Sutherland, Danica J.
- Demystifying MMD GANs
2018/01/04 by Mikołaj Bińkowski, Bińkowski, Mikołaj, Danica J. Sutherland +5 · 126 citations
Computer Science · Physics and Astronomy · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
- Exphormer: Sparse Transformers for Graphs
2023/03/10 by Shirzad, Hamed, Velingker, Ameya, Venkatachalam, Balaji +2 · 23 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG)
- Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy
2016/11/14 by Danica J. Sutherland, Sutherland, Danica J., Hsiao-Yu Fish Tung +11 · 12 citations
Computer Science · #Artificial Intelligence (cs.AI) #Bayesian Methods and Mixture Models #Digital Media Forensic Detection #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Neural and Evolutionary Computing (cs.NE)
- Learning Dynamics of LLM Finetuning
2024/07/15 by Yi Ren, Danica J. Sutherland, Ren, Yi +1 · 26 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Fuzzy Logic and Control Systems #Machine Learning (cs.LG) #Multi-Agent Systems and Negotiation #Natural Language Processing Techniques
- On the Error of Random Fourier Features
2015/06/09 by Sutherland, Danica J., Schneider, Jeff · 7 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Self-Supervised Learning with Kernel Dependence Maximization
2021/06/15 by Yazhe Li, Li, Yazhe, Roman Pogodin +5 · 8 citations
Computer Science · #Anomaly Detection Techniques and Applications #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization
2025/05/24 by Wenlong Deng, Yi Ren, Deng, Wenlong +9 · 14 citations
Social Sciences · #Advanced Computing and Algorithms #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
- Unbiased estimators for the variance of MMD estimators
2019/06/05 by Sutherland, Danica J., Deka, Namrata · 3 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Does Invariant Risk Minimization Capture Invariance?
2021/01/04 by Pritish Kamath, Akilesh Tangella, Kamath, Pritish +5 · 3 citations
Computer Science · Mathematics · #Artificial Intelligence (cs.AI) #Bayesian Methods and Mixture Models #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Bayesian Inference
- Practical Kernel Tests of Conditional Independence
2024/02/20 by Roman Pogodin, Pogodin, Roman, Antonin Schrab +7 · 5 citations
Mathematics · Computer Science · #Statistical Methods and Inference #Advanced Statistical Methods and Models #Bayesian Modeling and Causal Inference
- Why Do You Grok? A Theoretical Analysis of Grokking Modular Addition
2024/07/17 by Mohamad Amin Mohamadi, Mohamadi, Mohamad Amin, Zhiyuan Li +5 · 4 citations
Computer Science · #FOS: Computer and information sciences #Handwritten Text Recognition Techniques #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds, and\n Benign Overfitting
2021/06/17 by Frederic Koehler, Koehler, Frederic, Lijia Zhou +5 · 2 citations
Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification #Sparse and Compressive Sensing Techniques #Statistics Theory (math.ST)
- Object Discovery via Contrastive Learning for Weakly Supervised Object Detection
2022/08/16 by Seo, Jinhwan, Bae, Wonho, Sutherland, Danica J. +2 · 2 citations
#Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
- Kernels on Sample Sets via Nonparametric Divergence Estimates
2012/02/01 by Danica J. Sutherland, Liang Xiong, Sutherland, Danica J. +5 · 1 citation
Computer Science · #Advanced Image and Video Retrieval Techniques #FOS: Computer and information sciences #Face and Expression Recognition #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- AdaFlood: Adaptive Flood Regularization
2023/11/06 by Bae, Wonho, Ren, Yi, Ahmed, Mohamad Osama +3 · 2 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG)
- Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data
2021/06/14 by Liu, Feng, Wenkai Xu, Xu, Wenkai +3 · 2 citations
Computer Science · #Advanced Neural Network Applications #Artificial Intelligence (cs.AI) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Methodology (stat.ME)
- Generalized Coverage for More Robust Low-Budget Active Learning
2024/07/16 by Wonho Bae, Junhyug Noh, Bae, Wonho +3 · 3 citations
Computer Science · #Machine Learning and Algorithms
- The Role of Machine Learning in the Next Decade of Cosmology
2019/02/26 by Michelle Ntampaka, Ntampaka, Michelle, Camille Avestruz +57 · 1 citation
Physics and Astronomy · #Astronomy and Astrophysical Research #Cosmology and Nongalactic Astrophysics (astro-ph.CO) #FOS: Physical sciences #Galaxies: Formation, Evolution, Phenomena #Gamma-ray bursts and supernovae #Instrumentation and Methods for Astrophysics (astro-ph.IM)
- On Uniform Convergence and Low-Norm Interpolation Learning
2020/06/10 by Lijia Zhou, Danica J. Sutherland, Zhou, Lijia +3 · 1 citation
Computer Science · Engineering · #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Sparse and Compressive Sensing Techniques
- Improving Compositional Generalization Using Iterated Learning and Simplicial Embeddings
2023/10/28 by Yi Ren, Ren, Yi, Samuel Lavoie +7 · 2 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Materials Science · #Artificial Intelligence (cs.AI) #Computational Drug Discovery Methods #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning in Bioinformatics #Machine Learning in Materials Science
- Optimistic Rates: A Unifying Theory for Interpolation Learning and Regularization in Linear Regression
2021/12/08 by Zhou, Lijia, Koehler, Frederic, Sutherland, Danica J. +1 · 1 citation
#FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
- Evaluating Graph Generative Models with Contrastively Learned Features
2022/06/13 by Shirzad, Hamed, Hassani, Kaveh, Sutherland, Danica J. · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Pre-trained Perceptual Features Improve Differentially Private Image Generation
2022/05/25 by Harder, Fredrik, Asadabadi, Milad Jalali, Sutherland, Danica J. +1 · 1 citation
#Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Uncertainty Herding: One Active Learning Method for All Label Budgets
2024/12/30 by Bae, Wonho, Oliveira, Gabriel L., Sutherland, Danica J. · 3 citations
#FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Bias Amplification in Language Model Evolution: An Iterated Learning Perspective
2024/04/04 by Yi Ren, Shangmin Guo, Ren, Yi +7 · 1 voice · 1 citation
#cs.CL #cs.AI #cs.LG
- A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models
2022/10/21 by Lijia Zhou, Frederic Koehler, Zhou, Lijia +7 · 1 citation
Mathematics · Computer Science · #Statistical Methods and Inference #Machine Learning and Algorithms #Markov Chains and Monte Carlo Methods
- DUAL: Learning Diverse Kernels for Aggregated Two-sample and Independence Testing
2025/10/13 by Zhou, Zhijian, Tian, Xunye, Peng, Liuhua +4 · 1 citation
#FOS: Computer and information sciences #Machine Learning (cs.LG)