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Implicit Interpretation of Importance Weight Aware Updates
Due to its speed and simplicity, subgradient descent is one of the most used optimization algorithms in convex machine learning algorithms.
Generalized Implicit Follow-The-Regularized-Leader
We propose a new class of online learning algorithms, generalized implicit Follow-The-Regularized-Leader (FTRL), that expands the scope of FTRL framework.
Implicit Parameter-free Online Learning with Truncated Linear Models
Parameter-free algorithms are online learning algorithms that do not require setting learning rates.
Better Parameter-free Stochastic Optimization with ODE Updates for Coin-Betting
Parameter-free stochastic gradient descent (PFSGD) algorithms do not require setting learning rates while achieving optimal theoretical performance.
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