3 papers
cs.LG2026
When Softmax Fails at the Top: Extreme Value Corrections for InfoNCE
Melihcan Erol, Suat Evren, Oktay Ozel +3
InfoNCE is the standard contrastive learning objective, but its softmax form is not only a computational convenience: it also encodes a statistical assumption about how the top-sco…
cs.LG2024
Operator SVD with Neural Networks via Nested Low-Rank Approximation
J. Jon Ryu, Xiangxiang Xu, H. S. Melihcan Erol +3
Computing eigenvalue decomposition (EVD) of a given linear operator, or finding its leading eigenvalues and eigenfunctions, is a fundamental task in many machine learning and scien…
math.ST2024
On Semi-supervised Estimation of Discrete Distributions under f-divergences
Hasan Sabri Melihcan Erol, Lizhong Zheng
We study the problem of estimating the joint probability mass function (pmf) over two random variables. In particular, the estimation is based on the observation of samples con…