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As a result, a policymaker who does not have a preference for a specific policy space can let the data identify the best among competing spaces, optimally trading off approximation and estimation error
from the top result below

Producing Policy Recommendations: from Statistical Decision Theory to

https://arxiv.org/html/2607.29281v2
This paper reviews recent theoretical developments on research design for policy choice and provides new tools applied researchers can use to guide their design choices and communicate their policy recommendations

Existence of Richter–Peleg representation for general preferences

https://arxiv.org/html/2508.08980v3
org perpetual non-exclusive license arXiv:2508

Rainfall is rough

https://arxiv.org/html/2607.27099v1
org perpetual non-exclusive license arXiv:2607

You’ve Got to be Efficient: Ambiguity, Misspecification and

https://arxiv.org/html/2604.05327v4
Under mild conditions, the finite-sample likelihoods—which may themselves be misspecified—can be replaced by a limit experiment involving the Gaussian family as the reference likelihood

Preying on Leveraged ETFsPreliminary and incomplete. This project was

https://arxiv.org/html/2608.03703v1
Dispersing the rebalance through the session, Korea’s chosen remedy, moves the order but not the reference that sizes it and can raise the toll

Mathematics

https://arxiv.org/list/math/new
Their finite iterates can develop rapidly increasing numbers of linear pieces, making them a natural test case for the expressive power of deep neural networks

Microstructural Foundations of Rough Noise1footnote

https://arxiv.org/html/2607.29442v2
That is, does there exist a tick-by-tick model, replicating the salient features of ultrahigh-frequency prices, whose scaling limit is of the form Yt=Xt+ZtY_{t}=X_{t}+Z_{t} with ZZ a continuous-time rough process

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https://arxiv.org/pdf/2608.02122
) /Title (DEFT: Joint Task Placement and DVFS for Energy-Efficient Multi-GPU Runtimes) /Trapped /False /arXivID (https://arxiv

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https://arxiv.org/pdf/2407.00125
document was published isbn Text external ISBN for the publication in which the document was published doi Text external Digital Object Identifier for the document url URL external URL at which the document can be found byteCount Integer internal Approximate file size in octets pageCount Integer internal Number of

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https://arxiv.org/pdf/2608.01785
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1 Introduction

https://arxiv.org/html/2511.06451v1
1 Data Protocol (arXiv Release) Synthetic risk–neutral generator

[2006.02833] An Automated Implementation of Hybrid Cloud for Performance

https://arxiv.org/abs/2006.02833
We also explore performance evaluation of cloud bursting for six modern and distributed database systems on the hybrid cloud spanning over local OpenStack and Microsoft Azure

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https://arxiv.org/pdf/2608.00785
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https://arxiv.org/pdf/2608.02854v1
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https://arxiv.org/pdf/2205.01882v5
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https://arxiv.org/pdf/2608.03898
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https://arxiv.org/src/2608.03994
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https://arxiv.org/src/2006.03720
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https://arxiv.org/src/2006.01128
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https://arxiv.org/pdf/2608.02976
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https://arxiv.org/src/2006.00064
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https://arxiv.org/src/2006.02759
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https://arxiv.org/src/2608.03883
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https://arxiv.org/pdf/2006.02602
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https://arxiv.org/src/2006.01048
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https://arxiv.org/src/2006.01331
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https://arxiv.org/pdf/2608.02666
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https://arxiv.org/src/2104.08691
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https://arxiv.org/pdf/2608.03118
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https://arxiv.org/pdf/2006.00342
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