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Work3

Resource type

Dissertation3

Creator

Bahaadini Beigy Zarandi, Sara1
Dutta, Abhratanu1
Shan, Liren1

Keyword

Clustering[remove]3
Adversarial Learning1
Decision Tree1
Dimensionality Reduction1
Discriminative1
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Subject

Computer science[remove]3

Language

en3

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Discriminative Dimensionality Reduction using Deep Neural Networks

Description:

Deep neural networks have shown impressive performance for many applications. In this dissertation, leveraging the capabilities of neural networks for modeling the non-linearity exists in the data, we propose several models that can project data into a low dimensional, discriminative, and smooth manifold. The suggested models can transfer knowledge from...

Keyword:

Discriminative, Clustering, LIGO, and Dimensionality Reduction

Subject:

Computer science

Creator:

Bahaadini Beigy Zarandi, Sara

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

02/12/2020

Date Created:

2019-01-01

Resource Type:

Dissertation

Alternate Identifier:

http://dissertations.umi.com/northwestern:14850 and etdadmin_upload_686625
Learning under Adversarial Resilience

Description:

In this thesis we study two problems, one in unsupervised learning - k-means clustering and the other in a supervised learning setting with the presence of adversarial perturbations. We do a beyond-worst case style analysis and show that in either case instances that are resilient to adversarial perturbations are also...

Keyword:

Clustering, Margin Conditions, and Adversarial Learning

Subject:

Computer science

Creator:

Dutta, Abhratanu

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

02/01/2021

Date Created:

2020-01-01

Resource Type:

Dissertation

Alternate Identifier:

http://dissertations.umi.com/northwestern:15301 and etdadmin_upload_765296
Approximation Algorithms for Explainable Clustering

Description:

Clustering is a fundamental task in unsupervised learning, which aims to partition the data set into several clusters. It is widely used for data mining, image segmentation, and natural language processing. One of the most popular clustering methods is centroid-based clustering, including k-medians and k-means clustering. k-medians and k-means clustering...

Keyword:

Decision Tree, Clustering, Explainability, and k-means

Subject:

Computer science

Creator:

Shan, Liren

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

08/23/2023

Date Created:

2023-01-01

Resource Type:

Dissertation

Alternate Identifier:

http://dissertations.umi.com/northwestern:16717 and etdadmin_upload_1012370

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