Results 31 to 40 of about 6,336,923 (296)

Evaluating Continual Learning Algorithms by Generating 3D Virtual Environments [PDF]

, 2022
Continual learning refers to the ability of humans and animals to incrementally learn over time in a given environment. Trying to simulate this learning process in machines is a challenging task, also due to the inherent difficulty in creating conditions
Marullo, Simone, Meloni, Enrico, Melacci, Stefano, Betti, Alessandro, Tiezzi, Matteo, Faggi, Lapo   +5 more
core   +1 more source

A review of continual learning for robotics

智能科学与技术学报, 2022
One of the limitations of robotics is that it is difficult for robots to adapt to fickle tasks.A robot will inevitably forget the knowledge from old environments or tasks when facing new environments or tasks.In order to summarize research in continual ...
Chao ZHAO, Jie XU, Xingyu CHEN, Kuizhi MEI, Xuguang LAN   +4 more
doaj  

Visual Tracking by Adaptive Continual Meta-Learning

IEEE Access, 2022
We formulate the visual tracking problem as a semi-supervised continual learning problem, where only an initial frame is labeled. In contrast to conventional meta-learning based approaches that regard visual tracking as an instance detection problem with
Janghoon Choi, Sungyong Baik, Myungsub Choi, Junseok Kwon, Kyoung Mu Lee   +4 more
doaj   +1 more source

Continuous Invariance Learning

CoRR, 2023
Invariance learning methods aim to learn invariant features in the hope that they generalize under distributional shifts. Although many tasks are naturally characterized by continuous domains, current invariance learning techniques generally assume categorically indexed domains. For example, auto-scaling in cloud computing often needs a CPU utilization
Yong Lin, Fan Zhou 0012, Lu Tan, Lintao Ma, Jiameng Liu, Yansu He, Yuan Yuan, Yu Liu 0071, James Zhang, Yujiu Yang 0001, Hao Wang 0014   +10 more
openaire   +4 more sources

Exploration of the continual learning ability that supports the application ecological evolution of the large-scale pretraining Peng Cheng series open source models

智能科学与技术学报, 2022
Large-scale pre-training models have achieved great success in the field of natural language processing by using large-scale corpora and pre-training tasks.With the gradual development of large models, the continual learning ability of large models has ...
Yue YU, Xin LIU, Fangqing JIANG, Han ZHANG, Hui WANG, Wei ZENG   +5 more
doaj  

Bilevel Continual Learning

CoRR, 2020
Continual learning aims to learn continuously from a stream of tasks and data in an online-learning fashion, being capable of exploiting what was learned previously to improve current and future tasks while still being able to perform well on the previous tasks.
Quang Pham, Doyen Sahoo, Chenghao Liu, Steven C. H. Hoi   +3 more
openaire   +2 more sources

Heterogeneous Continual Learning

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
Accepted to CVPR ...
Divyam Madaan, Hongxu Yin, Wonmin Byeon, Jan Kautz, Pavlo Molchanov 0001   +4 more
openaire   +3 more sources

Latent Replay for Continual Learning on Edge devices with Efficient Architectures [PDF]

, 2023
openDue to the limited computational capabilities, low memory and limited energy budget, training deep neural networks on edge devices is very challenging.
TREMONTI, MATTEO
core  

Survey of Pre-training-based Continual Learning Methods (Invited) [PDF]

Jisuanji gongcheng
Traditional machine learning algorithms perform well only when the training and testing sets are identically distributed. They cannot perform incremental learning for new categories or tasks that were not present in the original training set.
LU Yue, ZHOU Xiangyu, ZHANG Shizhou, LIANG Guoqiang, XING Yinghui, CHENG De, ZHANG Yanning
doaj   +1 more source

Decentralized Federated Continual Learning Method Combined with Meta-learning [PDF]

Jisuanji kexue
For the problems of continual learning and data security in federated continual scenarios,a decentralized federated continual learning framework combined with meta-learning is constructed.First,in order to solve the problem of catastrophic forgetting in ...
HUANG Nan, LI Dongdong, YAO Jia, WANG Zhe
doaj   +1 more source