Statistical Learning
Learning De-Biased Representations for Remote-Sensing Imagery
It is an unsupervised learning approach that can diversify minor class features based on the shared attributes with major classes, where the attributes are obtained by a simple step of clustering.
Model-Based Diffusion for Trajectory Optimization
Additionally, MBD's ability to integrate with data enhances its versatility and
Initializing Services in Interactive ML Systems for Diverse Users
This paper investigates ML systems serving a group of users, with multiple models/services, each aimed at specializing to a sub-group of users.
Functionally Constrained Algorithm Solves Convex Simple Bilevel Problems
Then we follow recent works to pursue the weak approximate solutions.
Understanding Generalizability of Diffusion Models Requires Rethinking the Hidden Gaussian Structure
Essentially, the score functions can be interpreted as a series of deep denoisers trained on various noise levels.
Flow Priors for Linear Inverse Problems via Iterative Corrupted Trajectory Matching
Tweedie's formula, we show that we can perform gradient steps to sequentially optimize these objectives.