148 citations · 177 across the 6 of their papers we have counts for
6 papers
Explaining Adverse Actions in Credit Decisions Using Shapley Decomposition
Vijayan N. Nair, Tianshu Feng, Linwei Hu +3
When a financial institution declines an application for credit, an adverse action (AA) is said to occur. The applicant is then entitled to an explanation for the negative decision…
Distributed Linear Equations over Random Networks
Peng Yi, Jinlong Lei, Yiguang Hong +2
Distributed linear algebraic equation over networks, where nodes hold a part of problem data and cooperatively solve the equation via node-to-node communications, is a basic distri…
A Sequential Set Generation Method for Predicting Set-Valued Outputs
Tian Gao, Jie Chen, Vijil Chenthamarakshan +1
Consider a general machine learning setting where the output is a set of labels or sequences. This output set is unordered and its size varies with the input. Whereas multi-label c…
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…
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…
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…