25 citations · 27 across the 7 of their papers we have counts for
7 papers
Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting
Licheng Pan, Zhichao Chen, Haoxuan Li +5
Multi-task forecasting has become the standard approach for time-series forecasting (TSF). However, we show that it suffers from an Expressiveness Bottleneck, where predictions at…
Proximity Matters: Local Proximity Enhanced Balancing for Treatment Effect Estimation
Hao Wang, Zhichao Chen, Zhaoran Liu +3
Heterogeneous treatment effect (HTE) estimation from observational data poses significant challenges due to treatment selection bias. Existing methods address this bias by minimizi…
Modeling Task Relationships in Multi-variate Soft Sensor with Balanced Mixture-of-Experts
Yuxin Huang, Hao Wang, Zhaoran Liu +3
Accurate estimation of multiple quality variables is critical for building industrial soft sensor models, which have long been confronted with data efficiency and negative transfer…
An Accurate and Interpretable Framework for Trustworthy Process Monitoring
Hao Wang, Zhiyu Wang, Yunlong Niu +5
Trustworthy process monitoring seeks to build an accurate and interpretable monitoring framework, which is critical for ensuring the safety of energy conversion plant (ECP) that op…
Towards Relation Extraction From Speech
Tongtong Wu, Guitao Wang, Jinming Zhao +4
Relation extraction typically aims to extract semantic relationships between entities from the unstructured text. One of the most essential data sources for relation extraction is…
Entire Space Counterfactual Learning for Reliable Content Recommendations
Hao Wang, Zhichao Chen, Zhaoran Liu +4
Post-click conversion rate (CVR) estimation is a fundamental task in developing effective recommender systems, yet it faces challenges from data sparsity and sample selection bias.…
Analyze and Design Network Architectures by Recursion Formulas
Yilin Liao, Hao Wang, Zhaoran Liu +2
The effectiveness of shortcut/skip-connection has been widely verified, which inspires massive explorations on neural architecture design. This work attempts to find an effective w…