213 citations · 219 across the 6 of their papers we have counts for
6 papers
Exploring Multi-Modal Data with Tool-Augmented LLM Agents for Precise Causal Discovery
ChengAo Shen, Zhengzhang Chen, Dongsheng Luo +3
Causal discovery is an imperative foundation for decision-making across domains, such as smart health, AI for drug discovery and AIOps. Traditional statistical causal discovery met…
Parameterized Explainer for Graph Neural Network
Dongsheng Luo, Wei Cheng, Dongkuan Xu +4
Despite recent progress in Graph Neural Networks (GNNs), explaining predictions made by GNNs remains a challenging open problem. The leading method independently addresses the loca…
Leveraging Adversarial Training in Self-Learning for Cross-Lingual Text Classification
Xin Dong, Yaxin Zhu, Yupeng Zhang +4
In cross-lingual text classification, one seeks to exploit labeled data from one language to train a text classification model that can then be applied to a completely different la…
Longitudinal Deep Kernel Gaussian Process Regression
Junjie Liang, Yanting Wu, Dongkuan Xu +1
Gaussian processes offer an attractive framework for predictive modeling from longitudinal data, i.e., irregularly sampled, sparse observations from a set of individuals over time.…
LMLFM: Longitudinal Multi-Level Factorization Machine
Junjie Liang, Dongkuan Xu, Yiwei Sun +1
We consider the problem of learning predictive models from longitudinal data, consisting of irregularly repeated, sparse observations from a set of individuals over time. Such data…
PIGMIL: Positive Instance Detection via Graph Updating for Multiple Instance Learning
Dongkuan Xu, Jia Wu, Wei Zhang +1
Positive instance detection, especially for these in positive bags (true positive instances, TPIs), plays a key role for multiple instance learning (MIL) arising from a specific cl…