Type AdditiveSwapRegretOptimizer
Namespace tensorflow.contrib.constrained_optimization
Parent _SwapRegretOptimizer
Interfaces IAdditiveSwapRegretOptimizer
A `ConstrainedOptimizer` based on swap-regret minimization. This `ConstrainedOptimizer` uses the given `tf.compat.v1.train.Optimizer`s to
jointly
minimize over the model parameters, and maximize over constraint/objective
weight matrix (the analogue of Lagrange multipliers), with the latter
maximization using additive updates and an algorithm that minimizes swap
regret. For more specifics, please refer to: > Cotter, Jiang and Sridharan. "Two-Player Games for Efficient Non-Convex
> Constrained Optimization".
> [https://arxiv.org/abs/1804.06500](https://arxiv.org/abs/1804.06500) The formulation used by this optimizer can be found in Definition 2, and is
discussed in Section 4. It is most similar to Algorithm 2 in Section 4, with
the differences being that it uses `tf.compat.v1.train.Optimizer`s, instead of
SGD, for
the "inner" updates, and performs additive (instead of multiplicative) updates
of the stochastic matrix.