2 papers
cs.NE2021
Information Bottleneck-Based Hebbian Learning Rule Naturally Ties Working Memory and Synaptic Updates
Kyle Daruwalla, Mikko Lipasti
Artificial neural networks have successfully tackled a large variety of problems by training extremely deep networks via back-propagation. A direct application of back-propagation…
cs.LG2021
Accelerating Deep Learning with Dynamic Data Pruning
Ravi S Raju, Kyle Daruwalla, Mikko Lipasti
Deep learning's success has been attributed to the training of large, overparameterized models on massive amounts of data. As this trend continues, model training has become prohib…