13 citations · 60 across the 14 of their papers we have counts for
15 papers
eGAN: Unsupervised approach to class imbalance using transfer learning
Ademola Okerinde, Lior Shamir, William Hsu +2
Class imbalance is an inherent problem in many machine learning classification tasks. This often leads to trained models that are unusable for any practical purpose. In this study…
AdeNet: Deep learning architecture that identifies damaged electrical insulators in power lines
Ademola Okerinde, Lior Shamir, William Hsu +1
Ceramic insulators are important to electronic systems, designed and installed to protect humans from the danger of high voltage electric current. However, insulators are not immor…
Feature Selection for Learning to Predict Outcomes of Compute Cluster Jobs with Application to Decision Support
Adedolapo Okanlawon, Huichen Yang, Avishek Bose +3
We present a machine learning framework and a new test bed for data mining from the Slurm Workload Manager for high-performance computing (HPC) clusters. The focus was to find a me…
Vision-Based Layout Detection from Scientific Literature using Recurrent Convolutional Neural Networks
Huichen Yang, William H. Hsu
We present an approach for adapting convolutional neural networks for object recognition and classification to scientific literature layout detection (SLLD), a shared subtask of se…
Shape-aware Generative Adversarial Networks for Attribute Transfer
Lei Luo, William Hsu, Shangxian Wang
Generative adversarial networks (GANs) have been successfully applied to transfer visual attributes in many domains, including that of human face images. This success is partly att…
Pipelines for Procedural Information Extraction from Scientific Literature: Towards Recipes using Machine Learning and Data Science
Huichen Yang, Carlos A. Aguirre, Maria F. De La Torre +10
This paper describes a machine learning and data science pipeline for structured information extraction from documents, implemented as a suite of open-source tools and extensions t…
A Novel Approach for Detection and Ranking of Trendy and Emerging Cyber Threat Events in Twitter Streams
Avishek Bose, Vahid Behzadan, Carlos Aguirre +1
We present a new machine learning and text information extraction approach to detection of cyber threat events in Twitter that are novel (previously non-extant) and developing (mar…
Hybridized Threshold Clustering for Massive Data
Jianmei Luo, ChandraVyas Annakula, Aruna Sai Kannamareddy +3
As the size of datasets become massive, many commonly-used clustering algorithms (for example, -means or hierarchical agglomerative clustering (HAC) require prohibitive comp…
Sequential Triggers for Watermarking of Deep Reinforcement Learning Policies
Vahid Behzadan, William Hsu
This paper proposes a novel scheme for the watermarking of Deep Reinforcement Learning (DRL) policies. This scheme provides a mechanism for the integration of a unique identifier w…
Adversarial Exploitation of Policy Imitation
Vahid Behzadan, William Hsu
This paper investigates a class of attacks targeting the confidentiality aspect of security in Deep Reinforcement Learning (DRL) policies. Recent research have established the vuln…
Analysis and Improvement of Adversarial Training in DQN Agents With Adversarially-Guided Exploration (AGE)
Vahid Behzadan, William Hsu
This paper investigates the effectiveness of adversarial training in enhancing the robustness of Deep Q-Network (DQN) policies to state-space perturbations. We first present a form…
RL-Based Method for Benchmarking the Adversarial Resilience and Robustness of Deep Reinforcement Learning Policies
Vahid Behzadan, William Hsu
This paper investigates the resilience and robustness of Deep Reinforcement Learning (DRL) policies to adversarial perturbations in the state space. We first present an approach fo…
Machine Learning for Predictive Analytics of Compute Cluster Jobs
Dan Andresen, William Hsu, Huichen Yang +1
We address the problem of predicting whether sufficient memory and CPU resources have been requested for jobs at submission time. For this purpose, we examine the task of training…
Visualization of Clandestine Labs from Seizure Reports: Thematic Mapping and Data Mining Research Directions
William Hsu, Mohammed Abduljabbar, Ryuichi Osuga +2
The problem of spatiotemporal event visualization based on reports entails subtasks ranging from named entity recognition to relationship extraction and mapping of events. We prese…
KSU KDD: Word Sense Induction by Clustering in Topic Space
Wesam Elshamy, Doina Caragea, William Hsu
We describe our language-independent unsupervised word sense induction system. This system only uses topic features to cluster different word senses in their global context topic s…