Curriculum Learning

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An Empirical Exploration of Curriculum Learning for Neural Machine Translation

2 Nov 2018awslabs/sockeye

Machine translation systems based on deep neural networks are expensive to train.

CURRICULUM LEARNING MACHINE TRANSLATION

A Fully Progressive Approach to Single-Image Super-Resolution

9 Apr 2018fperazzi/proSR

Recent deep learning approaches to single image super-resolution have achieved impressive results in terms of traditional error measures and perceptual quality.

CURRICULUM LEARNING IMAGE SUPER-RESOLUTION SSIM SUPER RESOLUTION

Noisy Activation Functions

1 Mar 2016wojciechz/learning_to_execute

Common nonlinear activation functions used in neural networks can cause training difficulties due to the saturation behavior of the activation function, which may hide dependencies that are not visible to vanilla-SGD (using first order gradients only).

CURRICULUM LEARNING

Learning to Execute

17 Oct 2014wojciechz/learning_to_execute

Recurrent Neural Networks (RNNs) with Long Short-Term Memory units (LSTM) are widely used because they are expressive and are easy to train.

CURRICULUM LEARNING LEARNING TO EXECUTE

Feedback Network for Image Super-Resolution

CVPR 2019 Paper99/SRFBN_CVPR19

In this paper, we propose an image super-resolution feedback network (SRFBN) to refine low-level representations with high-level information.

CURRICULUM LEARNING IMAGE SUPER-RESOLUTION SUPER RESOLUTION

Amharic Abstractive Text Summarization

30 Mar 2020theamrzaki/text_summurization_abstractive_methods

Text Summarization is the task of condensing long text into just a handful of sentences.

ABSTRACTIVE TEXT SUMMARIZATION CURRICULUM LEARNING

Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks

NeurIPS 2015 theamrzaki/text_summurization_abstractive_methods

Recurrent Neural Networks can be trained to produce sequences of tokens given some input, as exemplified by recent results in machine translation and image captioning.

CONSTITUENCY PARSING CURRICULUM LEARNING IMAGE CAPTIONING SPEECH RECOGNITION

Agent Environment Cycle Games

28 Sep 2020PettingZoo-Team/PettingZoo

Partially Observable Stochastic Games (POSGs), are the most general model of games used in Multi-Agent Reinforcement Learning (MARL), modeling actions and observations as happening sequentially for all agents.

CURRICULUM LEARNING MULTI-AGENT REINFORCEMENT LEARNING

CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition

CVPR 2020 HuangYG123/CurricularFace

As an emerging topic in face recognition, designing margin-based loss functions can increase the feature margin between different classes for enhanced discriminability.

CURRICULUM LEARNING FACE RECOGNITION

Language Generation with Recurrent Generative Adversarial Networks without Pre-training

5 Jun 2017amirbar/rnn.wgan

Generative Adversarial Networks (GANs) have shown great promise recently in image generation.

CURRICULUM LEARNING TEXT GENERATION