1 citations · 1 across the 8 of their papers we have counts for
9 papers
FusAD: Time-Frequency Fusion with Adaptive Denoising for General Time Series Analysis
Da Zhang, Bingyu Li, Zhiyuan Zhao +3
Time series analysis plays a vital role in fields such as finance, healthcare, industry, and meteorology, underpinning key tasks including classification, forecasting, and anomaly…
UniDiff: A Unified Diffusion Framework for Multimodal Time Series Forecasting
Da Zhang, Bingyu Li, Zhuyuan Zhao +3
As multimodal data proliferates across diverse real-world applications, leveraging heterogeneous information such as texts and timestamps for accurate time series forecasting (TSF)…
FAIM: Frequency-Aware Interactive Mamba for Time Series Classification
Da Zhang, Bingyu Li, Zhiyuan Zhao +4
Time series classification (TSC) is crucial in numerous real-world applications, such as environmental monitoring, medical diagnosis, and posture recognition. TSC tasks require mod…
Towards Federated Clustering: A Client-wise Private Graph Aggregation Framework
Guanxiong He, Jie Wang, Liaoyuan Tang +3
Federated clustering addresses the critical challenge of extracting patterns from decentralized, unlabeled data. However, it is hampered by the flaw that current approaches are for…
Dynamic Manipulation of Deformable Objects in 3D: Simulation, Benchmark and Learning Strategy
Guanzhou Lan, Yuqi Yang, Anup Teejo Mathew +5
Goal-conditioned dynamic manipulation is inherently challenging due to complex system dynamics and stringent task constraints, particularly in deformable object scenarios character…
Riemannian Optimization on Relaxed Indicator Matrix Manifold
Jinghui Yuan, Fangyuan Xie, Feiping Nie +1
The indicator matrix plays an important role in machine learning, but optimizing it is an NP-hard problem. We propose a new relaxation of the indicator matrix and prove that this r…