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MAQA: A Quantum Framework for Supervised Learning
The Multiple Aggregator Quantum Algorithm (MAQA) is a quantum framework that can reproduce the output of a plethora of classical supervised machine learning algorithms using... -
Learning without Forgetting
The dataset used in the paper is a set of shared weights across all tasks. -
Towards Efficient Representation Identification in Supervised Learning
The authors used a dataset for supervised learning where latent factors cause the labels. -
Simple dataset for supervised learning
The dataset used in this paper is a collection of samples for training a supervised learning algorithm. The samples are drawn from a parametric model and are used to evaluate... -
Differentiable Triage
The dataset used in the paper is a synthetic dataset for supervised learning under algorithmic triage. -
Broadband DOA Estimation Using Convolutional Neural Networks Trained with Noi...
A convolution neural network (CNN) based classification method for broadband DOA estimation is proposed, where the phase com-ponent of the short-time Fourier transform... -
Diffusion Boosted Trees
Combining the merits of both denoising diffusion probabilistic models and gradient boosting, the diffusion boosting paradigm is introduced for tackling supervised learning...
