• Interpretable Data Phenotyping for Healthcare via Unsupervised Learning 

  Allen, Christine

  Healthcare applications of machine learning tend toward greater requirements for model transparency than most applications. Yet the often high dimensionality of the data presents a significant impediment to meeting this ...

• Management and Prediction of Moving Objects Under Location Uncertainty 

  Islam, Abdullah

  In spatio-temporal systems, precise location data is desirable but often not available due to obfuscation, privacy, hardware inaccuracies, and other factors. Progress has been made in research which deals with the uncertainty ...

• Electromyography (EMG) Based Finger Movement Detection 

  jowkar, ghazaleh

  One fundamental component of much modern human-machine interaction (HCI) devices is Myoelectric control systems which is a system that receives the Electromyography(EMG) signal originated from muscle movement. Much research ...

• Using biomedical data to identify genetic variants that drive drug responses in Acute Myeloid Leukemia 

  Kauer, Nicole Maryellen

  Acute Myeloid Leukemia (AML) is a heterogeneous cancer of the blood that progresses quickly, with approximately 10,000 AML related deaths reported annually in the United States. Patients with AML tend to have genetic ...

• Secure Training of Random Forest Classifiers over Continuous Data 

  Shen, Jianwei

  Existing Secure Multi-Party Computation (MPC) protocols for privacy-preserving training of decision trees over distributed data assume that the attributes are categorical. In real-life applications, attributes are often ...

• Improved Signcryption and Broadcast Signcryption with Detachable Signatures 

  Elliott, Edgar James

  With the ever-increasing amount of sensitive information being sent and received over the internet, the importance of fast secure cryptographic schemes will only continue to grow. In this paper we examine ...

• Hardening DGA Classifiers Using Adversarial Attacks and IVAP 

  Grumer, Charles Arthur

  Domain generation algorithms (DGAs) are utilized by botmasters as a way to connect malware-infected machines with the botmaster's command-and-control center (C\&C). Such a connection allows the botmaster to send and receive ...

• Street Parking Sign Detection, Recognition and Trust System 

  Jiang, Zhongyu

  Parking is one of the major problems in autonomous driving. Although cars can park in a parking spot automatically now, they can't find where they can park. In this thesis, we propose a novel street parking sign detection ...

• Authority, Expertise, and Active Learning in the CS Classroom 

  Kabu, Shubham

  Active learning is a teaching practice that involves students in the learning process as more than mere passive listeners, and there is ample evidence of its benefits. Learning is placed more in the hands of the students ...

• Hardening Inline DGA Classifiers Against Adversarial Attacks 

  Sivaguru, Raaghavi

  Domain Generation Algorithms (DGAs) are widely used by cybercriminals to generate domain names on-the-go for C&C (command-and-control) purposes of establishing communication with the bots and instructing them to perform ...

• Privacy-Preserving Machine Learning Applications 

  Todoki, Ariel Akemi

  Machine learning has its many applications in different areas of interest that involves huge amounts of data in order to learn how to recognize, predict, and classify. One such area is in text classification where a private ...

• Predicting German Compound Words Using a Recurrent Neural Network 

  Callow, Edward Joseph

  Accurate classification, morphological analysis and translation of compound words is a problem that has not been satisfactorily solved in many of its aspects. For example, as of the date of this paper, Google translates ...

• Toward an Accurate Acoustic Localization System 

  Fotouhi, Mohammabagher

  In this dissertation, we propose an accurate and fast multi-pair simultaneous localization systems for smartphones without the need of infrastructure support. The system is a purely software-based solution (an App), which ...

• Investigation of Extending Feature Selection Algorithms to Explicit Feature Selection in Kernel Space 

  LI, QIAOZHI

  Feature selection methods play important roles in the area of machine learning. Being a part of prepossessing, the technology of feature selection can select useful information from raw data. A good feature selection method ...

• Reconfigurable Convolution Implementation for CNNs in FPGAs 

  Bannon, Jesse Michael

  Deep learning continues to be the revolutionary method used in pattern recognition applications including image, video, and speech processing. Convolutional Neural Networks (CNNs) in particular have outperformed every ...

• Evaluating the fairness in the performance of machine learning methods 

  Yuan, Ming

  Machine learning plays an increasingly important role in our lives, tackling both prevalent and specialized but high-risk problems. Motivated by legislation, responsibility to ensure transparency and accountability of ...

• SMPCEngine: An N-Party Implementation of the Secure Multiparty Private Computation Protocol 

  McKinney, Nicholas

  In this thesis, we implement a framework for secure multiparty computation. Our framework works in the commodity-based model, where the players running the distributed computation receive pre-distributed data from a trusted ...

• Automatic Detection of Providers with Excess Healthcare Spending 

  Liu, Jiacheng

  This thesis aims to develop techniques to help large hospital systems to detect providers with excess spending. Identifying fraud, waste, and abuse resulting in super uous expendi- tures associated with care delivery is ...

• Performance Analysis of Real Time Streaming Systems for Smart Buildings 

  Stuart, Kim

  The Internet of Things (IoT) extends traditional cyber-physical systems by linking sensor-based edge devices to additional network-accessible services and resources. In most current IoT deployments, sensor data is streamed ...

• Integrating external biological knowledge in the construction of regulatory networks from LINCS data 

  Liang, Xiao

  The inference of gene regulatory networks is of great interest and has various applications. The recent advances in high-throughout biological data collection have facilitated the construction and understanding of gene ...

View more