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Poster
Mon 9:00 Vector-output ReLU Neural Network Problems are Copositive Programs: Convex Analysis of Two Layer Networks and Polynomial-time Algorithms
Arda Sahiner · Tolga Ergen · John M Pauly · Mert Pilanci
Spotlight
Mon 12:15 On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers
Kenji Kawaguchi
Poster
Mon 17:00 Benefit of deep learning with non-convex noisy gradient descent: Provable excess risk bound and superiority to kernel methods
Taiji Suzuki · Akiyama Shunta
Poster
Mon 17:00 The Role of Momentum Parameters in the Optimal Convergence of Adaptive Polyak's Heavy-ball Methods
Wei Tao · sheng long · Gaowei Wu · Qing Tao
Poster
Tue 9:00 On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers
Kenji Kawaguchi
Poster
Tue 9:00 NOVAS: Non-convex Optimization via Adaptive Stochastic Search for End-to-end Learning and Control
Ioannis Exarchos · Marcus A Pereira · Ziyi Wang · Evangelos Theodorou
Spotlight
Tue 12:40 Implicit Convex Regularizers of CNN Architectures: Convex Optimization of Two- and Three-Layer Networks in Polynomial Time
Tolga Ergen · Mert Pilanci
Poster
Tue 17:00 Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization
Chin-Wei Huang · Tian Qi Chen · Christos Tsirigotis · Aaron Courville
Poster
Tue 17:00 Implicit Convex Regularizers of CNN Architectures: Convex Optimization of Two- and Three-Layer Networks in Polynomial Time
Tolga Ergen · Mert Pilanci
Poster
Wed 1:00 Byzantine-Resilient Non-Convex Stochastic Gradient Descent
Zeyuan Allen-Zhu · Faeze Ebrahimianghazani · Jerry Li · Dan Alistarh
Spotlight
Wed 5:15 Benefit of deep learning with non-convex noisy gradient descent: Provable excess risk bound and superiority to kernel methods
Taiji Suzuki · Akiyama Shunta
Poster
Wed 9:00 Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization
Alexander Korotin · Lingxiao Li · Justin Solomon · Evgeny Burnaev