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Found 5 papers, 4 papers with code
Enhancing Cognitive Diagnosis using Un-interacted Exercises: A Collaboration-aware Mixed Sampling Approach
Finally, we demonstrate the effectiveness and interpretability of our framework through comprehensive experiments on real-world datasets.
Evolutionary Neural Architecture Search for Transformer in Knowledge Tracing
Knowledge tracing (KT) aims to trace students' knowledge states by predicting whether students answer correctly on exercises.
EQ-Net: Elastic Quantization Neural Networks
In this paper, we explore a one-shot network quantization regime, named Elastic Quantization Neural Networks (EQ-Net), which aims to train a robust weight-sharing quantization supernet.
Designing Novel Cognitive Diagnosis Models via Evolutionary Multi-Objective Neural Architecture Search
Then, we propose multi-objective genetic programming (MOGP) to explore the NAS task's search space by maximizing model performance and interpretability.
Accelerating Evolutionary Neural Architecture Search via Multi-Fidelity Evaluation
Evolutionary neural architecture search (ENAS) has recently received increasing attention by effectively finding high-quality neural architectures, which however consumes high computational cost by training the architecture encoded by each individual for complete epochs in individual evaluation.
