4 citations · 4 across the 10 of their papers we have counts for
10 papers
FedReLa: Imbalanced Federated Learning via Re-Labeling
Guangzheng Hu, Patricia Menéndez, Feng Liu +3
Federated learning has emerged as the foremost approach for decentralized model training with privacy preservation. The global class imbalance and cross-client data heterogeneity n…
SnapGen++: Unleashing Diffusion Transformers for Efficient High-Fidelity Image Generation on Edge Devices
Dongting Hu, Aarush Gupta, Magzhan Gabidolla +12
Recent advances in diffusion transformers (DiTs) have set new standards in image generation, yet remain impractical for on-device deployment due to their high computational and mem…
Are Two Datasets Close Enough With Statistical Significance? A Kernel Distributional Closeness Testing Approach
Zhijian Zhou, Liuhua Peng, Xunye Tian +2
Are two distributions close to each other with statistical significance? Distribution closeness testing (DCT) formalizes this question by testing whether the distance between a dis…
MF-VITON: High-Fidelity Mask-Free Virtual Try-On with Minimal Input
Zhenchen Wan, Yanwu xu, Dongting Hu +6
Recent advancements in Virtual Try-On (VITON) have significantly improved image realism and garment detail preservation, driven by powerful text-to-image (T2I) diffusion models. Ho…
LoCA: Location-Aware Cosine Adaptation for Parameter-Efficient Fine-Tuning
Zhekai Du, Yinjie Min, Jingjing Li +5
Low-rank adaptation (LoRA) has become a prevalent method for adapting pre-trained large language models to downstream tasks. However, the simple low-rank decomposition form may con…
SnapGen: Taming High-Resolution Text-to-Image Models for Mobile Devices with Efficient Architectures and Training
Dongting Hu, Jierun Chen, Xijie Huang +16
Existing text-to-image (T2I) diffusion models face several limitations, including large model sizes, slow runtime, and low-quality generation on mobile devices. This paper aims to…
Probabilistic Modeling of Disparity Uncertainty for Robust and Efficient Stereo Matching
Wenxiao Cai, Dongting Hu, Ruoyan Yin +4
Stereo matching plays a crucial role in various applications, where understanding uncertainty can enhance both safety and reliability. Despite this, the estimation and analysis of…
A Unified Data Representation Learning for Non-parametric Two-sample Testing
Xunye Tian, Liuhua Peng, Zhijian Zhou +3
Learning effective data representations has been crucial in non-parametric two-sample testing. Common approaches will first split data into training and test sets and then learn da…
AniFaceDiff: Animating Stylized Avatars via Parametric Conditioned Diffusion Models
Ken Chen, Sachith Seneviratne, Wei Wang +7
Animating stylized avatars with dynamic poses and expressions has attracted increasing attention for its broad range of applications. Previous research has made significant progres…
STBA: Towards Evaluating the Robustness of DNNs for Query-Limited Black-box Scenario
Renyang Liu, Kwok-Yan Lam, Wei Zhou +4
Many attack techniques have been proposed to explore the vulnerability of DNNs and further help to improve their robustness. Despite the significant progress made recently, existin…