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Class-incremental Learning for Time Series: Benchmark and Evaluation

Class-incremental Learning for Time Series: Benchmark and Evaluation

19 February 2024
Zhongzheng Qiao
Quang-Cuong Pham
Zhen Cao
Hoang H Le
Ponnuthurai Nagaratnam Suganthan
Xudong Jiang
Savitha Ramasamy
ArXivPDFHTML

Papers citing "Class-incremental Learning for Time Series: Benchmark and Evaluation"

6 / 6 papers shown
Title
Dynamic Integration of Task-Specific Adapters for Class Incremental Learning
Dynamic Integration of Task-Specific Adapters for Class Incremental Learning
Jiashuo Li
Shaokun Wang
Bo Qian
Yuhang He
Xing Wei
Qiang Wang
Yihong Gong
CLL
77
1
0
23 Sep 2024
Towards Continual Learning Desiderata via HSIC-Bottleneck
  Orthogonalization and Equiangular Embedding
Towards Continual Learning Desiderata via HSIC-Bottleneck Orthogonalization and Equiangular Embedding
Depeng Li
Tianqi Wang
Junwei Chen
Qining Ren
Kenji Kawaguchi
Zhigang Zeng
CLL
32
2
0
17 Jan 2024
Exploring System Performance of Continual Learning for Mobile and
  Embedded Sensing Applications
Exploring System Performance of Continual Learning for Mobile and Embedded Sensing Applications
Young D. Kwon
Jagmohan Chauhan
Abhishek Kumar
Pan Hui
Cecilia Mascolo
CLL
HAI
19
32
0
25 Oct 2021
Soft-DTW: a Differentiable Loss Function for Time-Series
Soft-DTW: a Differentiable Loss Function for Time-Series
Marco Cuturi
Mathieu Blondel
AI4TS
127
601
0
05 Mar 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,042
0
06 Jun 2015
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
279
39,083
0
01 Sep 2014
1