65 citations · 75 across the 13 of their papers we have counts for
13 papers
Baguan-TS: A Sequence-Native In-Context Learning Model for Time Series Forecasting with Covariates
Linxiao Yang, Xue Jiang, Gezheng Xu +9
Transformers enable in-context learning (ICL) for rapid, gradient-free adaptation in time series forecasting, yet most ICL-style approaches rely on tabularized, hand-crafted featur…
SolarBoost: Distributed Photovoltaic Power Forecasting Amid Time-varying Grid Capacity
Linyuan Geng, Linxiao Yang, Xinyue Gu +1
This paper presents SolarBoost, a novel approach for forecasting power output in distributed photovoltaic (DPV) systems. While existing centralized photovoltaic (CPV) methods are a…
ProtoTS: Learning Hierarchical Prototypes for Explainable Time Series Forecasting
Ziheng Peng, Shijie Ren, Xinyue Gu +3
While deep learning has achieved impressive performance in time series forecasting, it becomes increasingly crucial to understand its decision-making process for building trust in…
TriForecaster: A Mixture of Experts Framework for Multi-Region Electric Load Forecasting with Tri-dimensional Specialization
Zhaoyang Zhu, Zhipeng Zeng, Qiming Chen +4
Electric load forecasting is pivotal for power system operation, planning and decision-making. The rise of smart grids and meters has provided more detailed and high-quality load d…
Integrated Influence: Data Attribution with Baseline
Linxiao Yang, Xinyu Gu, Liang Sun
As an effective approach to quantify how training samples influence test sample, data attribution is crucial for understanding data and model and further enhance the transparency o…
Task-oriented Time Series Imputation Evaluation via Generalized Representers
Zhixian Wang, Linxiao Yang, Liang Sun +2
Time series analysis is widely used in many fields such as power energy, economics, and transportation, including different tasks such as forecasting, anomaly detection, classifica…
CURLS: Causal Rule Learning for Subgroups with Significant Treatment Effect
Jiehui Zhou, Linxiao Yang, Xingyu Liu +3
In causal inference, estimating heterogeneous treatment effects (HTE) is critical for identifying how different subgroups respond to interventions, with broad applications in field…
SLIM: a Scalable Light-weight Root Cause Analysis for Imbalanced Data in Microservice
Rui Ren, Jingbang Yang, Linxiao Yang +2
The newly deployed service -- one kind of change service, could lead to a new type of minority fault. Existing state-of-the-art methods for fault localization rarely consider the i…
Interactive Generalized Additive Model and Its Applications in Electric Load Forecasting
Linxiao Yang, Rui Ren, Xinyue Gu +1
Electric load forecasting is an indispensable component of electric power system planning and management. Inaccurate load forecasting may lead to the threat of outages or a waste o…
Robust Dominant Periodicity Detection for Time Series with Missing Data
Qingsong Wen, Linxiao Yang, Liang Sun
Periodicity detection is an important task in time series analysis, but still a challenging problem due to the diverse characteristics of time series data like abrupt trend change,…
Learning Interpretable Decision Rule Sets: A Submodular Optimization Approach
Fan Yang, Kai He, Linxiao Yang +4
Rule sets are highly interpretable logical models in which the predicates for decision are expressed in disjunctive normal form (DNF, OR-of-ANDs), or, equivalently, the overall mod…
Fast Compressed Power Spectrum Estimation: Towards A Practical Solution for Wideband Spectrum Sensing
Linxiao Yang, Jun Fang, Huiping Duan +1
There has been a growing interest in wideband spectrum sensing due to its applications in cognitive radios and electronic surveillance. To overcome the sampling rate bottleneck for…
Fast Low-Rank Bayesian Matrix Completion with Hierarchical Gaussian Prior Models
Linxiao Yang, Jun Fang, Huiping Duan +2
The problem of low rank matrix completion is considered in this paper. To exploit the underlying low-rank structure of the data matrix, we propose a hierarchical Gaussian prior mod…