1 citations · 1 across the 9 of their papers we have counts for
7 papers · 1 filter
ColdDDI: Evaluating Knowledge Utilization in Cold-Start Drug-Drug Interaction Prediction
Jiheng Liang, Chen Zhao, Di Wu +4
Cold-start drug-drug interaction (DDI) prediction tests whether models can identify clinically significant interactions for drugs without training-time interaction history. Existin…
Reducing Learner Redundancy in Boosting via Residual Orthogonalization
Ye Su, Jipeng Guo, Xin Xu +4
While sequential residual fitting is the bedrock of standard boosting frameworks, it inherently breeds learner redundancy by repeatedly revisiting correlated error components. To a…
FLFL: Federated Latent Factor Learning for Private Recovery of Spatio-Temporal Signals
Chengjun Yu, Di Wu, Yi He +1
Wireless sensor network (WSNs) stands out as a burgeoning and promising domain in intelligent sensing. Owing to various factors such as sudden sensor malfunctions or deliberate shu…
DT-GOL: Dual-Track Geometric Online Learning in Nonstationary Environment with Label Delay
Yulin Wang, Yi He, Dianlong You +1
Online learning is crucial for handling complex data streams in big data applications. Recent research has begun to focus on dynamic scenarios, i.e., non-stationary environments. H…
Extension OL-MDISF: Online Learning from Mix-Typed, Drifted, and Incomplete Streaming Features
Shengda Zhuo, Di Wu, Yi He +2
Online learning, where feature spaces can change over time, offers a flexible learning paradigm that has attracted considerable attention. However, it still faces three significant…
End-to-end Graph Learning Approach for Cognitive Diagnosis of Student Tutorial
Fulai Yang, Di Wu, Yi He +2
Cognitive diagnosis (CD) utilizes students' existing studying records to estimate their mastery of unknown knowledge concepts, which is vital for evaluating their learning abilitie…
Fairness-Aware Streaming Feature Selection with Causal Graphs
Leizhen Zhang, Lusi Li, Di Wu +2
Its crux lies in the optimization of a tradeoff between accuracy and fairness of resultant models on the selected feature subset. The technical challenge of our setting is twofold:…