44 citations · 199 across the 22 of their papers we have counts for
3 papers · 1 filter
Hierarchical Optimal Transport for Multimodal Distribution Alignment
John Lee, Max Dabagia, Eva L. Dyer +1
In many machine learning applications, it is necessary to meaningfully aggregate, through alignment, different but related datasets. Optimal transport (OT)-based approaches pose al…
Convex Relaxation Regression: Black-Box Optimization of Smooth Functions by Learning Their Convex Envelopes
Mohammad Gheshlaghi Azar, Eva Dyer, Konrad Kording
Finding efficient and provable methods to solve non-convex optimization problems is an outstanding challenge in machine learning and optimization theory. A popular approach used to…
oASIS: Adaptive Column Sampling for Kernel Matrix Approximation
Raajen Patel, Thomas A. Goldstein, Eva L. Dyer +2
Kernel matrices (e.g. Gram or similarity matrices) are essential for many state-of-the-art approaches to classification, clustering, and dimensionality reduction. For large dataset…