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2020 – today
- 2024
[c79]Mohammad Mahmudul Alam, Edward Raff, Stella Biderman, Tim Oates, James Holt:
Holographic Global Convolutional Networks for Long-Range Prediction Tasks in Malware Detection. AISTATS 2024: 4042-4050- [c78]Fred Lu
, Ryan R. Curtin, Edward Raff, Francis Ferraro, James Holt:
High-Dimensional Distributed Sparse Classification with Scalable Communication-Efficient Global Updates. KDD 2024: 2037-2047 - [c77]Manas Gaur, Efthymia Tsamoura, Edward Raff, Nikhita Vedula, Srinivasan Parthasarathy:
KiL 2024: 4th International Workshop on Knowledge-infused Learning (Towards Consistent, Reliable, Explainable, and Safe LLMs). KDD 2024: 6712-6713 - [c76]Amol Khanna, Edward Raff, Nathan Inkawhich:
SoK: A Review of Differentially Private Linear Models For High-Dimensional Data. SaTML 2024: 57-77 - [e2]Lauren Deason, Sagar Samtani, Edward Raff, Ethan M. Rudd:
Proceedings of the Conference on Applied Machine Learning in Information Security, Arlington, Virginia, USA, October 19-20, 2023. CEUR Workshop Proceedings 3652, CEUR-WS.org 2024 [contents] - [i94]Anish Lakkapragada, Amol Khanna, Edward Raff, Nathan Inkawhich:
Comprehensive OOD Detection Improvements. CoRR abs/2401.10176 (2024) - [i93]Mohammad Mahmudul Alam, Edward Raff, Stella Biderman, Tim Oates, James Holt:
Holographic Global Convolutional Networks for Long-Range Prediction Tasks in Malware Detection. CoRR abs/2403.17978 (2024) - [i92]Amol Khanna, Edward Raff, Nathan Inkawhich:
SoK: A Review of Differentially Private Linear Models For High-Dimensional Data. CoRR abs/2404.01141 (2024) - [i91]Deepa Tilwani, Yash Saxena, Ali Mohammadi, Edward Raff, Amit P. Sheth, Srinivasan Parthasarathy, Manas Gaur:
REASONS: A benchmark for REtrieval and Automated citationS Of scieNtific Sentences using Public and Proprietary LLMs. CoRR abs/2405.02228 (2024) - [i90]Chang Liu, Rebecca Saul, Yihao Sun, Edward Raff, Maya Fuchs, Townsend Southard Pantano, James Holt, Kristopher K. Micinski:
Assemblage: Automatic Binary Dataset Construction for Machine Learning. CoRR abs/2405.03991 (2024) - [i89]Fred Lu, Ryan R. Curtin, Edward Raff, Francis Ferraro, James Holt:
Optimizing the Optimal Weighted Average: Efficient Distributed Sparse Classification. CoRR abs/2406.01753 (2024) - [i88]Seyedali Mohammadi, Edward Raff, Jinendra Malekar, Vedant Palit, Francis Ferraro, Manas Gaur:
WellDunn: On the Robustness and Explainability of Language Models and Large Language Models in Identifying Wellness Dimensions. CoRR abs/2406.12058 (2024) - [i87]Fred Lu, Ryan R. Curtin, Edward Raff, Francis Ferraro, James Holt:
High-Dimensional Distributed Sparse Classification with Scalable Communication-Efficient Global Updates. CoRR abs/2407.06346 (2024) - [i86]Nilanjana Das, Edward Raff, Manas Gaur:
Human-Interpretable Adversarial Prompt Attack on Large Language Models with Situational Context. CoRR abs/2407.14644 (2024) - [i85]Ryan Swope, Amol Khanna, Philip Doldo, Saptarshi Roy, Edward Raff:
