This dissertation focuses on the development of machine learning algorithms for spiking neural networks, with an emphasis on local three-factor learning rules that are in keeping with the constraints imposed by current neuromorphic hardware. Spiking neural networks (SNNs) are an alternative to artificial neural networks (ANNs) that follow a similar graphical structure but use a processing ... WebJun 19, 2024 · This learning method–called e-prop–approaches the performance of backpropagation through time (BPTT), the best-known method for training recurrent neural networks in machine learning and suggests a method for powerful on-chip learning in energy-efficient spike-based hardware for artificial intelligence. Expand. 233. PDF.
Local learning algorithms for stochastic spiking …
WebNov 2, 2024 · Authors: Bleema Rosenfeld, Osvaldo Simeone, Bipin Rajendran. Download PDF Abstract: Neuromorphic data carries information in spatio-temporal patterns encoded by spikes. Accordingly, a central problem in neuromorphic computing is training spiking neural networks (SNNs) to reproduce spatio-temporal spiking patterns in response to … WebJan 1, 2014 · Melkersson-Rosenthal syndrome (MRS) is a rare, non-caseating chronic granulamatous neurocutaneous disease. MRS is frequently seen at the second or third … nick wright kyrie irving
Bleema Rosenfeld - New York City Metropolitan Area
WebRosenfeld, Bleema: View Online: njit-etd2024-025 (xiv, 98 pages ~ 2.7 MB pdf) Department: Department of Electrical and Computer Engineering: Degree: Doctor of Philosophy: ... This dissertation focuses on the development of machine learning algorithms for spiking neural networks, with an emphasis on local three-factor learning … WebLocal Learning Algorithms For Stochastic Spiking Neural Networks, Bleema Rosenfeld Dissertations This dissertation focuses on the development of machine learning … now feat. luh geeky