Zobrazeno 1 - 10
of 2 724
pro vyhledávání: '"P. Delage"'
The entropic risk measure is widely used in high-stakes decision making to account for tail risks associated with an uncertain loss. With limited data, the empirical entropic risk estimator, i.e. replacing the expectation in the entropic risk measure
Externí odkaz:
http://arxiv.org/abs/2409.19926
This paper develops the geometry of rational functions on non-singular real algebraic varieties that are locally bounded. First various basic geometric and algebraic results regarding these functions are established in any dimension, culminating with
Externí odkaz:
http://arxiv.org/abs/2409.04232
Centralized training for decentralized execution paradigm emerged as the state-of-the-art approach to epsilon-optimally solving decentralized partially observable Markov decision processes. However, scalability remains a significant issue. This paper
Externí odkaz:
http://arxiv.org/abs/2408.13139
X-Ray microtomography of mercury intruded compacted clay: An insight into the geometry of macropores
Autor:
Yuan, Shengyang, Liu, Xianfeng, Wang, Yongxin, Delage, Pierre, Aimedieu, Patrick, Buzzi, Olivier
Publikováno v:
Applied Clay Science, 2022, 227, pp.106573
Soil properties, such as wetting collapse behavior and permeability, are strongly correlated to the soil microstructure. To date, several techniques including mercury intrusion porosimetry (MIP), can be used to characterize the microstructure of soil
Externí odkaz:
http://arxiv.org/abs/2407.21083
Autor:
Chenreddy, Abhilash, Delage, Erick
The field of Contextual Optimization (CO) integrates machine learning and optimization to solve decision making problems under uncertainty. Recently, a risk sensitive variant of CO, known as Conditional Robust Optimization (CRO), combines uncertainty
Externí odkaz:
http://arxiv.org/abs/2403.04670
A recent theory shows that a multi-player decentralized partially observable Markov decision process can be transformed into an equivalent single-player game, enabling the application of \citeauthor{bellman}'s principle of optimality to solve the sin
Externí odkaz:
http://arxiv.org/abs/2402.02954
Inverse optimization has been increasingly used to estimate unknown parameters in an optimization model based on decision data. We show that such a point estimation is insufficient in a prescriptive setting where the estimated parameters are used to
Externí odkaz:
http://arxiv.org/abs/2402.01489
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract For individuals with hearing loss, even successful speech communication comes at a cost. Cochlear implants transmit degraded information, specifically for voice pitch, which demands extra and sustained listening effort. The current study hyp
Externí odkaz:
https://doaj.org/article/29ee0417ed68495c891ce59e0438267c
Autor:
Sadana, Utsav, Chenreddy, Abhilash, Delage, Erick, Forel, Alexandre, Frejinger, Emma, Vidal, Thibaut
Recently there has been a surge of interest in operations research (OR) and the machine learning (ML) community in combining prediction algorithms and optimization techniques to solve decision-making problems in the face of uncertainty. This gave ris
Externí odkaz:
http://arxiv.org/abs/2306.10374
The abundance of data has led to the emergence of a variety of optimization techniques that attempt to leverage available side information to provide more anticipative decisions. The wide range of methods and contexts of application have motivated th
Externí odkaz:
http://arxiv.org/abs/2306.05937