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检索条件"主题词=Expectation Maximization Algorithm"
643 条 记 录,以下是351-360 订阅
排序:
PixOOD: Pixel-Level Out-of-Distribution Detection
arXiv
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arXiv 2024年
作者: Vojíř, Tomáš Šochman, Jan Matas, Jiří Czech Technical University in Prague Faculty of Electrical Engineering Department of Cybernetics Visual Recognition Group Czech Republic
We propose a pixel-level out-of-distribution detection algorithm, called PixOOD, which does not require training on samples of anomalous data and is not designed for a specific application which avoids traditional tra... 详细信息
来源: 评论
A general statistical approach to quantum algorithms in a circuit model based on the expectation and standard deviation of each gate separately
arXiv
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arXiv 2024年
作者: Shushi, Tomer Center for Quantum Science and Technology Department of Business Administration Guilford Glazer Faculty of Business and Management Ben-Gurion University of the Negev Beer-Sheva Israel
Recently, there has been a growing literature exploring the generalization of quantum algorithms, such that different quantum algorithms are special examples of a more fundamental structure. In this short paper, we pr... 详细信息
来源: 评论
Mixed Noise and Posterior Estimation with Conditional DeepGEM
arXiv
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arXiv 2024年
作者: Hagemann, Paul Hertrich, Johannes Casfor, Maren Heidenreich, Sebastian Steidl, Gabriele Institute of Mathematics TU Berlin Straße des 17. Juni 136 BerlinD-10623 Germany University College London United Kingdom Physikalisch Technische Bundesanstalt Germany
We develop an algorithm for jointly estimating the posterior and the noise parameters in Bayesian inverse problems, which is motivated by indirect measurements and applications from nanometrology with a mixed noise mo... 详细信息
来源: 评论
Causal Bayesian Optimization via Exogenous Distribution Learning
arXiv
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arXiv 2024年
作者: Ren, Shaogang Qian, Xiaoning Department of Computer Science and Engineering University of Tennessee at Chattanooga United States Department of Electrical and Computer Engineering Texas A&M University United States
Maximizing a target variable as an operational objective in a structural causal model is an important problem. Causal Bayesian Optimization (CBO) methods either rely on interventions that alter the causal structure to... 详细信息
来源: 评论
THE PERTURBED PROX-PRECONDITIONED SPIDER algorithm FOR EM-BASED LARGE SCALE LEARNING  21
THE PERTURBED PROX-PRECONDITIONED SPIDER ALGORITHM FOR EM-BA...
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IEEE Statistical Signal Processing Workshop (SSP)
作者: Fort, G. Moulines, E. Univ Toulouse IMT F-31062 Toulouse France CNRS F-31062 Toulouse France Ecole Polytech CMAP Route Saclay F-91128 Palaiseau France
Incremental expectation maximization (EM) algorithms were introduced to design EM for the large scale learning framework by avoiding the full data set to be processed at each iteration. Nevertheless, these algorithms ... 详细信息
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A common random effect induced bivariate gamma degradation process with application to remaining useful life prediction
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RELIABILITY ENGINEERING & SYSTEM SAFETY 2022年 第0期219卷 108200-108200页
作者: Song, Kai Cui, Lirong Beijing Inst Technol Sch Management & Econ Beijing Peoples R China Qingdao Univ Coll Qual & Standardizat Qingdao Peoples R China
Due to the complex structures and the multi-functionality of modern products, there are usually two or more performance characteristics which can reflect a product's degradation states. The degradation processes c... 详细信息
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Multi-objective Reinforcement Learning with Nonlinear Preferences: Provable Approximation for Maximizing Expected Scalarized Return
arXiv
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arXiv 2023年
作者: Peng, Nianli Tian, Muhang Fain, Brandon Harvard University CambridgeMA United States Duke University DurhamNC United States
We study multi-objective reinforcement learning with nonlinear preferences over trajectories. That is, we maximize the expected value of a nonlinear function over accumulated rewards (expected scalarized return or ESR... 详细信息
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High-dimensional variable clustering based on maxima of a weakly dependent random process
arXiv
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arXiv 2023年
作者: Boulin, Alexis Di Bernardino, Elena Laloë, Thomas Toulemonde, Gwladys Université Côte d’Azur CNRS LJAD France Univ Montpellier CNRS Montpellier France Inria Lemon France
We propose a new class of models for variable clustering called Asymptotic Independent block (AI-block) models, which defines population-level clusters based on the independence of the maxima of a multivariate station... 详细信息
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Geometric Sampling
arXiv
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arXiv 2023年
作者: Panahbehagh, Bardia Faculty of Mathematical Sciences and Computer Kharazmi University Tehran Iran
This paper introduces an innovative and intuitive finite population sampling method that have been developed using a unique geometric framework. In this approach, I represent first-order inclusion probabilities as bar... 详细信息
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Factor extraction using Kalman filter and smoothing: This is not just another survey
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INTERNATIONAL JOURNAL OF FORECASTING 2021年 第4期37卷 1399-1425页
作者: Poncela, Pilar Ruiz, Esther Miranda, Karen Univ Autonoma Madrid Dept Econ Anal Quantitat Econ Madrid Spain Univ Carlos III Madrid Dept Stat Madrid Spain
Dynamic factor models have been the main "big data'' tool used by empirical macroeconomists during the last 30 years. In this context, Kalman filter and smoothing (KFS) procedures can cope with missing da... 详细信息
来源: 评论