Curriculum Learning

108 papers with code • 0 benchmarks • 5 datasets

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Greatest papers with code

PLATO-2: Towards Building an Open-Domain Chatbot via Curriculum Learning

PaddlePaddle/PaddleNLP 30 Jun 2020

To build a high-quality open-domain chatbot, we introduce the effective training process of PLATO-2 via curriculum learning.

 Ranked #1 on Chatbot on 10 Monkey Species (using extra training data)

Chatbot Curriculum Learning

BeBold: Exploration Beyond the Boundary of Explored Regions

maximecb/gym-minigrid 15 Dec 2020

In this paper, we analyze the pros and cons of each method and propose the regulated difference of inverse visitation counts as a simple but effective criterion for IR.

Curriculum Learning Efficient Exploration +1

An Empirical Exploration of Curriculum Learning for Neural Machine Translation

awslabs/sockeye 2 Nov 2018

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

fperazzi/proSR 9 Apr 2018

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 +1

CARLS: Cross-platform Asynchronous Representation Learning System

tensorflow/neural-structured-learning 26 May 2021

In this work, we propose CARLS, a novel framework for augmenting the capacity of existing deep learning frameworks by enabling multiple components -- model trainers, knowledge makers and knowledge banks -- to concertedly work together in an asynchronous fashion across hardware platforms.

Curriculum Learning Representation Learning

Deep Multi-agent Reinforcement Learning for Highway On-Ramp Merging in Mixed Traffic

eleurent/highway-env 12 May 2021

On-ramp merging is a challenging task for autonomous vehicles (AVs), especially in mixed traffic where AVs coexist with human-driven vehicles (HDVs).

Autonomous Vehicles Curriculum Learning +1

Agent Environment Cycle Games

PettingZoo-Team/PettingZoo 28 Sep 2020

Partially Observable Stochastic Games (POSGs) are the most general and common model of games used in Multi-Agent Reinforcement Learning (MARL).

Curriculum Learning Multi-agent Reinforcement Learning

Feedback Network for Image Super-Resolution

Paper99/SRFBN_CVPR19 CVPR 2019

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

Noisy Activation Functions

wojciechz/learning_to_execute 1 Mar 2016

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

wojciechz/learning_to_execute 17 Oct 2014

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