148 citations · 177 across the 6 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
cs.LG2018★ 2 cited
Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability
Lingfei Wu, Ian E. H. Yen, Jie Chen +1
Kernel method has been developed as one of the standard approaches for nonlinear learning, which however, does not scale to large data set due to its quadratic complexity in the nu…
stat.ML2018★ 148 cited
Learning ReLU Networks on Linearly Separable Data: Algorithm, Optimality, and Generalization
Gang Wang, Georgios B. Giannakis, Jie Chen
Neural networks with REctified Linear Unit (ReLU) activation functions (a.k.a. ReLU networks) have achieved great empirical success in various domains. Nonetheless, existing result…
cs.LG2018★ 26 cited
Stochastic Gradient Descent with Biased but Consistent Gradient Estimators
Jie Chen, Ronny Luss
Stochastic gradient descent (SGD), which dates back to the 1950s, is one of the most popular and effective approaches for performing stochastic optimization. Research on SGD resurg…