369 citations · 1.8k across the 93 of their papers we have counts for
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Quantum-Inspired Machine Learning: a Survey
Larry Huynh, Jin Hong, Ajmal Mian +3
Quantum-inspired Machine Learning (QiML) is a burgeoning field, receiving global attention from researchers for its potential to leverage principles of quantum mechanics within cla…
Q-Cogni: An Integrated Causal Reinforcement Learning Framework
Cris Cunha, Wei Liu, Tim French +1
We present Q-Cogni, an algorithmically integrated causal reinforcement learning framework that redesigns Q-Learning with an autonomous causal structure discovery method to improve…
Fast Parallel Bayesian Network Structure Learning
Jiantong Jiang, Zeyi Wen, Ajmal Mian
Bayesian networks (BNs) are a widely used graphical model in machine learning for representing knowledge with uncertainty. The mainstream BN structure learning methods require perf…
Bi-CLKT: Bi-Graph Contrastive Learning based Knowledge Tracing
Xiangyu Song, Jianxin Li, Qi Lei +3
The goal of Knowledge Tracing (KT) is to estimate how well students have mastered a concept based on their historical learning of related exercises. The benefit of knowledge tracin…
Orthogonal Deep Models As Defense Against Black-Box Attacks
Mohammad A. A. K. Jalwana, Naveed Akhtar, Mohammed Bennamoun +1
Deep learning has demonstrated state-of-the-art performance for a variety of challenging computer vision tasks. On one hand, this has enabled deep visual models to pave the way for…