Feature Selection from Differentially Private Correlations. CoRR abs/2408.10862 (2024) - [i84]Ashley Klein, Edward Raff, Elisabeth Seamon, Lily Foley, Timothy Bussert:
More Options for Prelabor Rupture of Membranes, A Bayesian Analysis. CoRR abs/2408.10876 (2024) - 2023
- [j7]Robert J. Joyce, Dev Amlani, Charles Nicholas, Edward Raff:
MOTIF: A Malware Reference Dataset with Ground Truth Family Labels. Comput. Secur. 124: 102921 (2023) - [j6]Maksim Ekin Eren, Manish Bhattarai, Robert J. Joyce, Edward Raff, Charles Nicholas, Boian S. Alexandrov:
Semi-Supervised Classification of Malware Families Under Extreme Class Imbalance via Hierarchical Non-Negative Matrix Factorization with Automatic Model Selection. ACM Trans. Priv. Secur. 26(4): 48:1-48:27 (2023) - [j5]Kasra Darvish, Edward Raff, Francis Ferraro, Cynthia Matuszek:
Multimodal Language Learning for Object Retrieval in Low Data Regimes in the Face of Missing Modalities. Trans. Mach. Learn. Res. 2023 (2023) - [c75]Fred Lu, Edward Raff, James Holt:
A Coreset Learning Reality Check. AAAI 2023: 8940-8948 - [c74]Zheng Xin Yong, Hailey Schoelkopf, Niklas Muennighoff, Alham Fikri Aji, David Ifeoluwa Adelani, Khalid Almubarak, M. Saiful Bari, Lintang Sutawika, Jungo Kasai, Ahmed Baruwa, Genta Indra Winata, Stella Biderman, Edward Raff, Dragomir Radev, Vassilina Nikoulina:
BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting. ACL (1) 2023: 11682-11703 - [c73]Niklas Muennighoff, Thomas Wang, Lintang Sutawika, Adam Roberts, Stella Biderman, Teven Le Scao, M. Saiful Bari, Sheng Shen, Zheng Xin Yong, Hailey Schoelkopf, Xiangru Tang, Dragomir Radev, Alham Fikri Aji, Khalid Almubarak, Samuel Albanie, Zaid Alyafeai, Albert Webson, Edward Raff, Colin Raffel:
Crosslingual Generalization through Multitask Finetuning. ACL (1) 2023: 15991-16111 - [c72]Edward Raff:
Does the Market of Citations Reward Reproducible Work? ACM-REP 2023: 89-96 - [c71]Edward Raff, Andrew L. Farris:
A Siren Song of Open Source Reproducibility, Examples from Machine Learning. ACM-REP 2023: 115-120 - [c70]Robert J. Joyce, Edward Raff, Charles Nicholas, James Holt:
MalDICT: Benchmark Datasets on Malware Behaviors, Platforms, Exploitation, and Packers. CAMLIS 2023: 105-121 - [c69]Tirth Patel, Fred Lu, Edward Raff, Charles Nicholas, Cynthia Matuszek, James Holt:
Small Effect Sizes in Malware Detection? Make Harder Train/Test Splits! CAMLIS 2023: 181-192 - [c68]Amol Khanna, Fred Lu, Edward Raff, Brian Testa:
Differentially Private Logistic Regression with Sparse Solutions. AISec@CCS 2023: 1-9 - [c67]Tyler LeBlond, Joseph Munoz, Fred Lu, Maya Fuchs, Elliott Zaresky-Williams, Edward Raff, Brian Testa:
Probing the Transition to Dataset-Level Privacy in ML Models Using an Output-Specific and Data-Resolved Privacy Profile. AISec@CCS 2023: 23-33 - [c66]Luke E. Richards, Edward Raff, Cynthia Matuszek:
Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech Recognition. AISec@CCS 2023: 161-171 - [c65]Robert J. Joyce, Tirth Patel, Charles Nicholas, Edward Raff:
