1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2023
Implicit Interpretation of Importance Weight Aware Updates
Keyi Chen, Francesco Orabona
Due to its speed and simplicity, subgradient descent is one of the most used optimization algorithms in convex machine learning algorithms. However, tuning its learning rate is pro…
cs.LG2023
Generalized Implicit Follow-The-Regularized-Leader
Keyi Chen, Francesco Orabona
We propose a new class of online learning algorithms, generalized implicit Follow-The-Regularized-Leader (FTRL), that expands the scope of FTRL framework. Generalized implicit FTRL…
cs.LG2022★ 1 cited
Implicit Parameter-free Online Learning with Truncated Linear Models
Keyi Chen, Ashok Cutkosky, Francesco Orabona
Parameter-free algorithms are online learning algorithms that do not require setting learning rates. They achieve optimal regret with respect to the distance between the initial po…