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10/28/2022
Scalable Spectral Clustering with Group Fairness Constraints
There are synergies of research interests and industrial efforts in mode...
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09/20/2022
Towards Auditing Unsupervised Learning Algorithms and Human Processes For Fairness
Existing work on fairness typically focuses on making known machine lear...
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09/20/2022
Explainable Clustering via Exemplars: Complexity and Efficient Approximation Algorithms
Explainable AI (XAI) is an important developing area but remains relativ...
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05/28/2021
Deep Fair Discriminative Clustering
Deep clustering has the potential to learn a strong representation and h...
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05/24/2021
Deep Descriptive Clustering
Recent work on explainable clustering allows describing clusters when th...
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01/07/2021
A Framework for Deep Constrained Clustering
The area of constrained clustering has been extensively explored by rese...
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12/29/2020
Towards Fair Deep Anomaly Detection
Anomaly detection aims to find instances that are considered unusual and...
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07/05/2020
Block Model Guided Unsupervised Feature Selection
Feature selection is a core area of data mining with a recent innovation...
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02/06/2020
Efficient Algorithms for Generating Provably Near-Optimal Cluster Descriptors for Explainability
Improving the explainability of the results from machine learning method...
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01/30/2020
A Graph-Based Approach for Active Learning in Regression
Active learning aims to reduce labeling efforts by selectively asking hu...
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11/06/2019
Coverage-based Outlier Explanation
Outlier detection is a core task in data mining with a plethora of algor...
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01/29/2019
Deep Constrained Clustering - Algorithms and Advances
The area of constrained clustering has been extensively explored by rese...
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01/29/2019
Towards Fair Deep Clustering With Multi-State Protected Variables
Fair clustering under the disparate impact doctrine requires that popula...
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10/12/2018
On The Equivalence of Tries and Dendrograms - Efficient Hierarchical Clustering of Traffic Data
The widespread use of GPS-enabled devices generates voluminous and conti...
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04/01/2018
Probabilistic Formulations of Regression with Mixed Guidance
Regression problems assume every instance is annotated (labeled) with a ...
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12/23/2017
Transfer Regression via Pairwise Similarity Regularization
Transfer learning methods address the situation where little labeled tra...
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05/24/2017
Dense Transformer Networks
The key idea of current deep learning methods for dense prediction is to...
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09/09/2016
Some Advances in Role Discovery in Graphs
Role discovery in graphs is an emerging area that allows analysis of com...
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01/16/2013
Minimum Message Length Clustering Using Gibbs Sampling
The K-Mean and EM algorithms are popular in clustering and mixture model...
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02/04/2012
A Reconstruction Error Formulation for Semi-Supervised Multi-task and Multi-view Learning
A significant challenge to make learning techniques more suitable for ge...
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01/25/2012