Results 151 to 160 of about 8,860,352 (207)

Enhancing Los Angeles' resilient energy systems amid wildfires. [PDF]

Sci Rep
Zhao AP, Alhazmi M, Li S, Li J, Xie D, Chen S, Hu PJ, Ju X.   +7 more
europepmc   +1 more source

Detecting anthropogenically induced changes in extreme and seasonal evapotranspiration observations. [PDF]

Nat Commun
Egli M, Sippel S, Knutti R, Humphrey V.
europepmc   +1 more source

A bi-objective robust optimization model for location-transportation under uncertainty with psychological costs. [PDF]

PLoS One
Zhang T, Liu Y, Peng Z.
europepmc   +1 more source

Recent trends in machine learning and deep learning-based prediction of G-protein coupled receptor-ligand binding affinities. [PDF]

Front Bioinform
Stephenson J, Karnati KR.
europepmc   +1 more source

LLMCARE: early detection of cognitive impairment via transformer models enhanced by LLM-generated synthetic data. [PDF]

Front Artif Intell
Zolnour A, Azadmaleki H, Haghbin Y, Taherinezhad F, Nezhad MJM, Rashidi S, Khani M, Taleban A, Sani SM, Dadkhah M, Noble JM, Bakken S, Yaghoobzadeh Y, Vahabie AH, Rouhizadeh M, Zolnoori M.   +15 more
europepmc   +1 more source

Outlier Detection in Functional Data Using Adjusted Outlyingness. [PDF]

Entropy (Basel)
Feng Z, Hong X, Li Y, Song X, Zhang K.
europepmc   +1 more source

Baseline Plasma GPX3 Level Predicts Efficacy of Insulin-Sensitization Drug Chiglitazar in Type 2 Diabetes. [PDF]

Phenomics
Cao Z, Chen H, Chen Q, Ding C, Shi L, Zheng Y.   +5 more
europepmc   +1 more source

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Globalized Distributionally Robust Counterpart

SSRN Electronic Journal, 2022
We extend the notion of globalized robustness to consider distributional information beyond the support of the ambiguous probability distribution. We propose the globalized distributionally robust counterpart that disallows any (respectively, allows limited) constraint violation for distributions residing (respectively, not residing) in the ambiguity ...
Feng Liu, Zhi Chen, Shuming Wang
openaire   +3 more sources

Distributionally Robust Optimization [PDF]

Acta Numerica, 2021
The robust optimization methodology that we have introduced so far is built on a fundamental modeling approach, that is based on set-theoretic, deterministic uncertainty models.
Xu Andy Sun, Antonio J. Conejo
openaire   +2 more sources