Pith Number

pith:4DB4CNBW

pith:2016:4DB4CNBWIUOHN6BPZ2TKKDRZNZ

not attested not anchored not stored refs resolved

The CMA Evolution Strategy: A Tutorial

Nikolaus Hansen (TAO)

The CMA-ES derives its search distribution from intuitive requirements for non-linear non-convex optimization in continuous space.

arxiv:1604.00772 v2 · 2016-04-04 · cs.LG · stat.ML

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Claims

C1strongest claim

The CMA-ES is a stochastic method for real-parameter optimization of non-linear, non-convex functions, motivated and derived from intuitive concepts and requirements of non-linear non-convex search in continuous domain.

C2weakest assumption

The reader possesses sufficient background in basic probability, linear algebra, and optimization to follow the intuitive derivation of the covariance adaptation rules.

C3one line summary

The CMA-ES is a stochastic optimizer for continuous non-linear non-convex problems that adapts a multivariate normal search distribution using covariance matrix updates derived from intuitive requirements.

References

37 extracted · 37 resolved · 1 Pith anchors

[1] Quality gain analysis of the weighted recombination evolution strategy on general convex quadratic functions 2017

[2] Diagonal acceleration for covariance matrix adaptation evolution strategies 2020

[3] A restart CMA evolution strategy with increasing population size 2005

[4] Weighted multirecombination evolution strategies 2006

[5] Performance analysis of evolutionary optimization with cumu- lative step length adaptation 2004

Formal links

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Cited by

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Receipt and verification

First computed	2026-05-17T23:38:50.157997Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

e0c3c13436451c76f82fcea6a50e396e65a5347a11d9502be333933e9a8919b9

Aliases

arxiv: 1604.00772 · arxiv_version: 1604.00772v2 · doi: 10.48550/arxiv.1604.00772 · pith_short_12: 4DB4CNBWIUOH · pith_short_16: 4DB4CNBWIUOHN6BP · pith_short_8: 4DB4CNBW

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/4DB4CNBWIUOHN6BPZ2TKKDRZNZ \
  | 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: e0c3c13436451c76f82fcea6a50e396e65a5347a11d9502be333933e9a8919b9

Canonical record JSON

{
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    "abstract_canon_sha256": "8fd74fa2d437d2abc834913f233d5816d118bba2eba6be08ceb71eb2d826c705",
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      "stat.ML"
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    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2016-04-04T08:16:12Z",
    "title_canon_sha256": "42e7bb62c1016578583756e6c386b030a1c99428f346813bf9dae2d385dabd61"
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}