Optimization
Rethinking the Variational Interpretation of Accelerated Optimization Methods
The continuous-time model of Nesterov's momentum provides a thought-provoking perspective for understanding the nature of the acceleration phenomenon in convex
LASSIE: Learning Articulated Shapes from Sparse Image Ensemble via 3D Part Discovery Chun-Han Y ao 1 Wei-Chih Hung 2 Y uanzhen Li3 Michael Rubinstein 3
Moreover, each input image ensemble can contain animal instances with varying poses, backgrounds, illuminations, and textures. Our key insight is that 3D parts have much simpler shape compared to the overall animal and that they are robust w.r.t.
Fair Clustering Under a Bounded Cost
Clustering is a fundamental unsupervised learning problem where a dataset is partitioned into clusters that consist of nearby points in a metric space.
Convergence of adaptive algorithms for constrained weakly convex optimization
Adaptive first order methods have become a mainstay of neural network training in recent years.
Walking in the Shadow: A New Perspective on Descent Directions for Constrained Minimization
CG's primary direction of descent is
