Pith Number

pith:HNMOMKPO

pith:2026:HNMOMKPODOKD4CLJDYFAXV5TQO

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S2MAM: Semi-supervised Meta Additive Model for Robust Estimation and Variable Selection

Bin Gu, Hong Chen, Tieliang Gong, Xuelin Zhang, Yingjie Wang

S2MAM uses bilevel optimization to automatically select informative variables and update similarity matrices in manifold-regularized semi-supervised learning.

arxiv:2604.19072 v3 · 2026-04-21 · cs.LG · cs.AI · stat.ML

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Claims

C1strongest claim

This paper proposes a new Semi-Supervised Meta Additive Model (S2MAM) based on a bilevel optimization scheme that automatically identifies informative variables, updates the similarity matrix, and simultaneously achieves interpretable predictions. Theoretical guarantees are provided for S2MAM, including the computing convergence and the statistical generalization bound.

C2weakest assumption

The assumption that the support of the unknown marginal distribution has the geometric structure of a Riemannian manifold, and that the bilevel optimization can effectively update the similarity matrix without introducing new biases.

C3one line summary

S2MAM is a new semi-supervised model that uses bilevel optimization to automatically identify informative variables, update similarity matrices, and provide interpretable predictions with theoretical guarantees.

Receipt and verification

First computed	2026-05-28T02:04:48.088186Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

3b58e629ee1b943e09691e0a0bd7b3839c42e51dac1a5909a7ca1bc1696697dd

Aliases

arxiv: 2604.19072 · arxiv_version: 2604.19072v3 · doi: 10.48550/arxiv.2604.19072 · pith_short_12: HNMOMKPODOKD · pith_short_16: HNMOMKPODOKD4CLJ · pith_short_8: HNMOMKPO

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/HNMOMKPODOKD4CLJDYFAXV5TQO \
  | 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: 3b58e629ee1b943e09691e0a0bd7b3839c42e51dac1a5909a7ca1bc1696697dd

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "f39ecbbff5bfd1c66349d3ec117dbc79c405328f111c24b529b63f75976506f7",
    "cross_cats_sorted": [
      "cs.AI",
      "stat.ML"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-04-21T04:27:12Z",
    "title_canon_sha256": "aefd48050c6592aa7cd471852669dc29977f5011743fba314bf475290a899c81"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.19072",
    "kind": "arxiv",
    "version": 3
  }
}