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Adversarial Example Games
The existence of adversarial examples capable of fooling trained neural ...
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Real World Games Look Like Spinning Tops
This paper investigates the geometrical properties of real world games (...
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Minimax Theorem for Latent Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets
Adversarial training, a special case of multi-objective optimization, is...
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Accelerating Smooth Games by Manipulating Spectral Shapes
We use matrix iteration theory to characterize acceleration in smooth ga...
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Finite Regret and Cycles with Fixed Step-Size via Alternating Gradient Descent-Ascent
Gradient descent is arguably one of the most popular online optimization...
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Lower Bounds and Conditioning of Differentiable Games
Many recent machine learning tools rely on differentiable game formulati...
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A Tight and Unified Analysis of Extragradient for a Whole Spectrum of Differentiable Games
We consider differentiable games: multi-objective minimization problems,...
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A Closer Look at the Optimization Landscapes of Generative Adversarial Networks
Generative adversarial networks have been very successful in generative ...
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Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics
A recent strategy to circumvent the exploding and vanishing gradient pro...
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Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates
Recent works have shown that stochastic gradient descent (SGD) achieves ...
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Implicit Regularization of Discrete Gradient Dynamics in Deep Linear Neural Networks
When optimizing over-parameterized models, such as deep neural networks,...
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Reducing Noise in GAN Training with Variance Reduced Extragradient
Using large mini-batches when training generative adversarial networks (...
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Negative Momentum for Improved Game Dynamics
Games generalize the optimization paradigm by introducing different obje...
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Frank-Wolfe Splitting via Augmented Lagrangian Method
Minimizing a function over an intersection of convex sets is an importan...
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Adaptive Three Operator Splitting
We propose and analyze a novel adaptive step size variant of the Davis-Y...
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A Variational Inequality Perspective on Generative Adversarial Nets
Stability has been a recurrent issue in training generative adversarial ...
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Parametric Adversarial Divergences are Good Task Losses for Generative Modeling
Generative modeling of high dimensional data like images is a notoriousl...
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Frank-Wolfe Algorithms for Saddle Point Problems
We extend the Frank-Wolfe (FW) optimization algorithm to solve constrain...
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