L2 Regularization

21 papers with code • 0 benchmarks • 0 datasets

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Most implemented papers

Re-evaluating Continual Learning Scenarios: A Categorization and Case for Strong Baselines

GT-RIPL/Continual-Learning-Benchmark 30 Oct 2018

Continual learning has received a great deal of attention recently with several approaches being proposed.

Convolutional Neural Networks for Facial Expression Recognition

mgeezzyy/Facial-Expression-Recognition-2018 22 Apr 2017

We have developed convolutional neural networks (CNN) for a facial expression recognition task.

On Regularization Parameter Estimation under Covariate Shift

wmkouw/covshift-l2reg 31 Jul 2016

This paper identifies a problem with the usual procedure for L2-regularization parameter estimation in a domain adaptation setting.

Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World

sgarg87/neurogenesis_inspired_dictionary_learning 22 Jan 2017

In this paper, we focus on online representation learning in non-stationary environments which may require continuous adaptation of model architecture.

Collaboratively Weighting Deep and Classic Representation via L2 Regularization for Image Classification

zengsn/research 21 Feb 2018

We propose a deep collaborative weight-based classification (DeepCWC) method to resolve this problem, by providing a novel option to fully take advantage of deep features in classic machine learning.

Quantifying Generalization in Reinforcement Learning

openai/coinrun 6 Dec 2018

In this paper, we investigate the problem of overfitting in deep reinforcement learning.

What is the Effect of Importance Weighting in Deep Learning?

hajohajo/TrainingFrameworkTrackDNN 8 Dec 2018

Importance-weighted risk minimization is a key ingredient in many machine learning algorithms for causal inference, domain adaptation, class imbalance, and off-policy reinforcement learning.

Learning a smooth kernel regularizer for convolutional neural networks

rfeinman/SK-regularization 5 Mar 2019

We propose a smooth kernel regularizer that encourages spatial correlations in convolution kernel weights.

Understanding and Stabilizing GANs' Training Dynamics with Control Theory

taufikxu/GAN_PID 29 Sep 2019

There are existing efforts that model the training dynamics of GANs in the parameter space but the analysis cannot directly motivate practically effective stabilizing methods.

Data and Model Dependencies of Membership Inference Attack

SJabin/Data_Model_Dependencies_MIA 17 Feb 2020

Our results reveal the relationship between MIA accuracy and properties of the dataset and training model in use.