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02/10/2023
Feature Affinity Assisted Knowledge Distillation and Quantization of Deep Neural Networks on Label-Free Data
In this paper, we propose a feature affinity (FA) assisted knowledge dis...
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12/10/2020
Recurrence of Optimum for Training Weight and Activation Quantized Networks
Deep neural networks (DNNs) are quantized for efficient inference on res...
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11/23/2020
Learning Quantized Neural Nets by Coarse Gradient Method for Non-linear Classification
Quantized or low-bit neural networks are attractive due to their inferen...
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02/28/2020
Global Convergence and Geometric Characterization of Slow to Fast Weight Evolution in Neural Network Training for Classifying Linearly Non-Separable Data
In this paper, we study the dynamics of gradient descent in learning neu...
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03/13/2019
Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets
Training activation quantized neural networks involves minimizing a piec...
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11/05/2018
Non-ergodic Convergence Analysis of Heavy-Ball Algorithms
In this paper, we revisit the convergence of the Heavy-ball method, and ...
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09/23/2018
Adversarial Defense via Data Dependent Activation Function and Total Variation Minimization
We improve the robustness of deep neural nets to adversarial attacks by ...
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08/15/2018
Blended Coarse Gradient Descent for Full Quantization of Deep Neural Networks
Quantized deep neural networks (QDNNs) are attractive due to their much ...
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06/17/2018
Laplacian Smoothing Gradient Descent
We propose a very simple modification of gradient descent and stochastic...
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01/23/2018
On the complexity of convex inertial proximal algorithms
The inertial proximal gradient algorithm is efficient for the composite ...
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01/19/2018
BinaryRelax: A Relaxation Approach For Training Deep Neural Networks With Quantized Weights
We propose BinaryRelax, a simple two-phase algorithm, for training deep ...
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11/23/2017
Deep Learning for Real-Time Crime Forecasting and its Ternarization
Real-time crime forecasting is important. However, accurate prediction o...
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10/21/2017