Daniel Sheldon

1. AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data
   2022/01/29 by Ryan M. McKenna, Brett Mullins, McKenna, Ryan +5 · 12 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. Winning the NIST Contest: A scalable and general approach to differentially private synthetic data
   2021/08/11 by Ryan M. McKenna, Gerome Miklau, McKenna, Ryan +3 · 8 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)
3. 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
4. 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
5. Parametric Bootstrap for Differentially Private Confidence Intervals
   2020/06/14 by Cecilia Ferrando, Shufan Wang, Ferrando, Cecilia +3 · 2 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
6. 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
7. Consistently Estimating Markov Chains with Noisy Aggregate Data
   2016/04/14 by Garrett Bernstein, Daniel Sheldon, Bernstein, Garrett +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
8. Differentially Private Bayesian Inference for Exponential Families
   2018/09/06 by Garrett Bernstein, Daniel Sheldon, Bernstein, Garrett +1 · 2 citations
   Computer Science · Mathematics · #Privacy-Preserving Technologies in Data #Statistical Methods and Bayesian Inference #Random Matrices and Applications
9. Variational Marginal Particle Filters
   2021/09/30 by Jinlin Lai, Justin Domke, Lai, Jinlin +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
10. Joint Selection: Adaptively Incorporating Public Information for Private Synthetic Data
    2024/03/12 by Miguel Fuentes, Fuentes, Miguel, Brett Mullins +7 · 1 citation
    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
11. Scalable Model-Assisted Multi-Target Estimation in Large Image Collections
    2026/07/20 by Max Hamilton, Jinlin Lai, Daniel Sheldon +1
    #cs.CV