In this paper, a multi-layer weighted extreme learning machine (ML-WELM) is proposed for high-dimensional datasets with class imbalance.
Efficient representation learning for high-dimensional imbalance data
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A multi-layer weighted extreme learning machine (ML-WELM) provides efficient representation learning for big image data using multiple hidden layers and at ...
In this paper, a multi-layer weighted extreme learning machine (ML-WELM) is proposed for high-dimensional datasets with class imbalance.
Abstract—In this paper, a multi-layer weighted extreme learning machine (ML-WELM) is proposed for high-dimensional datasets with class imbalance.
Efficient representation learning for high-dimensional imbalance data. B. Mirza, S. Kok, Z. Lin, Y. Yeo, X. Lai, J. Cao, and J. Sepulveda. DSP, page 511-515.
Dec 1, 2020 · In this paper, we propose a novel neural network-based method, called Consistent Representation Learning (CRL), to accomplish the three associated tasks end-to ...
Missing: Efficient imbalance
Nov 9, 2021 · We present a new imbalanced data learning model using energy-based contrastive learning for causal representations.
Dec 1, 2023 · This paper proposes a new multi-module intrusion detection system: DWGF-IDS, which consists of three modules: feature extraction, imbalance processing and ...
Missing: Efficient | Show results with:Efficient
May 9, 2024 · Imbalanced learning constitutes one of the most formidable challenges within data mining and machine learning. Despite continuous research ...
Jul 21, 2021 · To investigate suitable methodological solutions to deal with datasets that are both high-dimensional and class-imbalanced, we begin by studying ...