71 citations · 337 across the 32 of their papers we have counts for
33 papers
DISCount: Counting in Large Image Collections with Detector-Based Importance Sampling
Gustavo Perez, Subhransu Maji, Daniel Sheldon
Many modern applications use computer vision to detect and count objects in massive image collections. However, when the detection task is very difficult or in the presence of doma…
Kernel Interpolation with Sparse Grids
Mohit Yadav, Daniel Sheldon, Cameron Musco
Structured kernel interpolation (SKI) accelerates Gaussian process (GP) inference by interpolating the kernel covariance function using a dense grid of inducing points, whose corre…
Sample Average Approximation for Black-Box VI
Javier Burroni, Justin Domke, Daniel Sheldon
We present a novel approach for black-box VI that bypasses the difficulties of stochastic gradient ascent, including the task of selecting step-sizes. Our approach involves using a…
Automatically Marginalized MCMC in Probabilistic Programming
Jinlin Lai, Javier Burroni, Hui Guan +1
Hamiltonian Monte Carlo (HMC) is a powerful algorithm to sample latent variables from Bayesian models. The advent of probabilistic programming languages (PPLs) frees users from wri…
AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data
Ryan McKenna, Brett Mullins, Daniel Sheldon +1
We propose AIM, a new algorithm for differentially private synthetic data generation. AIM is a workload-adaptive algorithm within the paradigm of algorithms that first selects a se…
Relaxed Marginal Consistency for Differentially Private Query Answering
Ryan McKenna, Siddhant Pradhan, Daniel Sheldon +1
Many differentially private algorithms for answering database queries involve a step that reconstructs a discrete data distribution from noisy measurements. This provides consisten…