AVScan2Vec: Feature Learning on Antivirus Scan Data for Production-Scale Malware Corpora. AISec@CCS 2023: 185-196 - [c64]Edward Raff, Cynthia Matuszek:
Does Starting Deep Learning Homework Earlier Improve Grades? ECAI Workshops (2) 2023: 381-396 - [c63]Edward Raff, Mark McLean, James Holt:
An Easy Rejection Sampling Baseline via Gradient Refined Proposals. ECAI 2023: 1930-1937 - [c62]Catherine Ordun, Edward Raff, Sanjay Purushotham:
Vista Morph - Unsupervised Image Registration of Visible-Thermal Facial Pairs. IJCB 2023: 1-10 - [c61]Catherine Ordun, Edward Raff, Sanjay Purushotham:
When Visible-to-Thermal Facial GAN Beats Conditional Diffusion. ICIP 2023: 181-185 - [c60]Fred Lu, Edward Raff, Francis Ferraro:
Neural Bregman Divergences for Distance Learning. ICLR 2023 - [c59]Mohammad Mahmudul Alam, Edward Raff, Stella Biderman, Tim Oates, James Holt:
Recasting Self-Attention with Holographic Reduced Representations. ICML 2023: 490-507 - [c58]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:
Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling. ICML 2023: 2397-2430 - [c57]Catherine Ordun, Alexandra N. Cha, Edward Raff, Sanjay Purushotham, Karen Kwok, Mason Rule, James L. Gulley:
A Generative Approach for Image Registration of Visible-Thermal (VT) Cancer Faces. AIIIMA@MICCAI 2023: 91-100 - [c56]Nora Belrose, David Schneider-Joseph, Shauli Ravfogel, Ryan Cotterell, Edward Raff, Stella Biderman:
LEACE: Perfect linear concept erasure in closed form. NeurIPS 2023 - [c55]Stella Biderman, USVSN Sai Prashanth, Lintang Sutawika, Hailey Schoelkopf, Quentin Anthony, Shivanshu Purohit, Edward Raff:
Emergent and Predictable Memorization in Large Language Models. NeurIPS 2023 - [c54]Edward Raff, James Holt:
Reproducibility in Multiple Instance Learning: A Case For Algorithmic Unit Tests. NeurIPS 2023 - [c53]Edward Raff, Amol Khanna, Fred Lu:
Scaling Up Differentially Private LASSO Regularized Logistic Regression via Faster Frank-Wolfe Iterations. NeurIPS 2023 - [c52]Mike Wong, Edward Raff, James Holt, Ravi Netravali:
Marvolo: Programmatic Data Augmentation for Deep Malware Detection. ECML/PKDD (1) 2023: 270-285 - [c51]Corey J. Nolet, Divye Gala, Alexandre Fender, Mahesh Doijade, Joe Eaton, Edward Raff, John Zedlewski, Brad Rees, Tim Oates:
cuSLINK: Single-Linkage Agglomerative Clustering on the GPU. ECML/PKDD (1) 2023: 711-726 - [e1]Edward Raff, Sagar Samtani, Lauren Deason:
Proceedings of the Conference on Applied Machine Learning in Information Security, CAMLIS 2022, Arlington, Virginia, USA, October 20-21, 2022. CEUR Workshop Proceedings 3391, CEUR-WS.org 2023 [contents] - [i83]Fred Lu, Edward Raff, James Holt:
A Coreset Learning Reality Check. CoRR abs/2301.06163 (2023) - [i82]Luke E. Richards, Edward Raff, Cynthia Matuszek:
Measuring Equality in Machine Learning Security Defenses. CoRR abs/2302.08973 (2023) - [i81]Catherine Ordun, Edward Raff, Sanjay Purushotham:
When Visible-to-Thermal Facial GAN Beats Conditional Diffusion. CoRR abs/2302.09395 (2023) - [i80]Amol Khanna, Fred Lu, Edward Raff:
