Raff, Edward

45 publications

AAAI 2025 Can LLMs Obfuscate Code? a Systematic Analysis of Large Language Models into Assembly Code Obfuscation Seyedreza Mohseni, Seyedali Mohammadi, Deepa Tilwani, Yash Saxena, Gerald Ketu Ndawula, Sriram Vema, Edward Raff, Manas Gaur

CVPRW 2025 Multi-Layer Radial Basis Function Networks for Out-of-Distribution Detection Amol Khanna, Chenyi Ling, Derek Everett, Edward Raff, Nathan Inkawhich

ECML-PKDD 2025 Optimizing the Optimal Weighted Average: Efficient Distributed Sparse Classification Fred Lu, Ryan R. Curtin, Edward Raff, Francis Ferraro, James Holt

CVPR 2025 Stop Walking in Circles! Bailing Out Early in Projected Gradient Descent Philip Doldo, Derek Everett, Amol Khanna, Andre T Nguyen, Edward Raff

AAAI 2025 What Do Machine Learning Researchers Mean by "Reproducible"? Edward Raff, Michel Benaroch, Sagar Samtani, Andrew L. Farris

NeurIPS 2024 A Walsh Hadamard Derived Linear Vector Symbolic Architecture Mohammad Mahmudul Alam, Alexander Oberle, Edward Raff, Stella Biderman, Tim Oates, James Holt

NeurIPSW 2024 A Walsh Hadamard Derived Linear Vector Symbolic Architecture Mohammad Mahmudul Alam, Alexander Oberle, Edward Raff, Stella Biderman, Tim Oates, James Holt

NeurIPS 2024 Assemblage: Automatic Binary Dataset Construction for Machine Learning Chang Liu, Rebecca Saul, Yihao Sun, Edward Raff, Maya Fuchs, Townsend Southard Pantano, James Holt, Kristopher Micinski

AISTATS 2024 Holographic Global Convolutional Networks for Long-Range Prediction Tasks in Malware Detection Mohammad Mahmudul Alam, Edward Raff, Stella R Biderman, Tim Oates, James Holt

NeurIPS 2024 Is Function Similarity Over-Engineered? Building a Benchmark Rebecca Saul, Chang Liu, Noah Fleischmann, Richard Zak, Kristopher Micinski, Edward Raff, James Holt

NeurIPSW 2024 Neural Normalized Compression Distance and the Disconnect Between Compression and Classification John Hurwitz, Charles K. Nicholas, Edward Raff

NeurIPSW 2024 Position: Challenges and Opportunities for Differential Privacy in the U.S. Federal Government Amol Khanna, Adam Mccormick, Andre T Nguyen, Christopher Aguirre, Edward Raff

NeurIPS 2024 Stabilizing Linear Passive-Aggressive Online Learning with Weighted Reservoir Sampling Skyler Wu, Fred Lu, Edward Raff, James Holt

AAAI 2023 A Coreset Learning Reality Check Fred Lu, Edward Raff, James Holt

NeurIPSW 2023 DDxT: Deep Generative Transformer Models for Differential Diagnosis Mohammad Mahmudul Alam, Edward Raff, Tim Oates, Cynthia Matuszek

NeurIPS 2023 Emergent and Predictable Memorization in Large Language Models Stella Biderman, Usvsn Prashanth, Lintang Sutawika, Hailey Schoelkopf, Quentin Anthony, Shivanshu Purohit, Edward Raff

NeurIPS 2023 LEACE: Perfect Linear Concept Erasure in Closed Form Nora Belrose, David Schneider-Joseph, Shauli Ravfogel, Ryan Cotterell, Edward Raff, Stella Biderman

ECML-PKDD 2023 Marvolo: Programmatic Data Augmentation for Deep Malware Detection Mike Wong, Edward Raff, James Holt, Ravi Netravali

TMLR 2023 Multimodal Language Learning for Object Retrieval in Low Data Regimes in the Face of Missing Modalities Kasra Darvish, Edward Raff, Francis Ferraro, Cynthia Matuszek

ICLR 2023 Neural Bregman Divergences for Distance Learning Fred Lu, Edward Raff, Francis Ferraro

ICML 2023 Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling Stella Biderman, Hailey Schoelkopf, Quentin Gregory Anthony, Herbie Bradley, Kyle O’Brien, Eric Hallahan, Mohammad Aflah Khan, Shivanshu Purohit, Usvsn Sai Prashanth, Edward Raff, Aviya Skowron, Lintang Sutawika, Oskar Van Der Wal

