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07/20/2022
Multigraph Topology Design for Cross-Silo Federated Learning
Cross-silo federated learning utilizes a few hundred reliable data silos...
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06/04/2022
Stochastic Multiple Target Sampling Gradient Descent
Sampling from an unnormalized target distribution is an essential proble...
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02/07/2022
Distributionally Robust Fair Principal Components via Geodesic Descents
Principal component analysis is a simple yet useful dimensionality reduc...
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11/27/2021
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources
Domain adaptation (DA) benefits from the rigorous theoretical works that...
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10/18/2021
Exploiting Domain-Specific Features to Enhance Domain Generalization
Domain Generalization (DG) aims to train a model, from multiple observed...
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06/14/2021
KL Guided Domain Adaptation
Domain adaptation is an important problem and often needed for real-worl...
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02/09/2021
Domain Invariant Representation Learning with Domain Density Transformations
Domain generalization refers to the problem where we aim to train a mode...
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12/21/2020
Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior
Choosing a proper set of kernel functions is an important problem in lea...
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04/26/2019
Bayesian Generative Active Deep Learning
Deep learning models have demonstrated outstanding performance in severa...
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04/18/2019
A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning
We propose a method that substantially improves the efficiency of deep d...
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10/29/2017