

4094df887fc75d6e55bc7a343d7f1b3f4045a18973644b2c753fd725a23cf568

Aliases

arxiv: 2605.13203 · arxiv_version: 2605.13203v1 · doi: 10.48550/arxiv.2605.13203 · pith_short_12: ICKN7CD7Y5OW · pith_short_16: ICKN7CD7Y5OW4VN4 · pith_short_8: ICKN7CD7

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/ICKN7CD7Y5OW4VN4PI2D27Y3H5 \
  | 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: 4094df887fc75d6e55bc7a343d7f1b3f4045a18973644b2c753fd725a23cf568

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "cbafaf1d43ad9e8a1e8fba8b4aaa8958fc7c46560cb1d8ca1085ee0ea5c0bd7f",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "stat.ME",
    "submitted_at": "2026-05-13T08:55:11Z",
    "title_canon_sha256": "778867faa09dd118ed92b67920fb8cc52500d655dc1286e88d743b981b4eba0d"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13203",
    "kind": "arxiv",
    "version": 1
  }
}