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Poster
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Thu 12:00
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Randomized Block-Diagonal Preconditioning for Parallel Learning
Celestine Mendler-Dünner · Aurelien Lucchi
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Poster
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Tue 18:00
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Hybrid Stochastic-Deterministic Minibatch Proximal Gradient: Less-Than-Single-Pass Optimization with Nearly Optimal Generalization
Pan Zhou · Xiao-Tong Yuan
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Tutorial
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Mon 5:00
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Parameter-free Online Optimization
Francesco Orabona · Ashok Cutkosky
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Poster
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Thu 6:00
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Scalable Differentiable Physics for Learning and Control
Yi-Ling Qiao · Junbang Liang · Vladlen Koltun · Ming Lin
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Poster
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Thu 12:00
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The Complexity of Finding Stationary Points with Stochastic Gradient Descent
Yoel Drori · Ohad Shamir
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Workshop
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Sat 6:00
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7th ICML Workshop on Automated Machine Learning (AutoML 2020)
Frank Hutter · Joaquin Vanschoren · Marius Lindauer · Charles Weill · Katharina Eggensperger · Matthias Feurer · Matthias Feurer
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Poster
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Tue 12:00
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Restarted Bayesian Online Change-point Detector achieves Optimal Detection Delay
REDA ALAMI · Odalric-Ambrym Maillard · Raphaël Féraud
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Poster
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Thu 6:00
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Performative Prediction
Juan Perdomo · Tijana Zrnic · Celestine Mendler-Dünner · Moritz Hardt
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Poster
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Thu 6:00
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Multi-Task Learning with User Preferences: Gradient Descent with Controlled Ascent in Pareto Optimization
Debabrata Mahapatra · Vaibhav Rajan
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Poster
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Tue 18:00
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Rate-distortion optimization guided autoencoder for isometric embedding in Euclidean latent space
Keizo Kato · Jing Zhou · Tomotake Sasaki · Akira Nakagawa
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Poster
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Wed 9:00
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A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth
Yiping Lu · Chao Ma · Yulong Lu · Jianfeng Lu · Lexing Ying
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Poster
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Wed 13:00
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Convergence of a Stochastic Gradient Method with Momentum for Non-Smooth Non-Convex Optimization
Vien Mai · Mikael Johansson
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