Results 91 to 100 of about 10,752 (214)

The fuzzy Kullback-Leibler divergence for estimating parameters of the probability distribution in fuzzy data: an application to classifying Vietnamese Herb Leaves. [PDF]

Sci Rep, 2023
Le H, Sang VNT, Lam Thuy LN, Bao PT.
europepmc   +1 more source

Multi‐Objective Bayesian Co‐Optimization of Parameterized Moving Horizon Estimation and Model Predictive Control

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT This paper proposes a Machine Learning (ML)‐enabled estimator‐controller design framework, in which a parameterized Model Predictive Controller (MPC) and a parameterized Moving Horizon Estimator (MHE) are jointly refined using Bayesian Optimization (BO).
Hossein Nejatbakhsh Esfahani, Javad Mohammadpour Velni   +1 more
wiley   +1 more source

Affine Calculus for Constrained Minima of the Kullback–Leibler Divergence

Stats
The non-parametric version of Amari’s dually affine Information Geometry provides a practical calculus to perform computations of interest in statistical machine learning.
Giovanni Pistone
doaj   +1 more source

Sustainability Assessment: The Role of Entropy‐Based Indicators for Reconnecting Human' Subjectivity and Civilization With Natural Tendency of Ecosystems

Sustainable Development, EarlyView.
ABSTRACT Sustainability represents a complex issue in which scientific knowledge inevitably coexists with the subjective perception of humans in its turn influenced by civilization, cultural but also unconscious aspects. These results emerge with evidence from a critical analysis of the main definitions of sustainability delivered by credited entities (
Francesco Di Maria, Hamid Safarzadeh
wiley   +1 more source

Correction : Random-forest model for drug-target interaction prediction via Kullback-Leibler divergence. [PDF]

J Cheminform, 2022
Ahn S, Lee SE, Kim MH.
europepmc   +1 more source

Visionary, engineer, and experimenter: Three forms of entrepreneurship in the quest for product–market fit

Strategic Entrepreneurship Journal, EarlyView.
Abstract Research summary Entrepreneurship unfolds under uncertainty, which complicates entrepreneurs' efforts to align idea, action, and environment to reach product–market fit. To illuminate how entrepreneurs perform such alignment, we complement the theory‐based view and its focus on cognitive uncertainty with a discussion of behavioral uncertainty.
Thomas Zellweger, Djordje Djokovic
wiley   +1 more source

Using Feature Engineering and Principal Component Analysis for Monitoring Spindle Speed Change Based on Kullback-Leibler Divergence with a Gaussian Mixture Model. [PDF]

Sensors (Basel), 2023
Huang YC, Hou CC.
europepmc   +1 more source

PowerGPT‐R1: Vision‐Language Reinforcement Fine‐Tuning With Verifiable Reward for Power Inspection

High Voltage, EarlyView.
ABSTRACT Vision‐driven intelligent power inspection systems have long faced the challenge of scarce high‐quality datasets in specialised domains, leading to limited performance of traditional deep learning methods (e.g., Faster‐RCNN) in few‐shot learning scenarios. Recent breakthroughs in language models, particularly the open‐source DeepSeek‐R1 model,
Yangyang Zhong, Pengxin Luo, Yunfeng Yan, Jun Feng, Shixiang Tang, Weizhen He, Yiheng Deng, Yi Chen, Yuhao Zhou, Qi Li, Xianbo Wang, Fushuan Wen, Donglian Qi   +12 more
wiley   +1 more source

Bregman–Hausdorff Divergence: Strengthening the Connections Between Computational Geometry and Machine Learning

Machine Learning and Knowledge Extraction
The purpose of this paper is twofold. On a technical side, we propose an extension of the Hausdorff distance from metric spaces to spaces equipped with asymmetric distance measures.
Tuyen Pham, Hana Dal Poz Kouřimská, Hubert Wagner   +2 more
doaj   +1 more source

Deep blueprint: A literature review and guide to automated image classification for ecologists

Journal of Animal Ecology, EarlyView.
A practical, literature‐grounded review that gives ecologists a clear, modular workflow for deep learning image classification. With code, GUIs and a novel deep sea case study (automated deep sea biotope classification) it lowers technical barriers and provides a usable blueprint for accelerating, standardising, and scaling ecological image analysis ...
Chloe A. Game, Nils Piechaud, Kerry L. Howell   +2 more
wiley   +1 more source