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12/22/2020
APIK: Active Physics-Informed Kriging Model with Partial Differential Equations
Kriging (or Gaussian process regression) is a popular machine learning m...
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11/17/2019
A hierarchical expected improvement method for Bayesian optimization
Expected improvement (EI) is one of the most popular Bayesian optimizati...
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12/28/2018
On Computation and Generalization of GANs with Spectrum Control
Generative Adversarial Networks (GANs), though powerful, is hard to trai...
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11/03/2018
Learning to Defense by Learning to Attack
Adversarial training provides a principled approach for training robust ...
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06/13/2018
On Landscape of Lagrangian Functions and Stochastic Search for Constrained Nonconvex Optimization
We study constrained nonconvex optimization problems in machine learning...
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02/14/2018
Toward Deeper Understanding of Nonconvex Stochastic Optimization with Momentum using Diffusion Approximations
Momentum Stochastic Gradient Descent (MSGD) algorithm has been widely ap...
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02/27/2017