Search Results for author: Ian Davidson

Found 20 papers, 7 papers with code

Deep Fair Discriminative Clustering

no code implementations28 May 2021 Hongjing Zhang, Ian Davidson

Deep clustering has the potential to learn a strong representation and hence better clustering performance compared to traditional clustering methods such as $k$-means and spectral clustering.

Deep Clustering Fairness +1

Deep Descriptive Clustering

no code implementations24 May 2021 Hongjing Zhang, Ian Davidson

However, much modern machine learning focuses on complex data such as images, text, and graphs where deep learning is used but the raw features of data are not interpretable.

Representation Learning

A Framework for Deep Constrained Clustering

1 code implementation7 Jan 2021 Hongjing Zhang, Tianyang Zhan, Sugato Basu, Ian Davidson

A fundamental strength of deep learning is its flexibility, and here we explore a deep learning framework for constrained clustering and in particular explore how it can extend the field of constrained clustering.

Towards Fair Deep Anomaly Detection

no code implementations29 Dec 2020 Hongjing Zhang, Ian Davidson

Anomaly detection aims to find instances that are considered unusual and is a fundamental problem of data science.

Anomaly Detection Fairness

Block Model Guided Unsupervised Feature Selection

1 code implementation5 Jul 2020 Zilong Bai, Hoa Nguyen, Ian Davidson

Existing efforts for unsupervised feature selection on attributed networks have explored either directly regenerating the links by solving for $f$ such that $f(\mathbf{y}_i,\mathbf{y}_j) \approx \mathbf{A}_{i, j}$ or finding community structure in $\mathbf{A}$ and using the features in $\mathbf{Y}$ to predict these communities.

Efficient Algorithms for Generating Provably Near-Optimal Cluster Descriptors for Explainability

1 code implementation6 Feb 2020 Prathyush Sambaturu, Aparna Gupta, Ian Davidson, S. S. Ravi, Anil Vullikanti, Andrew Warren

Improving the explainability of the results from machine learning methods has become an important research goal.

A Graph-Based Approach for Active Learning in Regression

no code implementations30 Jan 2020 Hongjing Zhang, S. S. Ravi, Ian Davidson

Most existing active learning for regression methods use the regression function learned at each active learning iteration to select the next informative point to query.

Active Learning

Coverage-based Outlier Explanation

no code implementations6 Nov 2019 Yue Wu, Leman Akoglu, Ian Davidson

Existing algorithms are primarily focused on detection, that is the identification of outliers in a given dataset.

Outlier Detection

A Framework for Deep Constrained Clustering -- Algorithms and Advances

1 code implementation29 Jan 2019 Hongjing Zhang, Sugato Basu, Ian Davidson

The area of constrained clustering has been extensively explored by researchers and used by practitioners.

Towards Fair Deep Clustering With Multi-State Protected Variables

no code implementations29 Jan 2019 Bokun Wang, Ian Davidson

Fair clustering under the disparate impact doctrine requires that population of each protected group should be approximately equal in every cluster.

Deep Clustering Fairness

The Cluster Description Problem - Complexity Results, Formulations and Approximations

no code implementations NeurIPS 2018 Ian Davidson, Antoine Gourru, S Ravi

Since the descriptors/tags were not given to the clustering method, this is not a semi-supervised learning situation.

On The Equivalence of Tries and Dendrograms - Efficient Hierarchical Clustering of Traffic Data

no code implementations12 Oct 2018 Chia-Tung Kuo, Ian Davidson

The widespread use of GPS-enabled devices generates voluminous and continuous amounts of traffic data but analyzing such data for interpretable and actionable insights poses challenges.

Extreme Learning to Rank via Low Rank Assumption

no code implementations ICML 2018 Minhao Cheng, Ian Davidson, Cho-Jui Hsieh

We consider the setting where we wish to perform ranking for hundreds of thousands of users which is common in recommender systems and web search ranking.

Learning-To-Rank Recommendation Systems

Probabilistic Formulations of Regression with Mixed Guidance

1 code implementation1 Apr 2018 Aubrey Gress, Ian Davidson

Regression problems assume every instance is annotated (labeled) with a real value, a form of annotation we call \emph{strong guidance}.

Transfer Regression via Pairwise Similarity Regularization

no code implementations23 Dec 2017 Aubrey Gress, Ian Davidson

Transfer learning methods address the situation where little labeled training data from the "target" problem exists, but much training data from a related "source" domain is available.

Transfer Learning

Dense Transformer Networks

1 code implementation24 May 2017 Jun Li, Yongjun Chen, Lei Cai, Ian Davidson, Shuiwang Ji

The proposed dense transformer modules are differentiable, thus the entire network can be trained.

Semantic Segmentation

Some Advances in Role Discovery in Graphs

no code implementations9 Sep 2016 Sean Gilpin, Chia-Tung Kuo, Tina Eliassi-Rad, Ian Davidson

Role discovery in graphs is an emerging area that allows analysis of complex graphs in an intuitive way.

Stochastic Coordinate Coding and Its Application for Drosophila Gene Expression Pattern Annotation

no code implementations30 Jul 2014 Binbin Lin, Qingyang Li, Qian Sun, Ming-Jun Lai, Ian Davidson, Wei Fan, Jieping Ye

The effectiveness of gene expression pattern annotation relies on the quality of feature representation.

On Constrained Spectral Clustering and Its Applications

1 code implementation25 Jan 2012 Xiang Wang, Buyue Qian, Ian Davidson

Furthermore, by inheriting the objective function from spectral clustering and encoding the constraints explicitly, much of the existing analysis of unconstrained spectral clustering techniques remains valid for our formulation.

Transfer Learning

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