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Poster
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Wed 18:30
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Gradient descent GAN optimization is locally stable
Vaishnavh Nagarajan · J. Zico Kolter
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Poster
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Mon 18:30
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Large-Scale Quadratically Constrained Quadratic Program via Low-Discrepancy Sequences
Kinjal Basu · Ankan Saha · Shaunak Chatterjee
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Poster
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Mon 18:30
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Influence Maximization with ε-Almost Submodular Threshold Functions
Qiang Li · Wei Chen · Institute of Computing Xiaoming Sun · Institute of Computing Jialin Zhang
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Poster
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Tue 18:30
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Deep Mean-Shift Priors for Image Restoration
Siavash Arjomand Bigdeli · Matthias Zwicker · Paolo Favaro · Meiguang Jin
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Poster
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Wed 18:30
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Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent
Xiangru Lian · Ce Zhang · Huan Zhang · Cho-Jui Hsieh · Wei Zhang · Ji Liu
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Poster
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Tue 18:30
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Gradient Descent Can Take Exponential Time to Escape Saddle Points
Simon Du · Chi Jin · Jason D Lee · Michael Jordan · Aarti Singh · Barnabas Poczos
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Poster
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Tue 18:30
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Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural Networks
Ziming Zhang · Matthew Brand
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Poster
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Tue 18:30
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Finite sample analysis of the GTD Policy Evaluation Algorithms in Markov Setting
Yue Wang · Wei Chen · Yuting Liu · Zhi-Ming Ma · Tie-Yan Liu
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Poster
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Wed 18:30
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Multi-Information Source Optimization
Matthias Poloczek · Jialei Wang · Peter Frazier
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Poster
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Wed 18:30
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Train longer, generalize better: closing the generalization gap in large batch training of neural networks
Elad Hoffer · Itay Hubara · Daniel Soudry
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Poster
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Mon 18:30
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Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds
Yuanyuan Liu · Fanhua Shang · James Cheng · Hong Cheng · Licheng Jiao
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Poster
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Mon 18:30
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On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks
Arturs Backurs · Piotr Indyk · Ludwig Schmidt
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