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Found 4 papers, 2 papers with code
A Modular End-to-End Multimodal Learning Method for Structured and Unstructured Data
Multimodal learning is a rapidly growing research field that has revolutionized multitasking and generative modeling in AI.
Do we still need fuzzy classifiers for Small Data in the Era of Big Data?
Our findings show that, although slightly inferior, Big Data classifiers are gradually catching up with state-of-the-art classifiers for Small data, suggesting that a unified learning algorithm for Big and Small Data might be possible.
On the usage of the probability integral transform to reduce the complexity of multi-way fuzzy decision trees in Big Data classification problems
We present a new distributed fuzzy partitioning method to reduce the complexity of multi-way fuzzy decision trees in Big Data classification problems.
CFM-BD: a distributed rule induction algorithm for building Compact Fuzzy Models in Big Data classification problems
However, when it comes to Big Data classification problems, fuzzy rule-based classifiers have not been able to maintain the good trade-off between accuracy and interpretability that has characterized these techniques in non-Big Data environments.