The Challenge of Differentially Private Screening Rules. CoRR abs/2303.10303 (2023) - [i79]Stella Biderman, Hailey Schoelkopf, Quentin 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:
Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling. CoRR abs/2304.01373 (2023) - [i78]Stella Biderman, USVSN Sai Prashanth, Lintang Sutawika, Hailey Schoelkopf, Quentin Anthony, Shivanshu Purohit, Edward Raff:
Emergent and Predictable Memorization in Large Language Models. CoRR abs/2304.11158 (2023) - [i77]Amol Khanna, Fred Lu, Edward Raff, Brian Testa:
Sparse Private LASSO Logistic Regression. CoRR abs/2304.12429 (2023) - [i76]Mohammad Mahmudul Alam, Edward Raff, Stella Biderman, Tim Oates, James Holt:
Recasting Self-Attention with Holographic Reduced Representations. CoRR abs/2305.19534 (2023) - [i75]Nora Belrose, David Schneider-Joseph, Shauli Ravfogel, Ryan Cotterell, Edward Raff, Stella Biderman:
LEACE: Perfect linear concept erasure in closed form. CoRR abs/2306.03819 (2023) - [i74]Robert J. Joyce, Tirth Patel, Charles Nicholas, Edward Raff:
AVScan2Vec: Feature Learning on Antivirus Scan Data for Production-Scale Malware Corpora. CoRR abs/2306.06228 (2023) - [i73]Catherine Ordun, Edward Raff, Sanjay Purushotham:
Vista-Morph: Unsupervised Image Registration of Visible-Thermal Facial Pairs. CoRR abs/2306.06505 (2023) - [i72]Edward Raff, Michel Benaroch, Andrew L. Farris:
You Don't Need Robust Machine Learning to Manage Adversarial Attack Risks. CoRR abs/2306.09951 (2023) - [i71]Tyler LeBlond, Joseph Munoz, Fred Lu, Maya Fuchs, Elliott Zaresky-Williams, Edward Raff, Brian Testa:
Probing the Transition to Dataset-Level Privacy in ML Models Using an Output-Specific and Data-Resolved Privacy Profile. CoRR abs/2306.15790 (2023) - [i70]Corey J. Nolet, Divye Gala, Alexandre Fender, Mahesh Doijade, Joe Eaton, Edward Raff, John Zedlewski, Brad Rees, Tim Oates:
cuSLINK: Single-linkage Agglomerative Clustering on the GPU. CoRR abs/2306.16354 (2023) - [i69]Skyler Wu, Fred Lu, Edward Raff, James Holt:
Exploring the Sharpened Cosine Similarity. CoRR abs/2307.13855 (2023) - [i68]Catherine Ordun, Alexandra N. Cha, Edward Raff, Sanjay Purushotham, Karen Kwok, Mason Rule, James L. Gulley:
A Generative Approach for Image Registration of Visible-Thermal (VT) Cancer Faces. CoRR abs/2308.12271 (2023) - [i67]Maksim Ekin Eren, Manish Bhattarai, Robert J. Joyce, Edward Raff, Charles Nicholas, Boian S. Alexandrov:
Semi-supervised Classification of Malware Families Under Extreme Class Imbalance via Hierarchical Non-Negative Matrix Factorization with Automatic Model Selection. CoRR abs/2309.06643 (2023) - [i66]Robert J. Joyce, Edward Raff, Charles Nicholas, James Holt:
MalDICT: Benchmark Datasets on Malware Behaviors, Platforms, Exploitation, and Packers. CoRR abs/2310.11706 (2023) - [i65]Edward Raff, James Holt:
Reproducibility in Multiple Instance Learning: A Case For Algorithmic Unit Tests. CoRR abs/2310.17867 (2023) - [i64]Edward Raff, Amol Khanna, Fred Lu:
