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08/29/2023
Improving Neural Ranking Models with Traditional IR Methods
Neural ranking methods based on large transformer models have recently g...
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08/07/2023
A Cross-Domain Evaluation of Approaches for Causal Knowledge Extraction
Causal knowledge extraction is the task of extracting relevant causes an...
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05/31/2023
Deception by Omission: Using Adversarial Missingness to Poison Causal Structure Learning
Inference of causal structures from observational data is a key componen...
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04/20/2023
Word Sense Induction with Knowledge Distillation from BERT
Pre-trained contextual language models are ubiquitously employed for lan...
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02/28/2022
Anti-Malware Sandbox Games
We develop a game theoretic model of malware protection using the state-...
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02/26/2022
Missing Value Knockoffs
One limitation of the most statistical/machine learning-based variable s...
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07/08/2021
Output Randomization: A Novel Defense for both White-box and Black-box Adversarial Models
Adversarial examples pose a threat to deep neural network models in a va...
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11/14/2020
Patient-Specific Seizure Prediction Using Single Seizure Electroencephalography Recording
Electroencephalogram (EEG) is a prominent way to measure the brain activ...
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11/06/2020
Towards Obfuscated Malware Detection for Low Powered IoT Devices
With the increased deployment of IoT and edge devices into commercial an...
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11/06/2020
A survey on practical adversarial examples for malware classifiers
Machine learning based solutions have been very helpful in solving probl...
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07/27/2020
Image-driven discriminative and generative machine learning algorithms for establishing microstructure-processing relationships
We investigate methods of microstructure representation for the purpose ...
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06/13/2019
An image-driven machine learning approach to kinetic modeling of a discontinuous precipitation reaction
Micrograph quantification is an essential component of several materials...
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05/23/2019
Deep density ratio estimation for change point detection
In this work, we propose new objective functions to train deep neural ne...
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05/23/2019
Thwarting finite difference adversarial attacks with output randomization
Adversarial examples pose a threat to deep neural network models in a va...
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04/09/2019
Short Paper: Creating Adversarial Malware Examples using Code Insertion
There has been an increased interest in the application of convolutional...
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02/25/2019
Quantifying error contributions of computational steps, algorithms and hyperparameter choices in image classification pipelines
Data science relies on pipelines that are organized in the form of inter...
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02/21/2019
Quantifying contribution and propagation of error from computational steps, algorithms and hyperparameter choices in image classification pipelines
Data science relies on pipelines that are organized in the form of inter...
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05/29/2018
