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07/08/2022
Big Learning: A Universal Machine Learning Paradigm?
Recent breakthroughs based on big/foundation models reveal a vague avenu...
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07/13/2020
Bridging Maximum Likelihood and Adversarial Learning via α-Divergence
Maximum likelihood (ML) and adversarial learning are two popular approac...
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06/16/2020
GO Hessian for Expectation-Based Objectives
An unbiased low-variance gradient estimator, termed GO gradient, was pro...
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06/13/2020
GAN Memory with No Forgetting
Seeking to address the fundamental issue of memory in lifelong learning,...
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02/26/2020
On Leveraging Pretrained GANs for Limited-Data Generation
Recent work has shown GANs can generate highly realistic images that are...
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01/17/2019
GO Gradient for Expectation-Based Objectives
Within many machine learning algorithms, a fundamental problem concerns ...
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06/06/2017
Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC
It is challenging to develop stochastic gradient based scalable inferenc...
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12/09/2015
Gamma Belief Networks
To infer multilayer deep representations of high-dimensional discrete an...
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11/06/2015
