34 citations · 60 across the 13 of their papers we have counts for
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cs.LG2021★ 3 cited
Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions
Arda Sahiner, Tolga Ergen, Batu Ozturkler +4
Generative Adversarial Networks (GANs) are commonly used for modeling complex distributions of data. Both the generators and discriminators of GANs are often modeled by neural netw…
cs.LG2021★ 1 cited
Training Quantized Neural Networks to Global Optimality via Semidefinite Programming
Burak Bartan, Mert Pilanci
Neural networks (NNs) have been extremely successful across many tasks in machine learning. Quantization of NN weights has become an important topic due to its impact on their ener…
cs.LG2021★ 5 cited
Neural Spectrahedra and Semidefinite Lifts: Global Convex Optimization of Polynomial Activation Neural Networks in Fully Polynomial-Time
Burak Bartan, Mert Pilanci
The training of two-layer neural networks with nonlinear activation functions is an important non-convex optimization problem with numerous applications and promising performance i…