Scaling Up Differentially Private LASSO Regularized Logistic Regression via Faster Frank-Wolfe Iterations. CoRR abs/2310.19978 (2023) - [i63]Edward Raff, Cynthia Matuszek:
Does Starting Deep Learning Homework Earlier Improve Grades? CoRR abs/2311.09228 (2023) - [i62]Mohammad Mahmudul Alam, Edward Raff, Tim Oates, Cynthia Matuszek:
DDxT: Deep Generative Transformer Models for Differential Diagnosis. CoRR abs/2312.01242 (2023) - [i61]Mohammad Mahmudul Alam, Edward Raff, Tim Oates:
Towards Generalization in Subitizing with Neuro-Symbolic Loss using Holographic Reduced Representations. CoRR abs/2312.15310 (2023) - [i60]Tirth Patel, Fred Lu, Edward Raff, Charles Nicholas, Cynthia Matuszek, James Holt:
Small Effect Sizes in Malware Detection? Make Harder Train/Test Splits! CoRR abs/2312.15813 (2023) - 2022
- [c50]André T. Nguyen, Fred Lu, Gary Lopez Munoz, Edward Raff, Charles Nicholas, James Holt:
Out of Distribution Data Detection Using Dropout Bayesian Neural Networks. AAAI 2022: 7877-7885 - [c49]Gaoussou Youssouf Kebe, Luke E. Richards, Edward Raff, Francis Ferraro, Cynthia Matuszek:
Bridging the Gap: Using Deep Acoustic Representations to Learn Grounded Language from Percepts and Raw Speech. AAAI 2022: 10884-10893 - [c48]Ethan M. Rudd, David Krisiloff, Daniel Olszewski, Edward Raff, James Holt:
Efficient Malware Analysis Using Metric Embeddings. CAMLIS 2022: 65-80 - [c47]André T. Nguyen, Richard Zak, Luke E. Richards, Maya Fuchs, Fred Lu, Robert Brandon, Gary Lopez Munoz, Edward Raff, Charles Nicholas, James Holt:
Minimizing Compute Costs: When Should We Run More Expensive Malware Analysis? CAMLIS 2022: 81-99 - [c46]Stella Biderman, Edward Raff:
Fooling MOSS Detection with Pretrained Language Models. CIKM 2022: 2933-2943 - [c45]Katherine Crowson, Stella Biderman, Daniel Kornis, Dashiell Stander, Eric Hallahan, Louis Castricato, Edward Raff:
VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidance. ECCV (37) 2022: 88-105 - [c44]Rebecca Saul, Mohammad Mahmudul Alam, John Hurwitz, Edward Raff, Tim Oates, James Holt:
Lempel-Ziv Networks. ICBINB 2022: 1-11 - [c43]Mohammad Mahmudul Alam, Edward Raff, Tim Oates, James Holt:
Deploying Convolutional Networks on Untrusted Platforms Using 2D Holographic Reduced Representations. ICML 2022: 367-393 - [c42]Corey J. Nolet, Divye Gala, Edward Raff, Joe Eaton, Brad Rees, Tim Oates:
GPU Semiring Primitives for Sparse Neighborhood Methods. MLSys 2022 - [c41]Fred Lu, Joseph Munoz, Maya Fuchs, Tyler LeBlond, Elliott Zaresky-Williams, Edward Raff, Francis Ferraro, Brian Testa:
A General Framework for Auditing Differentially Private Machine Learning. NeurIPS 2022 - [c40]Fred Lu, Francis Ferraro, Edward Raff:
Continuously Generalized Ordinal Regression for Linear and Deep Models. SDM 2022: 28-36 - [i59]Robert J. Joyce, Edward Raff, Charles Nicholas:
Rank-1 Similarity Matrix Decomposition For Modeling Changes in Antivirus Consensus Through Time. CoRR abs/2201.00757 (2022) - [i58]Stella Biderman, Edward Raff:
