Results 61 to 70 of about 11,307,335 (373)

Online Class-Incremental Continual Learning with Adversarial Shapley Value

AAAI Conference on Artificial Intelligence, 2020
As image-based deep learning becomes pervasive on every device, from cell phones to smart watches, there is a growing need to develop methods that continually learn from data while minimizing memory footprint and power consumption.
Dongsub Shim, Zheda Mai, Jihwan Jeong, S. Sanner, Hyunwoo J. Kim, Jongseong Jang   +5 more
semanticscholar   +1 more source

A comprehensive review of the use of Shapley value to assess node importance in the analysis of biological networks

Computer Methods and Programs in Biomedicine Update
Background:: In 2017, Lundberg and Lee introduced SHAP, a breakthrough in Explainable AI, creatively applying the Shapley value to estimate the importance of input features in machine learning outputs.
Giang Pham, Paolo Milazzo
doaj   +1 more source

Two extensions of the Shapley value for cooperative games [PDF]

, 1999
Two extensions of the Shapley value are given. First we consider a probabilistic framework in which certain consistent allocation rules such as the Shapley value are characterized.
Driessen, T.S.H., Paulusma, D.
core   +2 more sources

Flux‐Regulated Crystallization of Perovskites Using Machine Learning‐Predicted Solvent Evaporation Rates for X‐Ray Detectors

Advanced Functional Materials, EarlyView.
By integrating machine learning into flux‐regulated crystallization (FRC), accurate prediction of solvent evaporation rates in real time, improving crystallization control and reducing crystal growth variability by over threefold, is achieved. This enhances the reproducibility and quality of perovskite single crystals, leading to reproducible ...
Tatiane Pretto, Sergey Dayneko, Antoine Pavesic Junior, Nicholas Sandor, Alexander Hart, Yuki Haruta, Magdalena Bazalova‐Carter, Marcos J. L. Santos, Makhsud I. Saidaminov   +8 more
wiley   +1 more source

Shapley-Based Estimation of Company Value—Concept, Algorithms and Parameters

Entropy, 2021
The aim of the article is to propose a new method of valuation of a company, considering its ownership relations with other companies. For this purpose, the concept of the Shapley value from cooperative game theory is used as the basis for assessing such
Jacek Mercik, Barbara Gładysz, Izabella Stach, Jochen Staudacher   +3 more
doaj   +1 more source

The Shapley value for airport and irrigation games [PDF]

, 2011
In this paper cost sharing problems are considered. We focus on problems given by rooted trees, we call these problems cost-tree problems, and on the induced transferable utility cooperative games, called irrigation games.
Márkus, Judit, Pintér, Miklós, Radványi, Anna   +2 more
core   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Calculation of exact Shapley values for explaining support vector machine models using the radial basis function kernel

Scientific Reports, 2023
Machine learning (ML) algorithms are extensively used in pharmaceutical research. Most ML models have black-box character, thus preventing the interpretation of predictions.
Andrea Mastropietro, Christian Feldmann, Jürgen Bajorath   +2 more
doaj   +1 more source

Shapley Values as a Strategy for Ensemble Weights Estimation

Applied Sciences, 2023
This study introduces a novel performance-based weighting scheme for ensemble learning using the Shapley value. The weighting uses the reciprocal of binary cross-entropy as a base learner’s performance metric and estimates its Shapley value to measure ...
Vaidotas Drungilas, Evaldas Vaičiukynas, Linas Ablonskis, Lina Čeponienė   +3 more
doaj   +1 more source

Digital Discovery of Synthesizable Metal−Organic Frameworks via Molecular Dynamics‑Informed, High‑Fidelity Deep Learning

Advanced Functional Materials, EarlyView.
Tabular foundation model interrogates the synthetic likelihood of metal−organic frameworks. Abstract Metal–organic frameworks (MOFs) are celebrated for their chemical and structural versatility, and in‑silico screening has significantly accelerated their discovery; yet most hypothetical MOFs (hMOFs) never reach the bench because their synthetic ...
Xiaoyu Wu, Rui Zheng, Quan Liu, Jianwen Jiang   +3 more
wiley   +1 more source