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Found 6 papers, 0 papers with code
SuperLoRA: Parameter-Efficient Unified Adaptation of Multi-Layer Attention Modules
Low-rank adaptation (LoRA) and its variants are widely employed in fine-tuning large models, including large language models for natural language processing and diffusion models for computer vision.
Learning to Learn Financial Networks for Optimising Momentum Strategies
Network momentum provides a novel type of risk premium, which exploits the interconnections among assets in a financial network to predict future returns.
Network Momentum across Asset Classes
We investigate the concept of network momentum, a novel trading signal derived from momentum spillover across assets.
Adversarial Bi-Regressor Network for Domain Adaptive Regression
Domain adaptation (DA) aims to transfer the knowledge of a well-labeled source domain to facilitate unlabeled target learning.
Multi-Modal Recurrent Fusion for Indoor Localization
This paper considers indoor localization using multi-modal wireless signals including Wi-Fi, inertial measurement unit (IMU), and ultra-wideband (UWB).
Multi-Band Wi-Fi Sensing with Matched Feature Granularity
The granularity matching is realized by pairing two feature maps from the CSI and beam SNR at different granularity levels and linearly combining all paired feature maps into a fused feature map with learnable weights.
