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05/29/2023
Robust Lipschitz Bandits to Adversarial Corruptions
Lipschitz bandit is a variant of stochastic bandits that deals with a co...
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02/18/2023
Online Continuous Hyperparameter Optimization for Contextual Bandits
In stochastic contextual bandit problems, an agent sequentially makes ac...
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11/18/2021
A Review of Adversarial Attack and Defense for Classification Methods
Despite the efficiency and scalability of machine learning systems, rece...
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05/18/2021
Detecting Adversarial Examples with Bayesian Neural Network
In this paper, we propose a new framework to detect adversarial examples...
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01/27/2021
Change point detection and image segmentation for time series of astrophysical images
Many astrophysical phenomena are time-varying, in the sense that their i...
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04/08/2020
Estimating Fiber Orientation Distribution through Blockwise Adaptive Thresholding with Application to HCP Young Adults Data
Due to recent technological advances, large brain imaging data sets can ...
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11/14/2019
Uncertainty Quantification in Ensembles of Honest Regression Trees using Generalized Fiducial Inference
Due to their accuracies, methods based on ensembles of regression trees ...
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08/04/2019
Measuring the Algorithmic Convergence of Randomized Ensembles: The Regression Setting
When randomized ensemble methods such as bagging and random forests are ...
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11/29/2018
Segmenting Dynamic Network Data
Networks and graphs arise naturally in many complex systems, often exhib...
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11/19/2018
Optimal Transport Classifier: Defending Against Adversarial Attacks by Regularized Deep Embedding
Recent studies have demonstrated the vulnerability of deep convolutional...
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11/04/2018
Block-wise Partitioning for Extreme Multi-label Classification
Extreme multi-label classification aims to learn a classifier that annot...
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09/03/2018
Network estimation via graphon with node features
Estimating the probabilities of linkages in a network has gained increas...
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05/18/2018
Method G: Uncertainty Quantification for Distributed Data Problems using Generalized Fiducial Inference
It is not unusual for a data analyst to encounter data sets distributed ...
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03/01/2015
