Fast stochastic second-order method logarithmic in condition number von Ye, Haishan, Xie, Guangzeng, Luo, Luo, Zhang, Zhihua

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Complex contraction on trees without proof of correlation decay von Li, Liang, Xie, Guangzeng

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DIPPA: An improved Method for Bilinear Saddle Point Problems von Xie, Guangzeng, Han, Yuze, Zhang, Zhihua

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Lower Complexity Bounds of Finite-Sum Optimization Problems: The Results and Construction von Han, Yuze, Xie, Guangzeng, Zhang, Zhihua

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Complex contraction on trees without proof of correlation decay von Li, Liang, Xie, Guangzeng

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Near Optimal Stochastic Algorithms for Finite-Sum Unbalanced Convex-Concave Minimax Optimization von Luo, Luo, Xie, Guangzeng, Zhang, Tong, Zhang, Zhihua

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A General Analysis Framework of Lower Complexity Bounds for Finite-Sum Optimization von Xie, Guangzeng, Luo, Luo, Zhang, Zhihua

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Meta-Regularization: An Approach to Adaptive Choice of the Learning Rate in Gradient Descent von Xie, Guangzeng, Jin, Hao, Lin, Dachao, Zhang, Zhihua

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Finding the Near Optimal Policy via Adaptive Reduced Regularization in MDPs von Yang, Wenhao, Li, Xiang, Xie, Guangzeng, Zhang, Zhihua

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Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices von Luo, Luo, Chen, Cheng, Xie, Guangzeng, Ye, Haishan

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Lower Complexity Bounds of Finite-Sum Optimization Problems: The Results and Construction von Han, Yuze, Xie, Guangzeng, Zhang, Zhihua

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Optimal Quantization for Batch Normalization in Neural Network Deployments and Beyond von Lin, Dachao, Sun, Peiqin, Xie, Guangzeng, Zhou, Shuchang, Zhang, Zhihua

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A Stochastic Proximal Point Algorithm for Saddle-Point Problems von Luo, Luo, Chen, Cheng, Li, Yujun, Xie, Guangzeng, Zhang, Zhihua

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DIPPA: An improved Method for Bilinear Saddle Point Problems von Xie, Guangzeng, Han, Yuze, Zhang, Zhihua

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Interpolatron: Interpolation or Extrapolation Schemes to Accelerate Optimization for Deep Neural Networks von Xie, Guangzeng, Wang, Yitan, Zhou, Shuchang, Zhang, Zhihua

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Near Optimal Stochastic Algorithms for Finite-Sum Unbalanced Convex-Concave Minimax Optimization von Luo, Luo, Xie, Guangzeng, Zhang, Tong, Zhang, Zhihua

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A General Analysis Framework of Lower Complexity Bounds for Finite-Sum Optimization von Xie, Guangzeng, Luo, Luo, Zhang, Zhihua

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Meta-Regularization: An Approach to Adaptive Choice of the Learning Rate in Gradient Descent von Xie, Guangzeng, Jin, Hao, Lin, Dachao, Zhang, Zhihua

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Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices von Luo, Luo, Chen, Cheng, Xie, Guangzeng, Ye, Haishan

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Finding the Near Optimal Policy via Adaptive Reduced Regularization in MDPs von Yang, Wenhao, Li, Xiang, Xie, Guangzeng, Zhang, Zhihua

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