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Kernel Methods and Multi-layer Perceptrons Learn Linear Models in High Dimensions

Empirical observation of high dimensional phenomena, such as the double ...

Near-Optimal Sparse Allreduce for Distributed Deep Learning

Communication overhead is one of the major obstacles to train large deep...

GAN-based Matrix Factorization for Recommender Systems

Proposed in 2014, Generative Adversarial Networks (GAN) initiated a fres...

Investigating underdiagnosis of AI algorithms in the presence of multiple sources of dataset bias

Deep learning models have shown great potential for image-based diagnosi...

Direct Mutation and Crossover in Genetic Algorithms Applied to Reinforcement Learning Tasks

Neuroevolution has recently been shown to be quite competitive in reinfo...

Priors, Hierarchy, and Information Asymmetry for Skill Transfer in Reinforcement Learning

The ability to discover behaviours from past experience and transfer the...