no code implementations • 23 Nov 2023 • Gilad Yehudai, Alon Cohen, Amit Daniely, Yoel Drori, Tomer Koren, Mariano Schain
We introduce a novel dynamic learning-rate scheduling scheme grounded in theory with the goal of simplifying the manual and time-consuming tuning of schedules in practice.
2 code implementations • 17 Feb 2023 • Jiaxi Tang, Yoel Drori, Daryl Chang, Maheswaran Sathiamoorthy, Justin Gilmer, Li Wei, Xinyang Yi, Lichan Hong, Ed H. Chi
Recommender systems play an important role in many content platforms.
no code implementations • NeurIPS 2021 • Alon Cohen, Amit Daniely, Yoel Drori, Tomer Koren, Mariano Schain
In the general non-convex smooth optimization setting, we give a simple and efficient algorithm that requires $O( \sigma^2/\epsilon^4 + \tau/\epsilon^2 )$ steps for finding an $\epsilon$-stationary point $x$, where $\tau$ is the \emph{average} delay $\smash{\frac{1}{T}\sum_{t=1}^T d_t}$ and $\sigma^2$ is the variance of the stochastic gradients.
no code implementations • ICML 2020 • Yoel Drori, Ohad Shamir
We study the iteration complexity of stochastic gradient descent (SGD) for minimizing the gradient norm of smooth, possibly nonconvex functions.
no code implementations • ACL 2019 • Genady Beryozkin, Yoel Drori, Oren Gilon, Tzvika Hartman, Idan Szpektor
We study a variant of domain adaptation for named-entity recognition where multiple, heterogeneously tagged training sets are available.
1 code implementation • 15 Mar 2018 • Yoel Drori, Adrien B. Taylor
We describe a novel constructive technique for devising efficient first-order methods for a wide range of large-scale convex minimization settings, including smooth, non-smooth, and strongly convex minimization.
Optimization and Control Numerical Analysis