Results 131 to 140 of about 32,144 (182)

Parameter estimation from aggregate observations: a Wasserstein distance-based sequential Monte Carlo sampler. [PDF]

R Soc Open Sci, 2023
Cheng C, Wen L, Li J.
europepmc   +1 more source

Entropy–Mean–Upper Partial Deviation–Absolute Deviation Portfolio Problem and Its Wasserstein Distributionally Robust Counterpart

IEEE Access
This paper proposes an Entropy–Mean–Upper partial deviation–Absolute Deviation (EMUAD) portfolio problem, introducing entropy to reduce investment risk and enhance portfolio diversification while simultaneously considering metrics ...
Haonan Wang, Mingyang Fan, Bowen Liu
doaj   +1 more source

Skorohod Representation Theorem Via Disintegrations [PDF]

Let (µn : n >= 0) be Borel probabilities on a metric space S such that µn -> µ0 weakly. Say that Skorohod representation holds if, on some probability space, there are S-valued random variables Xn satisfying Xn - µn for all n and Xn -> X0 in probability.
Luca Pratelli, Patrizia Berti, Pietro Rigo   +2 more
core  

Mean convergence rates for Gaussian-smoothed Wasserstein distances and classical Wasserstein distances

We establish upper bounds for the expected Gaussian-smoothed $p$-Wasserstein distance between a probability measure $μ$ and the corresponding empirical measure $μ_N$, whenever $μ$ has finite $q$-th moments for any $q>p$. This generalizes recent results that were valid only for $q>2p+2d$. We provide two distinct proofs of such a result.
Cosso, Andrea, Martini, Mattia, Perelli, Laura   +2 more
openaire   +2 more sources

The Wasserstein Distance for Ricci Shrinkers

International Mathematics Research Notices
Abstract Let $(M^{n},g,f)$ be a Ricci shrinker such that $\text{Ric}_{f}=\frac{1}{2}g$ and the measure induced by the weighted volume element $(4\pi )^{-\frac{n}{2}}e^{-f}dv_{g}$ is a probability measure. Given a point $p\in M$, we consider two probability measures defined in the tangent space $T_{p}M$, namely the Gaussian measure ...
Conrado, Franciele, Zhou, Detang
openaire   +2 more sources

Optimal Estimation of Wasserstein Distance on A Tree with An Application to Microbiome Studies. [PDF]

J Am Stat Assoc, 2021
Wang S, Cai TT, Li H.
europepmc   +1 more source

Accurate Identification Method of Small-Size Polymetallic Nodules Based on Seafloor Hyperspectral Data

Journal of Marine Science and Engineering
Polymetallic nodules are spherical or ellipsoidal mineral aggregates formed naturally in deep-sea environments. They contain a variety of metallic elements and are important solid mineral resources on the seabed.
Kai Sun, Ziyin Wu, Mingwei Wang, Jihong Shang, Zhihao Liu, Dineng Zhao, Xiaowen Luo   +6 more
doaj   +1 more source

Wasserstein Distances, Neuronal Entanglement, and Sparsity

Disentangling polysemantic neurons is at the core of many current approaches to interpretability of large language models. Here we attempt to study how disentanglement can be used to understand performance, particularly under weight sparsity, a leading post-training optimization technique. We suggest a novel measure for estimating neuronal entanglement:
Sawmya, Shashata, Kong, Linghao, Markov, Ilia, Alistarh, Dan-Adrian, Shavit, Nir   +4 more
openaire   +2 more sources

Quantum distance approximation for persistence diagrams

Journal of Physics: Complexity
Topological data analysis (TDA) methods can be useful for classification and clustering tasks in many different fields as they can provide two dimensional persistence diagrams that summarize important information about the shape of potentially complex ...
Bernardo Ameneyro, Rebekah Herrman, George Siopsis, Vasileios Maroulas   +3 more
doaj   +1 more source

Distributionally Robust Bayesian Optimization via Sinkhorn-Based Wasserstein Barycenter

Machine Learning and Knowledge Extraction
This paper introduces a novel framework for Distributionally Robust Bayesian Optimization (DRBO) with continuous context that integrates optimal transport theory and entropic regularization.
Iman Seyedi, Antonio Candelieri, Francesco Archetti   +2 more
doaj   +1 more source