Results 61 to 70 of about 3,537 (211)

The In Vivo Microstructural Profile of Human Hippocampal Subfield CA1 and Its Relation to Memory Performance

Human Brain Mapping, Volume 47, Issue 7, May 2026.
Using 7 T structural MRI, we mapp layer‐dependent microstructural profiles of hippocampal subfield CA1 in vivo and linked them to individual differences in memory performance. The results reveal detectable, layer‐specific myelin patterns that mirror canonical histological organization, providing a framework for studying microstructural alterations in ...
Dayana Hayek, Joseph Höpker Fernandes, Niklas Vockert, Berta Garcia‐Garcia, Hendrik Mattern, Niklas Behrenbruch, Larissa Fischer, Avinash Kalyani, Juliane Doehler, Dorothea Hämmerer, Yeo‐Jin Yi, Stefanie Schreiber, Anne Maass, Esther Kuehn   +13 more
wiley   +1 more source

A Survey on Multi-Task Learning

, 2017
Multi-Task Learning (MTL) is a learning paradigm in machine learning and its aim is to leverage useful information contained in multiple related tasks to help improve the generalization performance of all the tasks.
Zhang, Yu, Yang, Qiang
core   +1 more source

Unraveling the Potential of MXenes in Electrochemical Sensing: Mechanistic Insight, Design Principles, and Analytical Applications

Small Science, Volume 6, Issue 5, May 2026.
This review comprehensively examines recent progress in MXene‐based electrochemical sensors for the detection of glucose, hydrogen peroxide, heavy metals, pesticides, nitrites, phenolic pollutants, neurotransmitters, biomarkers, and pharmaceutical compounds.
Hichem Moulahoum, Faezeh Ghorbanizamani, Tomáš Kovářík, Kalim Deshmukh   +3 more
wiley   +1 more source

PRO-MTL : Parameterized Route Optimization using Multi-Task Learning

ACM Transactions on Intelligent Systems and Technology
In the current ridesharing scenario, finding a compatible passenger is highly challenging and largely dependent on chance. Existing algorithms prioritize the shortest route without considering future requests or traffic conditions, which reduces the likelihood of matching with another compatible passenger. This uncertainty leads to increased congestion
Jayant Vyas, Jayesh Budhwani, Debasis Das 0001   +2 more
openaire   +1 more source

MTL-Split: Multi-Task Learning for Edge Devices using Split Computing

Proceedings of the 61st ACM/IEEE Design Automation Conference
Accepted at the 61st Design Automation Conference (DAC 2024)
Luigi Capogrosso, Enrico Fraccaroli, Samarjit Chakraborty, Franco Fummi, Marco Cristani   +4 more
openaire   +3 more sources

Origins and Evolution of Imagination, From Australopithecus to Modern‐Day Deep Learning

WIREs Cognitive Science, Volume 17, Issue 3, May/June 2026.
From Australopithecus to deep learning, this update traces how imaginative generativity, vivid mental imagery, and recombines memory into novel scenarios that evolved as a survival engine shaping consciousness, culture, and even today's AI. ABSTRACT Where does imagination come from?
Kiranpreet K. Sidhu, Raymond Roy, Amedeo D'Angiulli   +2 more
wiley   +1 more source

Local rademacher complexity-based learning guarantees for multi-task learning

, 2018
We show a Talagrand-type concentration inequality for Multi-Task Learning (MTL), with which we establish sharp excess risk bounds for MTL in terms of the Local Rademacher Complexity (LRC).
Anagnostopoulos, Georgios C., Kloft, Marius, Lei, Yunwen, Mollaghasemi, Mansooreh, Yousefi, Niloofar   +4 more
core   +1 more source

Deep Safe Multi-Task Learning

, 2022
In recent years, Multi-Task Learning (MTL) has attracted much attention due to its good performance in many applications. However, many existing MTL models cannot guarantee that their performance is no worse than their single-task counterparts on each ...
Zhang, Yu, Tsang, Ivor W., Yue, Zhixiong, Ye, Feiyang, Liang, Christy   +4 more
core  

Estimation of Potato Growth Parameters Under Limited Field Data Availability by Integrating Few-Shot Learning and Multi-Task Learning

Agriculture
Leaf chlorophyll content (LCC), leaf area index (LAI), and above-ground biomass (AGB) are important growth parameters for characterizing potato growth and predicting yield.
Sen Yang, Quan Feng, Faxu Guo, Wenwei Zhou   +3 more
doaj   +1 more source

Climate‐Smart Dairy Practices: The Role of Practice Clusters in Enhancing the Performance of Dairy Farms in Kenya

Agribusiness, Volume 42, Issue 2, Page 717-732, Spring 2026.
ABSTRACT Climate variability is affecting the productivity, profitability, and resilience of smallholder dairy producers in developing countries. The adoption of climate‐smart (CS) dairy practices has been promoted to mitigate these negative effects. However, while interest in dairy CS practices is growing, empirical evidence on their adoption patterns
Mercy Mburu, Amin Mugera, John Mburu, Rose Nyikal, Oghaiki Asaah Ndambi   +4 more
wiley   +1 more source