Neural Language Models are Effective Plagiarists. CoRR abs/2201.07406 (2022) - [i57]Fred Lu, Francis Ferraro, Edward Raff:
Continuously Generalized Ordinal Regression for Linear and Deep Models. CoRR abs/2202.07005 (2022) - [i56]André T. Nguyen, Fred Lu, Gary Lopez Munoz, Edward Raff, Charles Nicholas, James Holt:
Out of Distribution Data Detection Using Dropout Bayesian Neural Networks. CoRR abs/2202.08985 (2022) - [i55]James Holt, Edward Raff, Ahmad Ridley, Dennis Ross, Arunesh Sinha, Diane Staheli, William Streilen, Milind Tambe, Yevgeniy Vorobeychik, Allan B. Wollaber:
Artificial Intelligence for Cyber Security (AICS). CoRR abs/2202.14010 (2022) - [i54]Edward Raff:
Does the Market of Citations Reward Reproducible Work? CoRR abs/2204.03829 (2022) - [i53]Catherine Ordun, Alexandra N. Cha, Edward Raff, Byron Gaskin, Alex Hanson, Mason Rule, Sanjay Purushotham, James L. Gulley:
Intelligent Sight and Sound: A Chronic Cancer Pain Dataset. CoRR abs/2204.04214 (2022) - [i52]Edward Raff, Andrew L. Farris:
A Siren Song of Open Source Reproducibility. CoRR abs/2204.04372 (2022) - [i51]Katherine Crowson, Stella Biderman, Daniel Kornis, Dashiell Stander, Eric Hallahan, Louis Castricato, Edward Raff:
VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidance. CoRR abs/2204.08583 (2022) - [i50]Michael D. Wong, Edward Raff, James Holt, Ravi Netravali:
Marvolo: Programmatic Data Augmentation for Practical ML-Driven Malware Detection. CoRR abs/2206.03265 (2022) - [i49]Fred Lu, Edward Raff, Francis Ferraro:
Neural Bregman Divergences for Distance Learning. CoRR abs/2206.04763 (2022) - [i48]Mohammad Mahmudul Alam, Edward Raff, Tim Oates, James Holt:
Deploying Convolutional Networks on Untrusted Platforms Using 2D Holographic Reduced Representations. CoRR abs/2206.05893 (2022) - [i47]Derek Everett, André T. Nguyen, Luke E. Richards, Edward Raff:
Improving Out-of-Distribution Detection via Epistemic Uncertainty Adversarial Training. CoRR abs/2209.03148 (2022) - [i46]Fred Lu, Joseph Munoz, Maya Fuchs, Tyler LeBlond, Elliott Zaresky-Williams, Edward Raff, Francis Ferraro, Brian Testa:
A General Framework for Auditing Differentially Private Machine Learning. CoRR abs/2210.08643 (2022) - [i45]Niklas Muennighoff, Thomas Wang, Lintang Sutawika, Adam Roberts, Stella Biderman, Teven Le Scao, M. Saiful Bari, Sheng Shen, Zheng Xin Yong, Hailey Schoelkopf, Xiangru Tang, Dragomir Radev, Alham Fikri Aji, Khalid Almubarak, Samuel Albanie, Zaid Alyafeai, Albert Webson, Edward Raff, Colin Raffel:
Crosslingual Generalization through Multitask Finetuning. CoRR abs/2211.01786 (2022) - [i44]Rebecca Saul, Mohammad Mahmudul Alam, John Hurwitz, Edward Raff, Tim Oates, James Holt:
Lempel-Ziv Networks. CoRR abs/2211.13250 (2022) - [i43]Ethan M. Rudd, David Krisiloff, Scott E. Coull, Daniel Olszewski, Edward Raff, James Holt:
Efficient Malware Analysis Using Metric Embeddings. CoRR abs/2212.02663 (2022) - 2021
- [c39]Corey J. Nolet, Victor Lafargue, Edward Raff, Thejaswi Nanditale, Tim Oates, John Zedlewski, Joshua Patterson:
