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08/02/2022
Do I really need all this work to find vulnerabilities? An empirical case study comparing vulnerability detection techniques on a Java application
CONTEXT: Applying vulnerability detection techniques is one of many task...
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05/02/2022
Reducing the Cost of Training Security Classifier (via Optimized Semi-Supervised Learning)
Background: Most of the existing machine learning models for security ta...
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03/22/2022
Dazzle: Using Optimized Generative Adversarial Networks to Address Security Data Class Imbalance Issue
Background: Machine learning techniques have been widely used and demons...
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06/14/2021
Temporal Predictive Coding For Model-Based Planning In Latent Space
High-dimensional observations are a major challenge in the application o...
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03/08/2021
Structuring a Comprehensive Software Security Course Around the OWASP Application Security Verification Standard
Lack of security expertise among software practitioners is a problem wit...
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11/23/2020
Omni: Automated Ensemble with Unexpected Models against Adversarial Evasion Attack
BACKGROUND: Machine learning-based security detection models have become...
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06/12/2020
Predicting Project Health for Open Source Projects (using the DECART Hyperparameter Optimizer)
Software developed on public platforms are a source of data that can be ...
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03/02/2020
Predictive Coding for Locally-Linear Control
High-dimensional observations and unknown dynamics are major challenges ...
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12/09/2019
Sequential Model Optimization for Software Process Control
Many methods have been proposed to estimate how much effort is required ...
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11/04/2019
Improved Recognition of Security Bugs via Dual Hyperparameter Optimization
Background: Security bugs need to be handled by small groups of engineer...
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10/26/2019
Fair Generative Modeling via Weak Supervision
Real-world datasets are often biased with respect to key demographic fac...
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10/22/2019
Weakly Supervised Disentanglement with Guarantees
Learning disentangled representations that correspond to factors of vari...
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09/04/2019
Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control
Many real-world sequential decision-making problems can be formulated as...
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05/30/2019
AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows
Given unpaired data from multiple domains, a key challenge is to efficie...
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05/16/2019
Better Security Bug Report Classification via Hyperparameter Optimization
When security bugs are detected, they should be (a) discussed privately ...
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02/27/2019
Training Variational Autoencoders with Buffered Stochastic Variational Inference
The recognition network in deep latent variable models such as variation...
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05/23/2018
Amortized Inference Regularization
The variational autoencoder (VAE) is a popular model for density estimat...
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05/21/2018
Generative Adversarial Examples
Adversarial examples are typically constructed by perturbing an existing...
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02/23/2018
A DIRT-T Approach to Unsupervised Domain Adaptation
Domain adaptation refers to the problem of leveraging labeled data in a ...
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05/03/2014
