3 papers
cs.LG2026
Radial-VCReg: More Informative Representation Learning Through Radial Gaussianization
Yilun Kuang, Yash Dagade, Deep Chakraborty +4
Self-supervised learning aims to learn maximally informative representations, but explicit information maximization is hindered by the curse of dimensionality. Existing methods lik…
cs.LG2025
Improving Pre-trained Self-Supervised Embeddings Through Effective Entropy Maximization
Deep Chakraborty, Yann LeCun, Tim G. J. Rudner +1
A number of different architectures and loss functions have been applied to the problem of self-supervised learning (SSL), with the goal of developing embeddings that provide the b…
math.ST2025
On the admissibility of bounds on the mean of discrete, scalar probability distributions from an iid sample
Erik Learned-Miller
We address the problem of producing a lower bound for the mean of a discrete probability distribution, with known support over a finite set of real numbers, from an iid sample of t…