Bringing UMAP Closer to the Speed of Light with GPU Acceleration. AAAI 2021: 418-426 - [c38]Edward Raff:
Research Reproducibility as a Survival Analysis. AAAI 2021: 469-478 - [c37]Edward Raff, William Fleshman, Richard Zak, Hyrum S. Anderson, Bobby Filar, Mark McLean:
Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection. AAAI 2021: 9386-9394 - [c36]Luke E. Richards, André T. Nguyen, Ryan Capps, Steven Forsyth, Cynthia Matuszek, Edward Raff:
Adversarial Transfer Attacks With Unknown Data and Class Overlap. AISec@CCS 2021: 13-24 - [c35]Robert J. Joyce, Edward Raff, Charles Nicholas:
A Framework for Cluster and Classifier Evaluation in the Absence of Reference Labels. AISec@CCS 2021: 73-84 - [c34]André T. Nguyen, Luke E. Richards, Gaoussou Youssouf Kebe, Edward Raff, Kasra Darvish, Frank Ferraro, Cynthia Matuszek:
Practical Cross-Modal Manifold Alignment for Robotic Grounded Language Learning. CVPR Workshops 2021: 1613-1622 - [c33]Catherine Ordun, Edward Raff, Sanjay Purushotham:
Generating Thermal Human Faces for Physiological Assessment using Thermal Sensor Auxiliary Labels. ICIP 2021: 1319-1323 - [c32]Edward Raff:
Exact Acceleration of K-Means++ and K-Means||. IJCAI 2021: 2928-2935 - [c31]Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Nazanin Mohammadi Sepahvand, Edward Raff, Kanika Madan, Vikram Voleti, Samira Ebrahimi Kahou, Vincent Michalski, Tal Arbel, Chris Pal, Gaël Varoquaux, Pascal Vincent:
Accounting for Variance in Machine Learning Benchmarks. MLSys 2021 - [c30]Ashwinkumar Ganesan, Hang Gao, Sunil Gandhi, Edward Raff, Tim Oates, James Holt, Mark McLean:
Learning with Holographic Reduced Representations. NeurIPS 2021: 25606-25620 - [c29]Gaoussou Youssouf Kebe, Padraig Higgins, Patrick Jenkins, Kasra Darvish, Rishabh Sachdeva, Ryan Barron, John Winder, Don Engel, Edward Raff, Francis Ferraro, Cynthia Matuszek:
A Spoken Language Dataset of Descriptions for Speech-Based Grounded Language Learning. NeurIPS Datasets and Benchmarks 2021 - [c28]Catherine Ordun, Alexandra N. Cha, Edward Raff, Byron Gaskin, Alex Hanson, Mason Rule, Sanjay Purushotham, James L. Gulley:
Intelligent Sight and Sound: A Chronic Cancer Facial Pain Dataset. NeurIPS Datasets and Benchmarks 2021 - [i42]Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Naz Sepah, Edward Raff, Kanika Madan, Vikram Voleti, Samira Ebrahimi Kahou, Vincent Michalski, Dmitriy Serdyuk, Tal Arbel, Chris Pal, Gaël Varoquaux, Pascal Vincent:
Accounting for Variance in Machine Learning Benchmarks. CoRR abs/2103.03098 (2021) - [i41]Corey J. Nolet, Divye Gala, Edward Raff, Joe Eaton, Brad Rees, John Zedlewski, Tim Oates:
Semiring Primitives for Sparse Neighborhood Methods on the GPU. CoRR abs/2104.06357 (2021) - [i40]Edward Raff:
Exact Acceleration of K-Means++ and K-Means∥. CoRR abs/2105.02936 (2021) - [i39]John Boutsikas, Maksim Ekin Eren, Charles K. Varga, Edward Raff, Cynthia Matuszek, Charles Nicholas:
Evading Malware Classifiers via Monte Carlo Mutant Feature Discovery. CoRR abs/2106.07860 (2021) - [i38]