Edward Raff

Orcid: 0000-0002-9900-1972

According to our database1, Edward Raff authored at least 119 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Optimizing the Optimal Weighted Average: Efficient Distributed Sparse Classification.
CoRR, 2024

Assemblage: Automatic Binary Dataset Construction for Machine Learning.
CoRR, 2024

REASONS: A benchmark for REtrieval and Automated citationS Of scieNtific Sentences using Public and Proprietary LLMs.
CoRR, 2024

Comprehensive OOD Detection Improvements.
CoRR, 2024

SoK: A Review of Differentially Private Linear Models For High-Dimensional Data.
Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2024

Holographic Global Convolutional Networks for Long-Range Prediction Tasks in Malware Detection.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Semi-Supervised Classification of Malware Families Under Extreme Class Imbalance via Hierarchical Non-Negative Matrix Factorization with Automatic Model Selection.
ACM Trans. Priv. Secur., November, 2023

Towards Generalization in Subitizing with Neuro-Symbolic Loss using Holographic Reduced Representations.
CoRR, 2023

DDxT: Deep Generative Transformer Models for Differential Diagnosis.
CoRR, 2023

Exploring the Sharpened Cosine Similarity.
CoRR, 2023

You Don't Need Robust Machine Learning to Manage Adversarial Attack Risks.
CoRR, 2023

Sparse Private LASSO Logistic Regression.
CoRR, 2023

The Challenge of Differentially Private Screening Rules.
CoRR, 2023

Measuring Equality in Machine Learning Security Defenses.
CoRR, 2023

MOTIF: A Malware Reference Dataset with Ground Truth Family Labels.
Comput. Secur., 2023

Marvolo: Programmatic Data Augmentation for Deep Malware Detection.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

cuSLINK: Single-Linkage Agglomerative Clustering on the GPU.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Scaling Up Differentially Private LASSO Regularized Logistic Regression via Faster Frank-Wolfe Iterations.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Reproducibility in Multiple Instance Learning: A Case For Algorithmic Unit Tests.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Emergent and Predictable Memorization in Large Language Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

LEACE: Perfect linear concept erasure in closed form.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Generative Approach for Image Registration of Visible-Thermal (VT) Cancer Faces.
Proceedings of the Artificial Intelligence Over Infrared Images for Medical Applications (AIIIMA 2023), 2023

Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling.
Proceedings of the International Conference on Machine Learning, 2023

Recasting Self-Attention with Holographic Reduced Representations.
Proceedings of the International Conference on Machine Learning, 2023

Neural Bregman Divergences for Distance Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

When Visible-to-Thermal Facial GAN Beats Conditional Diffusion.
Proceedings of the IEEE International Conference on Image Processing, 2023

Vista Morph - Unsupervised Image Registration of Visible-Thermal Facial Pairs.
Proceedings of the IEEE International Joint Conference on Biometrics, 2023

An Easy Rejection Sampling Baseline via Gradient Refined Proposals.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Does Starting Deep Learning Homework Earlier Improve Grades?
Proceedings of the Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30, 2023

Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech Recognition.
Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security, 2023

Probing the Transition to Dataset-Level Privacy in ML Models Using an Output-Specific and Data-Resolved Privacy Profile.
Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security, 2023

Differentially Private Logistic Regression with Sparse Solutions.
Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security, 2023

AVScan2Vec: Feature Learning on Antivirus Scan Data for Production-Scale Malware Corpora.
Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security, 2023

Small Effect Sizes in Malware Detection? Make Harder Train/Test Splits!
Proceedings of the Conference on Applied Machine Learning in Information Security, 2023

MalDICT: Benchmark Datasets on Malware Behaviors, Platforms, Exploitation, and Packers.
Proceedings of the Conference on Applied Machine Learning in Information Security, 2023

A Siren Song of Open Source Reproducibility, Examples from Machine Learning.
Proceedings of the 2023 ACM Conference on Reproducibility and Replicability, 2023

Does the Market of Citations Reward Reproducible Work?
Proceedings of the 2023 ACM Conference on Reproducibility and Replicability, 2023

BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Crosslingual Generalization through Multitask Finetuning.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

A Coreset Learning Reality Check.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Efficient Malware Analysis Using Metric Embeddings.
CoRR, 2022

Improving Out-of-Distribution Detection via Epistemic Uncertainty Adversarial Training.
CoRR, 2022

Marvolo: Programmatic Data Augmentation for Practical ML-Driven Malware Detection.
CoRR, 2022

A Siren Song of Open Source Reproducibility.
CoRR, 2022

Intelligent Sight and Sound: A Chronic Cancer Pain Dataset.
CoRR, 2022

Artificial Intelligence for Cyber Security (AICS).
CoRR, 2022

Neural Language Models are Effective Plagiarists.
CoRR, 2022

Rank-1 Similarity Matrix Decomposition For Modeling Changes in Antivirus Consensus Through Time.
CoRR, 2022

Continuously Generalized Ordinal Regression for Linear and Deep Models.
Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

A General Framework for Auditing Differentially Private Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

GPU Semiring Primitives for Sparse Neighborhood Methods.
Proceedings of the Fifth Conference on Machine Learning and Systems, 2022

Deploying Convolutional Networks on Untrusted Platforms Using 2D Holographic Reduced Representations.
Proceedings of the International Conference on Machine Learning, 2022

Lempel-Ziv Networks.
Proceedings of the Proceedings on "I Can't Believe It's Not Better!, 2022

VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidance.
Proceedings of the Computer Vision - ECCV 2022, 2022

Fooling MOSS Detection with Pretrained Language Models.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Efficient Malware Analysis Using Metric Embeddings.
Proceedings of the Conference on Applied Machine Learning in Information Security, 2022

Minimizing Compute Costs: When Should We Run More Expensive Malware Analysis?
Proceedings of the Conference on Applied Machine Learning in Information Security, 2022

Out of Distribution Data Detection Using Dropout Bayesian Neural Networks.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Bridging the Gap: Using Deep Acoustic Representations to Learn Grounded Language from Percepts and Raw Speech.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
MOTIF: A Large Malware Reference Dataset with Ground Truth Family Labels.
CoRR, 2021

Leveraging Uncertainty for Improved Static Malware Detection Under Extreme False Positive Constraints.
CoRR, 2021

Evading Malware Classifiers via Monte Carlo Mutant Feature Discovery.
CoRR, 2021

Semiring Primitives for Sparse Neighborhood Methods on the GPU.
CoRR, 2021

Accounting for Variance in Machine Learning Benchmarks.
CoRR, 2021

Intelligent Sight and Sound: A Chronic Cancer Facial Pain Dataset.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

A Spoken Language Dataset of Descriptions for Speech-Based Grounded Language Learning.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Learning with Holographic Reduced Representations.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021


Exact Acceleration of K-Means++ and K-Means||.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Generating Thermal Human Faces for Physiological Assessment using Thermal Sensor Auxiliary Labels.
Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

Practical Cross-Modal Manifold Alignment for Robotic Grounded Language Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Adversarial Transfer Attacks With Unknown Data and Class Overlap.
Proceedings of the AISec@CCS 2021: Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security, 2021

A Framework for Cluster and Classifier Evaluation in the Absence of Reference Labels.
Proceedings of the AISec@CCS 2021: Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security, 2021

Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Research Reproducibility as a Survival Analysis.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Bringing UMAP Closer to the Speed of Light with GPU Acceleration.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Trimming the Thorns of AI Fairness Research.
IEEE Data Eng. Bull., 2020

The Use of AI for Thermal Emotion Recognition: A Review of Problems and Limitations in Standard Design and Data.
CoRR, 2020

Practical Cross-modal Manifold Alignment for Grounded Language.
CoRR, 2020

Presentation and Analysis of a Multimodal Dataset for Grounded LanguageLearning.
CoRR, 2020

A Survey of Machine Learning Methods and Challenges for Windows Malware Classification.
CoRR, 2020

Exploratory Analysis of Covid-19 Tweets using Topic Modeling, UMAP, and DiGraphs.
CoRR, 2020

