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Tag: functional

  • Functional Central Limit Theorem for Stochastic Gradient Descent

    Functional Central Limit Theorem for Stochastic Gradient Descent arXiv:2602.15538v1 Announce Type: new Abstract: We study the asymptotic shape of the trajectory of the stochastic gradient descent algorithm applied to a convex objective function. Under mild regularity assumptions, we prove a functional central limit theorem for the properly rescaled trajectory. Our result characterizes the long-term fluctuations…

  • Deep learning estimation of the spectral density of functional time series on large domains

    Deep learning estimation of the spectral density of functional time series on large domains arXiv:2601.00284v1 Announce Type: cross Abstract: We derive an estimator of the spectral density of a functional time series that is the output of a multilayer perceptron neural network. The estimator is motivated by difficulties with the computation of existing spectral density…

  • Functional Random Forest with Adaptive Cost-Sensitive Splitting for Imbalanced Functional Data Classification

    Functional Random Forest with Adaptive Cost-Sensitive Splitting for Imbalanced Functional Data Classification arXiv:2512.07888v1 Announce Type: new Abstract: Classification of functional data where observations are curves or trajectories poses unique challenges, particularly under severe class imbalance. Traditional Random Forest algorithms, while robust for tabular data, often fail to capture the intrinsic structure of functional observations and…

  • Bayesian Optimization for Function-Valued Responses under Min-Max Criteria

    Bayesian Optimization for Function-Valued Responses under Min-Max Criteria arXiv:2512.07868v1 Announce Type: cross Abstract: Bayesian optimization is widely used for optimizing expensive black box functions, but most existing approaches focus on scalar responses. In many scientific and engineering settings the response is functional, varying smoothly over an index such as time or wavelength, which makes classical…

  • Partial Functional Dynamic Backdoor Diffusion-based Causal Model

    Partial Functional Dynamic Backdoor Diffusion-based Causal Model arXiv:2509.00472v1 Announce Type: new Abstract: We introduce a Partial Functional Dynamic Backdoor Diffusion-based Causal Model (PFD-BDCM), specifically designed for causal inference in the presence of unmeasured confounders with spatial heterogeneity and temporal dependency. The proposed PFD-BDCM framework addresses the restrictions of the existing approaches by uniquely integrating models…

  • L1-Regularized Functional Support Vector Machine

    L1-Regularized Functional Support Vector Machine arXiv:2508.05567v1 Announce Type: new Abstract: In functional data analysis, binary classification with one functional covariate has been extensively studied. We aim to fill in the gap of considering multivariate functional covariates in classification. In particular, we propose an $L_1$-regularized functional support vector machine for binary classification. An accompanying algorithm is…

  • funOCLUST: Clustering Functional Data with Outliers

    funOCLUST: Clustering Functional Data with Outliers arXiv:2508.00110v1 Announce Type: new Abstract: Functional data present unique challenges for clustering due to their infinite-dimensional nature and potential sensitivity to outliers. An extension of the OCLUST algorithm to the functional setting is proposed to address these issues. The approach leverages the OCLUST framework, creating a robust method to…

  • Semi-parametric Functional Classification via Path Signatures Logistic Regression

    Semi-parametric Functional Classification via Path Signatures Logistic Regression arXiv:2507.06637v1 Announce Type: new Abstract: We propose Path Signatures Logistic Regression (PSLR), a semi-parametric framework for classifying vector-valued functional data with scalar covariates. Classical functional logistic regression models rely on linear assumptions and fixed basis expansions, which limit flexibility and degrade performance under irregular sampling. PSLR overcomes…

  • What is your functional area?

    What is your functional area? I don’t mean industry. I mean product, operations, etc. I work in operations. I don’t grow the business. I keep the business alive. submitted by /u/Trick-Interaction396 [link] [comments] /u/Trick-Interaction396 Go to original source

  • Fairness-aware Bayes optimal functional classification

    Fairness-aware Bayes optimal functional classification arXiv:2505.09471v1 Announce Type: new Abstract: Algorithmic fairness has become a central topic in machine learning, and mitigating disparities across different subpopulations has emerged as a rapidly growing research area. In this paper, we systematically study the classification of functional data under fairness constraints, ensuring the disparity level of the classifier…

  • Enhancing Visual Interpretability and Explainability in Functional Survival Trees and Forests

    Enhancing Visual Interpretability and Explainability in Functional Survival Trees and Forests arXiv:2504.18498v1 Announce Type: new Abstract: Functional survival models are key tools for analyzing time-to-event data with complex predictors, such as functional or high-dimensional inputs. Despite their predictive strength, these models often lack interpretability, which limits their value in practical decision-making and risk analysis. This…

  • Scalable Geometric Learning with Correlation-Based Functional Brain Networks

    Scalable Geometric Learning with Correlation-Based Functional Brain Networks arXiv:2503.23653v1 Announce Type: new Abstract: The correlation matrix is a central representation of functional brain networks in neuroimaging. Traditional analyses often treat pairwise interactions independently in a Euclidean setting, overlooking the intrinsic geometry of correlation matrices. While earlier attempts have embraced the quotient geometry of the correlation…

  • Bayesian Kernel Regression for Functional Data

    Bayesian Kernel Regression for Functional Data arXiv:2503.13676v1 Announce Type: new Abstract: In supervised learning, the output variable to be predicted is often represented as a function, such as a spectrum or probability distribution. Despite its importance, functional output regression remains relatively unexplored. In this study, we propose a novel functional output regression model based on…

  • Tensor Product Neural Networks for Functional ANOVA Model

    Tensor Product Neural Networks for Functional ANOVA Model arXiv:2502.15215v1 Announce Type: new Abstract: Interpretability for machine learning models is becoming more and more important as machine learning models become more complex. The functional ANOVA model, which decomposes a high-dimensional function into a sum of lower dimensional functions so called components, is one of the most…

  • Variable Selection Methods for Multivariate, Functional, and Complex Biomedical Data in the AI Age

    Variable Selection Methods for Multivariate, Functional, and Complex Biomedical Data in the AI Age arXiv:2501.06868v1 Announce Type: new Abstract: Many problems within personalized medicine and digital health rely on the analysis of continuous-time functional biomarkers and other complex data structures emerging from high-resolution patient monitoring. In this context, this work proposes new optimization-based variable selection…

  • Introduction to TensorFlow’s Functional API

    Introduction to TensorFlow’s Functional API Learn what the Functional API is, and how to build complex keras models using it Continue reading on Towards Data Science » Javier Martínez Ojeda Go to original source

  • Functional relevance based on the continuous Shapley value

    Functional relevance based on the continuous Shapley value arXiv:2411.18575v1 Announce Type: new Abstract: The presence of Artificial Intelligence (AI) in our society is increasing, which brings with it the need to understand the behaviour of AI mechanisms, including machine learning predictive algorithms fed with tabular data, text, or images, among other types of data. This…