
MetaRegularization: An Approach to Adaptive Choice of the Learning Rate in Gradient Descent
We propose MetaRegularization, a novel approach for the adaptive choice...
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Lower Complexity Bounds of FiniteSum Optimization Problems: The Results and Construction
The contribution of this paper includes two aspects. First, we study the...
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DIPPA: An improved Method for Bilinear Saddle Point Problems
This paper studies bilinear saddle point problems min_xmax_y g(x) + x^⊤A...
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Revisiting CoOccurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices
We study the streaming model for approximate matrix multiplication (AMM)...
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Optimal Quantization for Batch Normalization in Neural Network Deployments and Beyond
Quantized Neural Networks (QNNs) use low bitwidth fixedpoint numbers f...
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A Stochastic Proximal Point Algorithm for SaddlePoint Problems
We consider saddle point problems which objective functions are the aver...
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A General Analysis Framework of Lower Complexity Bounds for FiniteSum Optimization
This paper studies the lower bound complexity for the optimization probl...
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Interpolatron: Interpolation or Extrapolation Schemes to Accelerate Optimization for Deep Neural Networks
In this paper we explore acceleration techniques for large scale nonconv...
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Guangzeng Xie
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