5 papers
Wasserstein convergence rates for empirical measures of point processes
Dongzhou Huang, Tianyi Jiang, Haonan Wang
In this paper, we establish upper and lower bounds on the convergence rate of empirical measures of point processes under the Wasserstein distance. To this end, we first introduce…
Iterative Data-Consistent Inversion with Multiple Push-forward Constraints
Tianyi Jiang, Troy Butler, Timothy Wildey +2
A foundational challenge in uncertainty quantification involves estimating a probability measure on the space of uncertain parameters such that its push-forward through a computati…
Unified Communication Compression Beyond Global Error Bounds for Distributed Nonconvex Optimization
Haonan Wang, Minghui Liwang, Yiguang Hong +2
In this paper, we propose a unified compression algorithm for distributed nonconvex opitmization with both the locally- and globally-bounded communication compressors, including 1-…
Heterogeneous Distributed Zeroth-Order Nonconvex Optimization with Communication Compression
Haonan Wang, Xinlei Yi, Yiguang Hong +1
Distributed zeroth-order optimization is increasingly applied in heterogeneous scenarios where agents possess distinct data distributions and objectives. This heterogeneity poses f…
Compressed Zeroth-Order Algorithm for Stochastic Distributed Nonconvex Optimization
Haonan Wang, Xinlei Yi, Yiguang Hong
This paper studies the stochastic distributed nonconvex optimization problem over a network of agents, where agents only access stochastic zeroth-order information about their loca…