A personalized communication efficient federated learning framework with low rank adaptation for intelligent leukemia diagnosis [PDF]
Scientific ReportsLeukemia diagnosis with medical imaging necessitates the development of highly accurate and individualized models that uphold data privacy among institutions. This research proposes a framework named FedPerLoRA-Health, a communication-efficient federated
P. Suresh +2 more
doaj +2 more sources
A framework for efficient scientific diagram captioning using mixture-of-experts and low-rank adaptation [PDF]
Scientific ReportsGenerating captions for diagrams is a challenging task because of their complex structures, diverse visual elements, and domain-specific semantic content.
Deepika Kamboj, Gaurav Harit
doaj +2 more sources
Cross-domain subcortical brain structure segmentation algorithm based on low-rank adaptation fine-tuning SAM [PDF]
BMC Medical ImagingPurpose Accurate and robust segmentation of anatomical structures in brain MRI provides a crucial basis for the subsequent observation, analysis, and treatment planning of various brain diseases.
Yuan Sui, Qian Hu, Yujie Zhang
doaj +2 more sources
Lottery Rank-Pruning Adaptation Parameter Efficient Fine-Tuning
MathematicsRecent studies on parameter-efficient fine-tuning (PEFT) have introduced effective and efficient methods for fine-tuning large language models (LLMs) on downstream tasks using fewer parameters than required by full fine-tuning.
Sangwoo Kang, Gyunyeop Kim
exaly +3 more sources
Dynamic Low-Rank Instance Adaptation for Universal Neural Image Compression [PDF]
, 2023 The latest advancements in neural image compression show great potential in surpassing the rate-distortion performance of conventional standard codecs.
Xiang, Jinxi +5 more
core +1 more source
Low rank prior in single patches for non-pointwise impulse noise removal [PDF]
, 2015 This paper introduces a low rank prior in small oriented noise-free image patches: Considering an oriented patch as a matrix, a low-rank matrix approximation is enough to preserve the texture details in the optimally oriented patch.
Trucco, Emanuele; id_orcid +2 more
core +1 more source
Dynamical low-rank training of neural networks [PDF]
, 2022 openNeural networks have achieved tremendous success in a large variety of applications. However, their space and time computational demand can limit their usage in resource limited devices. At the same time, overparametrization seems to be necessary in
ZANGRANDO, EMANUELE
core
Open-Vocabulary Speech Emotion Recognition Based on Improved Low-Rank Adaptation [PDF]
Jisuanji kexue yu tansuoThe emergence of audio large language models (AudioLLMs) has propelled speech emotion recognition (SER) from simple categorical discrimination toward profound emotional understanding, aiming to transcend current closed-set classification paradigms by ...
LIU Kangwei, DING Hanyu, GAO Lijian, MAO Qirong
doaj +1 more source
Simultaneously Improve Transferability and Discriminability for Adversarial Domain Adaptation
Entropy, 2021 Although adversarial domain adaptation enhances feature transferability, the feature discriminability will be degraded in the process of adversarial learning.
Ting Xiao +3 more
doaj +1 more source
Sparse Low-rank Adaptation of Pre-trained Language Models [PDF]
, 2023 Fine-tuning pre-trained large language models in a parameter-efficient manner is widely studied for its effectiveness and efficiency. The popular method of low-rank adaptation (LoRA) offers a notable approach, hypothesizing that the adaptation process is
Lv, Xingtai +6 more
core +1 more source