Flexible and Adaptive Fairness-aware Learning in Non-stationary Data Streams.
Proceedings of the 32nd IEEE International Conference on Tools with Artificial Intelligence, 2020

Getting Passive Aggressive About False Positives: Patching Deployed Malware Detectors.
Proceedings of the 20th International Conference on Data Mining Workshops, 2020

COVID-19 Kaggle Literature Organization.
Proceedings of the DocEng '20: ACM Symposium on Document Engineering 2020, Virtual Event, CA, USA, September 29, 2020

Robust Design of Deep Neural Networks Against Adversarial Attacks Based on Lyapunov Theory.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Automatic Yara Rule Generation Using Biclustering.
Proceedings of the AISec@CCS 2020: Proceedings of the 13th ACM Workshop on Artificial Intelligence and Security, 2020

Sampling Approach Matters: Active Learning for Robotic Language Acquisition.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

A New Burrows Wheeler Transform Markov Distance.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Heterogeneous Relational Kernel Learning.
CoRR, 2019

KiloGrams: Very Large N-Grams for Malware Classification.
CoRR, 2019

Connecting Lyapunov Control Theory to Adversarial Attacks.
CoRR, 2019

PyLZJD: An Easy to Use Tool for Machine Learning.
Proceedings of the 18th Python in Science Conference 2019 (SciPy 2019), Austin, Texas, July 8, 2019

A Step Toward Quantifying Independently Reproducible Machine Learning Research.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Barrage of Random Transforms for Adversarially Robust Defense.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Would a File by Any Other Name Seem as Malicious?
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018
An investigation of byte n-gram features for malware classification.
J. Comput. Virol. Hacking Tech., 2018

Lempel-Ziv Jaccard Distance, an effective alternative to ssdeep and sdhash.
Digit. Investig., 2018

Adversarial Attacks, Regression, and Numerical Stability Regularization.
CoRR, 2018

Growing and Retaining AI Talent for the United States Government.
CoRR, 2018

Gradient Reversal Against Discrimination.
CoRR, 2018

Non-Negative Networks Against Adversarial Attacks.
CoRR, 2018

What About Applied Fairness?
CoRR, 2018

Toward Metric Indexes for Incremental Insertion and Querying.
CoRR, 2018

Dr. AI, Where Did You Get Your Degree?
Proceedings of the Artificial Intelligence in Health - First International Workshop, 2018

Neural Fingerprint Enhancement.
Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

Gradient Reversal against Discrimination: A Fair Neural Network Learning Approach.
Proceedings of the 5th IEEE International Conference on Data Science and Advanced Analytics, 2018

Hash-Grams: Faster N-Gram Features for Classification and Malware Detection.
Proceedings of the ACM Symposium on Document Engineering 2018, 2018

Engineering a Simplified 0-Bit Consistent Weighted Sampling.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

Linear Models with Many Cores and CPUs: A Stochastic Atomic Update Scheme.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

Hash-Grams On Many-Cores and Skewed Distributions.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

Fair Forests: Regularized Tree Induction to Minimize Model Bias.
Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 2018

Static Malware Detection & Subterfuge: Quantifying the Robustness of Machine Learning and Current Anti-Virus.
Proceedings of the AAAI Symposium on Adversary-Aware Learning Techniques and Trends in Cybersecurity (ALEC 2018) co-located with the Association for the Advancement of Artificial Intelligence 2018 Fall Symposium Series (AAAI-FSS 2018), 2018

Malware Detection by Eating a Whole EXE.
Proceedings of the Workshops of the The Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
JSAT: Java Statistical Analysis Tool, a Library for Machine Learning.
J. Mach. Learn. Res., 2017

What can N-grams learn for malware detection?
Proceedings of the 12th International Conference on Malicious and Unwanted Software, 2017

An Alternative to NCD for Large Sequences, Lempel-Ziv Jaccard Distance.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Learning the PE Header, Malware Detection with Minimal Domain Knowledge.
Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security, 2017

Malware Classification and Class Imbalance via Stochastic Hashed LZJD.
Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security, 2017


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