Results 101 to 110 of about 33,100 (246)
Local Search and the Evolution of World Models
Topics in Cognitive Science, EarlyView., 2023 Abstract An open question regarding how people develop their models of the world is how new candidates are generated for consideration out of infinitely many possibilities. We discuss the role that evolutionary mechanisms play in this process. Specifically, we argue that when it comes to developing a global world model, innovation is necessarily ...
Neil R. Bramley +3 more
wiley +1 more source
The State Itself as a Vulnerable Subject? Existential Resilience under International Law
The Modern Law Review, EarlyView.This paper proposes a new framework for analysis of the law governing State continuity, with particular reference to Small Island Developing States (SIDS) threatened with legal extinction as a result of rising sea‐levels. Prevailing wisdom suggests that if States were to lose their inhabitable land or permanently resident populations, their status ...
Alex Green (文浩航)
wiley +1 more source
Generalisable deep Learning framework to overcome catastrophic forgetting
Intelligent Systems with ApplicationsGeneralisation across multiple tasks is a major challenge in deep learning for medical imaging applications, as it can cause a catastrophic forgetting problem.
Zaenab Alammar +5 more
doaj +1 more source
‘A Sort of Armed Argument’: Ireland's Civil War of Words
History, EarlyView.Abstract This article sets out to contribute to the study of the languages of European civil wars through outlining and analysing the deployment of language as a weapon by the opposing sides of the Irish independence movement that split over the terms of the Anglo‐Irish Treaty of December 1921.
DONAL Ó DRISCEOIL
wiley +1 more source
Unsupervised Learning to Overcome Catastrophic Forgetting in Neural Networks
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2019 Continual learning is the ability to acquire a new task or knowledge without losing any previously collected information. Achieving continual learning in artificial intelligence (AI) is currently prevented by catastrophic forgetting, where training of a ...
Irene Munoz-Martin +5 more
doaj +1 more source
, 2016 Learning to solve complex sequences of tasks--while both leveraging transfer and avoiding catastrophic forgetting--remains a key obstacle to achieving human-level intelligence. The progressive networks approach represents a step forward in this direction:
Desjardins, Guillaume +7 more
core
Toward Understanding Catastrophic Forgetting in Continual Learning
CoRR, 2019 We study the relationship between catastrophic forgetting and properties of task sequences. In particular, given a sequence of tasks, we would like to understand which properties of this sequence influence the error rates of continual learning algorithms trained on the sequence.
Cuong V. Nguyen +5 more
openaire +2 more sources
International Journal of Urban and Regional Research, EarlyView.Abstract Contributing to global urban history, planning theory and the geography of ideas, this article discusses the travels of Henri Lefebvre’s The Right to the City in the wake of May 1968, in France. That year, under the direction of Mario González and Max Baquero, a small team including the Italian architect Vittorio Garatti, French planner Jean ...
William Kutz
wiley +1 more source
Brain InformaticsClass incremental learning (CIL) is a specific scenario in incremental learning. It aims to continuously learn new classes from the data stream, which suffers from the challenge of catastrophic forgetting.
Yan Xian, Hong Yu, Ye Wang, Guoyin Wang
doaj +1 more source
MathematicsContinual Learning (CL), the ability of a model to learn new tasks without forgetting previously acquired knowledge, remains a critical challenge in artificial intelligence. This is particularly true for Vision Transformers (ViTs) that utilize Multilayer
Zahid Ullah, Jihie Kim
doaj +1 more source