We present a general framework for designing efficient algorithms for unsupervised learning problems, such as mixtures of Gaussians and subspace clustering. Our framework is based on a meta algorithm ...

From classrooms to kitchen tables, debates about math education are never far away. Should teachers drill multiplication facts or encourage creative strategies to solve problems? The answer, ...

Spiking Neural Networks (SNNs) are promising for neuromorphic computing due to their biological plausibility and energy efficiency. However, training methods like Backpropagation Through Time (BPTT) ...