17 citations · 28 across the 11 of their papers we have counts for
12 papers
PDMP: Rethinking Balanced Multimodal Learning via Performance-Dominant Modality Prioritization
Shicai Wei, Chunbo Luo, Qiang Zhu +1
Multimodal learning has attracted increasing attention due to its practicality. However, it often suffers from insufficient optimization, where the multimodal model underperforms e…
Improving Multimodal Learning via Imbalanced Learning
Shicai Wei, Chunbo Luo, Yang Luo
Multimodal learning often encounters the under-optimized problem and may perform worse than unimodal learning. Existing approaches attribute this issue to imbalanced learning acros…
Boosting Multimodal Learning via Disentangled Gradient Learning
Shicai Wei, Chunbo Luo, Yang Luo
Multimodal learning often encounters the under-optimized problem and may have worse performance than unimodal learning. Existing methods attribute this problem to the imbalanced le…
AE-DENet: Enhancement for Deep Learning-based Channel Estimation in OFDM Systems
Ephrem Fola, Yang Luo, Chunbo Luo
Deep learning (DL)-based methods have demonstrated remarkable achievements in addressing orthogonal frequency division multiplexing (OFDM) channel estimation challenges. However, e…
Robust Multimodal Learning via Representation Decoupling
Shicai Wei, Yang Luo, Yuji Wang +1
Multimodal learning robust to missing modality has attracted increasing attention due to its practicality. Existing methods tend to address it by learning a common subspace represe…
Scale Decoupled Distillation
Shicai Wei Chunbo Luo Yang Luo
Logit knowledge distillation attracts increasing attention due to its practicality in recent studies. However, it often suffers inferior performance compared to the feature knowled…
Intelligent Reflecting Surfaces vs. Full-Duplex Relays: A Comparison in the Air
Qian Ding, Jie Yang, Yang Luo +1
This letter aims to provide a fundamental analytical comparison for the two major types of relaying methods: intelligent reflecting surfaces and full-duplex relays, particularly fo…
Towards the THz Networks in the 6G Era
Qian Ding, Jie Yang, Yang Luo +1
This commentary dedicates to envision what role THz is going to play in the coming human-centric 6G era. Three distinct THz network types including outdoor, indoor, and body area n…
One-stage Modality Distillation for Incomplete Multimodal Learning
Shicai Wei, Yang Luo, Chunbo Luo
Learning based on multimodal data has attracted increasing interest recently. While a variety of sensory modalities can be collected for training, not all of them are always availa…
MMANet: Margin-aware Distillation and Modality-aware Regularization for Incomplete Multimodal Learning
Shicai Wei, Yang Luo, Chunbo Luo
Multimodal learning has shown great potentials in numerous scenes and attracts increasing interest recently. However, it often encounters the problem of missing modality data and t…
Deep Learning Based Automatic Modulation Recognition: Models, Datasets, and Challenges
Fuxin Zhang, Chunbo Luo, Jialang Xu +2
Automatic modulation recognition (AMR) detects the modulation scheme of the received signals for further signal processing without needing prior information, and provides the essen…
An Efficient Deep Learning Model for Automatic Modulation Recognition Based on Parameter Estimation and Transformation
Fuxin Zhang, Chunbo Luo, Jialang Xu +1
Automatic modulation recognition (AMR) is a promising technology for intelligent communication receivers to detect signal modulation schemes. Recently, the emerging deep learning (…