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04/15/2023
Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis
We study finite-sum distributed optimization problems with n-clients und...
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05/17/2022
On the Convergence of Policy in Unregularized Policy Mirror Descent
In this short note, we give the convergence analysis of the policy in th...
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01/08/2022
Global Convergence Analysis of Deep Linear Networks with A One-neuron Layer
In this paper, we follow Eftekhari's work to give a non-local convergenc...
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10/16/2021
Greedy and Random Broyden's Methods with Explicit Superlinear Convergence Rates in Nonlinear Equations
In this paper, we propose the greedy and random Broyden's method for sol...
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05/09/2021
Directional Convergence Analysis under Spherically Symmetric Distribution
We consider the fundamental problem of learning linear predictors (i.e.,...
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04/12/2021
Meta-Regularization: An Approach to Adaptive Choice of the Learning Rate in Gradient Descent
We propose Meta-Regularization, a novel approach for the adaptive choice...
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09/16/2020
Landscape of Sparse Linear Network: A Brief Investigation
Network pruning, or sparse network has a long history and practical sign...
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08/30/2020
Optimal Quantization for Batch Normalization in Neural Network Deployments and Beyond
Quantized Neural Networks (QNNs) use low bit-width fixed-point numbers f...
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09/07/2019
Towards Understanding the Importance of Noise in Training Neural Networks
Numerous empirical evidence has corroborated that the noise plays a cruc...
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08/18/2019