ICML 2023 Recasting Self-Attention with Holographic Reduced Representations Mohammad Mahmudul Alam, Edward Raff, Stella Biderman, Tim Oates, James Holt

NeurIPS 2023 Reproducibility in Multiple Instance Learning: A Case for Algorithmic Unit Tests Edward Raff, James Holt

NeurIPS 2023 Scaling up Differentially Private LASSO Regularized Logistic Regression via Faster Frank-Wolfe Iterations Edward Raff, Amol Khanna, Fred Lu

ICMLW 2023 The Challenge of Differentially Private Screening Rules Amol Khanna, Fred Lu, Edward Raff

ECML-PKDD 2023 cuSLINK: Single-Linkage Agglomerative Clustering on the GPU Corey J. Nolet, Divye Gala, Alexandre Fender, Mahesh Doijade, Joe Eaton, Edward Raff, John Zedlewski, Brad Rees, Tim Oates

NeurIPS 2022 A General Framework for Auditing Differentially Private Machine Learning Fred Lu, Joseph Munoz, Maya Fuchs, Tyler LeBlond, Elliott Zaresky-Williams, Edward Raff, Francis Ferraro, Brian Testa

AAAI 2022 Bridging the Gap: Using Deep Acoustic Representations to Learn Grounded Language from Percepts and Raw Speech Gaoussou Youssouf Kebe, Luke E. Richards, Edward Raff, Francis Ferraro, Cynthia Matuszek

ICML 2022 Deploying Convolutional Networks on Untrusted Platforms Using 2D Holographic Reduced Representations Mohammad Mahmudul Alam, Edward Raff, Tim Oates, James Holt

NeurIPSW 2022 Exploring the Sharpened Cosine Similarity Skyler Wu, Fred Lu, Edward Raff, James Holt

NeurIPSW 2022 Lempel-Ziv Networks Rebecca Saul, Mohammad Mahmudul Alam, John Hurwitz, Edward Raff, Tim Oates, James Holt

AAAI 2022 Out of Distribution Data Detection Using Dropout Bayesian Neural Networks André T. Nguyen, Fred Lu, Gary Lopez Munoz, Edward Raff, Charles Nicholas, James Holt

ECCV 2022 VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidance Katherine Crowson, Stella Biderman, Daniel Kornis, Dashiell Stander, Eric Hallahan, Louis Castricato, Edward Raff

AAAI 2021 Bringing UMAP Closer to the Speed of Light with GPU Acceleration Corey J. Nolet, Victor Lafargue, Edward Raff, Thejaswi Nanditale, Tim Oates, John Zedlewski, Joshua Patterson

AAAI 2021 Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection Edward Raff, William Fleshman, Richard Zak, Hyrum S. Anderson, Bobby Filar, Mark McLean

IJCAI 2021 Exact Acceleration of K-Means++ and K-Means Edward Raff

NeurIPS 2021 Learning with Holographic Reduced Representations Ashwinkumar Ganesan, Hang Gao, Sunil Gandhi, Edward Raff, Tim Oates, James Holt, Mark McLean

CVPRW 2021 Practical Cross-Modal Manifold Alignment for Robotic Grounded Language Learning André T. Nguyen, Luke E. Richards, Gaoussou Youssouf Kebe, Edward Raff, Kasra Darvish, Frank Ferraro, Cynthia Matuszek

AAAI 2021 Research Reproducibility as a Survival Analysis Edward Raff

AAAI 2020 A New Burrows Wheeler Transform Markov Distance Edward Raff, Charles Nicholas, Mark McLean

CVPR 2020 Robust Design of Deep Neural Networks Against Adversarial Attacks Based on Lyapunov Theory Arash Rahnama, Andre T. Nguyen, Edward Raff

NeurIPS 2019 A Step Toward Quantifying Independently Reproducible Machine Learning Research Edward Raff

CVPR 2019 Barrage of Random Transforms for Adversarially Robust Defense Edward Raff, Jared Sylvester, Steven Forsyth, Mark McLean

IJCAI 2018 Dr. AI, Where Did You Get Your Degree? Edward Raff, Shannon Lantzy, Ezekiel J. Maier

MLOSS 2017 JSAT: Java Statistical Analysis Tool, a Library for Machine Learning Edward Raff