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06/09/2022
A Learning-Theoretic Framework for Certified Auditing of Machine Learning Models
Responsible use of machine learning requires that models be audited for ...
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06/09/2022
There is no Accuracy-Interpretability Tradeoff in Reinforcement Learning for Mazes
Interpretability is an essential building block for trustworthiness in r...
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02/01/2022
Framework for Evaluating Faithfulness of Local Explanations
We study the faithfulness of an explanation system to the underlying pre...
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02/14/2021
Connecting Interpretability and Robustness in Decision Trees through Separation
Recent research has recognized interpretability and robustness as essent...
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02/09/2021
Bounded Memory Active Learning through Enriched Queries
The explosive growth of easily-accessible unlabeled data has lead to gro...
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02/08/2021
A Constant Approximation Algorithm for Sequential No-Substitution k-Median Clustering under a Random Arrival Order
We study k-median clustering under the sequential no-substitution settin...
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12/28/2020
No-substitution k-means Clustering with Adversarial Order
We investigate k-means clustering in the online no-substitution setting ...
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06/03/2020
ExKMC: Expanding Explainable k-Means Clustering
Despite the popularity of explainable AI, there is limited work on effec...
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02/28/2020
Explainable k-Means and k-Medians Clustering
Clustering is a popular form of unsupervised learning for geometric data...
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02/08/2020
Towards a combinatorial characterization of bounded memory learning
Combinatorial dimensions play an important role in the theory of machine...
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08/09/2019
Unexpected Effects of Online K-means Clustering
In this paper we study k-means clustering in the online setting. In the ...
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04/09/2019
Novel Uncertainty Framework for Deep Learning Ensembles
Deep neural networks have become the default choice for many of the mach...
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12/10/2017
A General Memory-Bounded Learning Algorithm
In an era of big data there is a growing need for memory-bounded learnin...
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09/18/2016
