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Identifying and mitigating vulnerabilities in llm-integrated applications
F Jiang - 2024 - search.proquest.com
Large language models (LLMs) are increasingly deployed as the backend for various
applications, including code completion tools and AI-powered search engines. Unlike …
applications, including code completion tools and AI-powered search engines. Unlike …
Supervised training of conditional monge maps
Optimal transport (OT) theory describes general principles to define and select, among many
possible choices, the most efficient way to map a probability measure onto another. That …
possible choices, the most efficient way to map a probability measure onto another. That …
Faster Wasserstein distance estimation with the Sinkhorn divergence
The squared Wasserstein distance is a natural quantity to compare probability distributions
in a non-parametric setting. This quantity is usually estimated with the plug-in estimator …
in a non-parametric setting. This quantity is usually estimated with the plug-in estimator …
Entropic estimation of optimal transport maps
AA Pooladian, J Niles-Weed - ar** via input convex neural networks
In this paper, we present a novel and principled approach to learn the optimal transport
between two distributions, from samples. Guided by the optimal transport theory, we learn …
between two distributions, from samples. Guided by the optimal transport theory, we learn …
Plugin estimation of smooth optimal transport maps
Plugin estimation of smooth optimal transport maps Page 1 The Annals of Statistics 2024, Vol.
52, No. 3, 966–998 https://doi.org/10.1214/24-AOS2379 © Institute of Mathematical Statistics …
52, No. 3, 966–998 https://doi.org/10.1214/24-AOS2379 © Institute of Mathematical Statistics …
Rates of estimation of optimal transport maps using plug-in estimators via barycentric projections
Optimal transport maps between two probability distributions $\mu $ and $\nu $ on $\R^ d $
have found extensive applications in both machine learning and statistics. In practice, these …
have found extensive applications in both machine learning and statistics. In practice, these …
[PDF][PDF] Statistical optimal transport
Statistical Optimal Transport arxiv:2407.18163v2 [math.ST] 7 Nov 2024 Page 1 Statistical
Optimal Transport Sinho Chewi Yale Jonathan Niles-Weed NYU Philippe Rigollet MIT …
Optimal Transport Sinho Chewi Yale Jonathan Niles-Weed NYU Philippe Rigollet MIT …
Projection‐based techniques for high‐dimensional optimal transport problems
Optimal transport (OT) methods seek a transformation map (or plan) between two probability
measures, such that the transformation has the minimum transportation cost. Such a …
measures, such that the transformation has the minimum transportation cost. Such a …
Minimax estimation of discontinuous optimal transport maps: The semi-discrete case
We consider the problem of estimating the optimal transport map between two probability
distributions, $ P $ and $ Q $ in $\mathbb {R}^ d $, on the basis of iid samples. All existing …
distributions, $ P $ and $ Q $ in $\mathbb {R}^ d $, on the basis of iid samples. All existing …