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07/25/2023
Exploring the Sharpened Cosine Similarity
Convolutional layers have long served as the primary workhorse for image...
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05/31/2023
Recasting Self-Attention with Holographic Reduced Representations
In recent years, self-attention has become the dominant paradigm for seq...
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01/15/2023
A Coreset Learning Reality Check
Subsampling algorithms are a natural approach to reduce data size before...
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12/05/2022
Efficient Malware Analysis Using Metric Embeddings
In this paper, we explore the use of metric learning to embed Windows PE...
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11/23/2022
Lempel-Ziv Networks
Sequence processing has long been a central area of machine learning res...
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06/13/2022
Deploying Convolutional Networks on Untrusted Platforms Using 2D Holographic Reduced Representations
Due to the computational cost of running inference for a neural network,...
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06/07/2022
Marvolo: Programmatic Data Augmentation for Practical ML-Driven Malware Detection
Data augmentation has been rare in the cyber security domain due to tech...
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02/28/2022
Proceedings of the Artificial Intelligence for Cyber Security (AICS) Workshop at AAAI 2022
The workshop will focus on the application of AI to problems in cyber se...
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02/18/2022
Out of Distribution Data Detection Using Dropout Bayesian Neural Networks
We explore the utility of information contained within a dropout based B...
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09/05/2021
Learning with Holographic Reduced Representations
Holographic Reduced Representations (HRR) are a method for performing sy...
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08/09/2021
Leveraging Uncertainty for Improved Static Malware Detection Under Extreme False Positive Constraints
The detection of malware is a critical task for the protection of comput...
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10/22/2020
Getting Passive Aggressive About False Positives: Patching Deployed Malware Detectors
False positives (FPs) have been an issue of extreme importance for anti-...
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09/06/2020