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Sheldon, Daniel

  1. AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data
    2022/01/29 by Ryan M. McKenna, Brett Mullins, McKenna, Ryan +5 · 13 citations
    Computer Science · #Cryptography and Data Security #Databases (cs.DB) #FOS: Computer and information sciences #Privacy-Preserving Technologies in Data #Stochastic Gradient Optimization Techniques
  2. Graphical-model based estimation and inference for differential privacy
    2019/01/26 by McKenna, Ryan, Sheldon, Daniel, Miklau, Gerome · 9 citations
    #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  3. Winning the NIST Contest: A scalable and general approach to differentially private synthetic data
    2021/08/11 by Ryan M. McKenna, McKenna, Ryan, Gerome Miklau +3 · 9 citations
    Computer Science · Decision Sciences · Engineering · #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Privacy-Preserving Technologies in Data #Probability and Risk Models #Vehicular Ad Hoc Networks (VANETs)
  4. The Spatio-Temporal Poisson Point Process: A Simple Model for the Alignment of Event Camera Data
    2021/06/13 by Cheng Gu, Erik Learned-Miller, Gu, Cheng +7 · 5 citations
    Engineering · Neuroscience · #Advanced Memory and Neural Computing #Ferroelectric and Negative Capacitance Devices #Neural dynamics and brain function
  5. Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization
    2020/06/18 by Agrawal, Abhinav, Sheldon, Daniel, Domke, Justin · 4 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  6. Parametric Bootstrap for Differentially Private Confidence Intervals
    2020/06/14 by Cecilia Ferrando, Shufan Wang, Ferrando, Cecilia +3 · 4 citations
    Computer Science · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Privacy-Preserving Technologies in Data #Statistical Methods and Bayesian Inference #Statistical Methods and Inference
  7. Differentially Private Bayesian Inference for Exponential Families
    2018/09/06 by Garrett Bernstein, Bernstein, Garrett, Daniel Sheldon +1 · 4 citations
    Computer Science · Mathematics · #Privacy-Preserving Technologies in Data #Statistical Methods and Bayesian Inference #Random Matrices and Applications
  8. Differentially Private Bayesian Linear Regression
    2019/10/29 by Garrett Bernstein, Daniel Sheldon, Bernstein, Garrett +1 · 3 citations
    Computer Science · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  9. A Bayesian Perspective on the Deep Image Prior
    2019/04/16 by Zezhou Cheng, Matheus Gadelha, Cheng, Zezhou +5 · 3 citations
    Computer Science · #Image and Signal Denoising Methods #Advanced Image Processing Techniques #Medical Image Segmentation Techniques
  10. Permute-and-Flip: A new mechanism for differentially private selection
    2020/10/23 by McKenna, Ryan, Sheldon, Daniel · 2 citations
    #Cryptography and Security (cs.CR) #FOS: Computer and information sciences
  11. Sample Average Approximation for Black-Box VI
    2023/04/13 by Javier Burroni, Justin Domke, Burroni, Javier +3 · 2 citations
    Computer Science · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Metaheuristic Optimization Algorithms Research #Optimization and Control (math.OC) #Stochastic Gradient Optimization Techniques
  12. Consistently Estimating Markov Chains with Noisy Aggregate Data
    2016/04/14 by Garrett Bernstein, Bernstein, Garrett, Daniel Sheldon +1 · 1 citation
    Computer Science · Mathematics · #Bayesian Methods and Mixture Models #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods
  13. Importance Weighting and Variational Inference
    2018/08/27 by Domke, Justin, Sheldon, Daniel · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  14. Human-in-the-Loop Visual Re-ID for Population Size Estimation
    2023/12/08 by Perez, Gustavo, Sheldon, Daniel, Van Horn, Grant +1 · 2 citations
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
  15. Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation
    2019/06/24 by Domke, Justin, Sheldon, Daniel · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  16. Maximizing the Spread of Cascades Using Network Design
    2012/03/15 by Daniel Sheldon, Sheldon, Daniel, Bistra Dilkina +19 · 1 citation
    Medicine · Physics and Astronomy · Social Sciences · #Complex Network Analysis Techniques #Evolutionary Game Theory and Cooperation #FOS: Computer and information sciences #FOS: Physical sciences #Mathematical and Theoretical Epidemiology and Ecology Models #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI)
  17. Joint Selection: Adaptively Incorporating Public Information for Private Synthetic Data
    2024/03/12 by Miguel Fuentes, Fuentes, Miguel, Brett Mullins +7 · 2 citations
    Computer Science · Decision Sciences · #Artificial Intelligence (cs.AI) #Cryptography and Data Security #Data Quality and Management #FOS: Computer and information sciences #Machine Learning (cs.LG) #Privacy-Preserving Technologies in Data
  18. Normalizing Flows Across Dimensions
    2020/06/23 by Cunningham, Edmond, Zabounidis, Renos, Agrawal, Abhinav +2 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  19. Variational Marginal Particle Filters
    2021/09/30 by Jinlin Lai, Lai, Jinlin, Justin Domke +3 · 1 citation
    Computer Science · Engineering · Physics and Astronomy · #Control Systems and Identification #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
  20. Kernel Interpolation with Sparse Grids
    2023/05/23 by Yadav, Mohit, Sheldon, Daniel, Musco, Cameron · 1 citation
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  21. DISCount: Counting in Large Image Collections with Detector-Based Importance Sampling
    2023/06/05 by Perez, Gustavo, Maji, Subhransu, Sheldon, Daniel · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  22. Consensus-Driven Active Model Selection
    2025/07/31 by Kay, Justin, Van Horn, Grant, Maji, Subhransu +2 · 2 citations
    #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)