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state-of-the-art-result-for-machine-learning-problems

by RedditSota

This repository provides state of the art (SoTA) results for all machine learning problems. We do ou...

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State-of-the-art result for all Machine Learning Problems

LAST UPDATE: 20th Februray 2019

NEWS: I am looking for a Collaborator esp who does research in NLP, Computer Vision and Reinforcement learning. If you are not a researcher, but you are willing, contact me. Email me: [email protected]

This repository provides state-of-the-art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately.

You can also submit this Google Form if you are new to Github.

This is an attempt to make one stop for all types of machine learning problems state of the art result. I can not do this alone. I need help from everyone. Please submit the Google form/raise an issue if you find SOTA result for a dataset. Please share this on Twitter, Facebook, and other social media.

This summary is categorized into:

Supervised Learning

NLP

1. Language Modelling

Research Paper Datasets Metric Source Code Year
Language Models are Unsupervised Multitask Learners

2. Machine Translation

Research Paper Datasets Metric Source Code Year
Understanding Back-Translation at Scale

3. Text Classification

Research Paper Datasets Metric Source Code Year
Learning Structured Text Representations Yelp Accuracy: 68.6

4. Natural Language Inference

Leader board:

Stanford Natural Language Inference (SNLI)

MultiNLI

Research Paper Datasets Metric Source Code Year
NATURAL LANGUAGE INFERENCE OVER INTERACTION SPACE Stanford Natural Language Inference (SNLI) Accuracy: 88.9 Tensorflow 2017
BERT-LARGE (ensemble) Multi-Genre Natural Language Inference (MNLI)

5. Question Answering

Leader Board

SQuAD

Research Paper Datasets Metric Source Code Year
BERT-LARGE (ensemble) The Stanford Question Answering Dataset

6. Named entity recognition

Research Paper Datasets Metric Source Code Year
Named Entity Recognition in Twitter using Images and Text Ritter

7. Abstractive Summarization

Research Paper Datasets Metric Source Code Year
Cutting-off redundant repeating generations for neural abstractive summarization
  • DUC-2004

  • Gigaword |

  • DUC-2004

    • ROUGE-1: 32.28
    • ROUGE-2: 10.54
    • ROUGE-L: 27.80
  • Gigaword

  • DUC-2004

  • Gigaword |

  • DUC-2004

    • ROUGE-1: 33.44
    • ROUGE-2: 10.84
    • ROUGE-L: 26.90
  • Gigaword

    • ROUGE-1: 35.88
    • ROUGE-2: 27.48
    • ROUGE-L: 33.29 | PyTorch | 2017

      8. Dependency Parsing

Research Paper Datasets Metric Source Code Year
Globally Normalized Transition-Based Neural Networks
  • Final CoNLL ’09 dependency parsing |
  • 94.08% UAS accurancy
  • 92.15% LAS accurancy |
  • SyntaxNet |
  • 2017

Computer Vision

1. Classification

Research Paper Datasets Metric Source Code Year
Dynamic Routing Between Capsules

2. Instance Segmentation

Research Paper Datasets Metric Source Code Year
Mask R-CNN

3. Visual Question Answering

Research Paper Datasets Metric Source Code Year
Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challenge
  • VQA |
  • Overall score: 69 |
  • NOT FOUND | 2017 |

4. Person Re-identification

Research Paper Datasets Metric Source Code Year
Random Erasing Data Augmentation

Speech

Speech SOTA

1. ASR

Research Paper Datasets Metric Source Code Year
The Microsoft 2017 Conversational Speech Recognition System

Semi-supervised Learning

Computer Vision

Research Paper Datasets Metric Source Code Year
DISTRIBUTIONAL SMOOTHINGWITH VIRTUAL ADVERSARIAL TRAINING

Unsupervised Learning

Computer Vision

1. Generative Model
Research Paper Datasets Metric Source Code Year
PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION Unsupervised CIFAR 10 Inception score: 8.80 Theano 2017

NLP

Machine Translation

Research Paper Datasets Metric Source Code Year
UNSUPERVISED MACHINE TRANSLATION USING MONOLINGUAL CORPORA ONLY

Transfer Learning

Research Paper Datasets Metric Source Code Year
One Model To Learn Them All
  • WMT EN → DE
  • WMT EN → FR (BLEU)
  • ImageNet (top-5 accuracy) |
  • BLEU: 21.2
  • BLEU:30.5
  • 86% |
  • Tensorflow | 2017 |

Reinforcement Learning

Research Paper Datasets Metric Source Code Year
Mastering the game of Go without human knowledge the game of Go ElO Rating: 5185

Email: [email protected]

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