机器学习论文大全,涵盖深度学习、计算机视觉、分类、聚类、机器人学等

2019 年 1 月 4 日 专知
机器学习论文大全,涵盖深度学习、计算机视觉、分类、聚类、机器人学等

【导读】机器学习论文大全,涵盖深度学习、计算机视觉、分类、聚类、机器人学等等

https://github.com/mlreview/machine-learning-surveys


Machine Learning Surveys

Table of Contents

  • Active Learning

  • Bioinformatics

  • Classification

  • Clustering

  • Computer Vision

  • Deep Learning

  • Dimensionality Reduction

  • Ensemble Learning

  • Metric Learning

  • Monte Carlo

  • Multi-Armed Bandit

  • Multi-View Learning

  • Natural Language Processing

  • Physics

  • Probabilistic Models

  • Recommender Systems

  • Reinforcement Learning

  • Robotics

  • Semi-Supervised Learning

  • Submodular Functions

  • Transfer Learning

  • Unsupervised Learning

Active Learning

  • Active Learning Literature Survey (2010) [B Settles] [67pp]

Bioinformatics

  • Introduction to Bioinformatics (2013) [A Lesk] [255pp] 

    📚
  • Bioinformatics - an Introduction for Computer Scientists (2004) [J Cohen] [37pp]

  • Opportunities and Obstacles for Deep Learning in Biology and Medicine (2017) [T Ching, DS Himmelstein, BK Beaulieu-jones] [102pp]

Classification

  • Supervised Machine Learning: A Review of Classification Techniques (2007) [SB Kotsiantis, I Zaharakis, P Pintelas] [20pp]

  • Web Page Classification: Features and Algorithms (2009) [X Qi, BD Davison] [31pp]

Clustering

  • Data Clustering: 50 Years Beyond K-Means (2010) [AK Jain] [16pp] ⭐

  • A Tutorial on Spectral Clustering (2007) [U VON Luxburg] [32pp]

  • Handbook of Blind Source Separation: Independent Component Analysis and Applications (2010) [P Comon, C Jutten] [65pp] 

    📚
  • Survey of Clustering Algorithms (2005) [R Xu, D Wunsch] [34pp]

  • A Survey of Clustering Data Mining Techniques (2006) [P Berkhin] [56pp]

  • Clustering (2008) [R Xu, D Wunsch] [341pp] 

    📚

Computer Vision

  • Pedestrian Detection: An Evaluation of the State of the Art (2012) [P Dollar, C Wojek, B Schiele] [19pp] ⭐

  • Computer Vision: Algorithms and Applications (2010) [R Szeliski] [874pp] 

    📚

     ⭐

  • A Survey of Appearance Models in Visual Object Tracking (2013) [X Li] [42pp] ⭐

  • Object Tracking: A Survey (2006) [A Yilmaz] [45pp]

  • Head Pose Estimation in Computer Vision: A Survey (2009) [E Murphy-chutorian, MM Trivedi] [20pp]

  • A Survey of Recent Advances in Face Detection (2010) [C Zhang, Z Zhang] [17pp]

  • Monocular Model-Based 3d Tracking of Rigid Objects: A Survey (2005) [V Lepetit] [91pp]

  • A Survey on Face Detection in the Wild: Past, Present and Future (2015) [S Zafeiriou, C Zhang, Z Zhang] [50pp]

  • A Review on Deep Learning Techniques Applied to Semantic Segmentation (2017) [A Garcia-garcia, S Orts-escolano] [23pp]

  • Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art (2017) [D Russo, B VAN Roy, A Kazerouni, I Osband] [67pp]

  • Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art (2017) [J Janai, F Güney, A Behl, A Geiger] [14pp]

Deep Learning

  • Deep Learning (2016) [IJ Goodfellow, Y Bengio, A Courville] [800pp] 

    📚

     ⭐⭐

  • Deep Learning in Neural Networks: An Overview (2015) [J Schmidhuber] [88pp] ⭐⭐

  • Learning Deep Architectures for Ai (2009) [Y Bengio] [71pp] ⭐

  • Tutorial on Variational Autoencoders (2016) [C Doersch] [65pp] ⭐

  • Deep Reinforcement Learning: An Overview (2017) [ Y Li] [30pp]

  • NIPS 2016 Tutorial: Generative Adversarial Networks (2016) [I Goodfellow] [57pp]

  • Opportunities and Obstacles for Deep Learning in Biology and Medicine (2017) [T Ching, DS Himmelstein, BK Beaulieu-jones] [102pp]

  • A Review on Deep Learning Techniques Applied to Semantic Segmentation (2017) [A Garcia-garcia, S Orts-escolano] [23pp]

  • Deep Learning for Video Game Playing (2017) [N Justesen, P Bontrager, J Togelius, S Risi] [16pp]

  • Deep Learning Techniques for Music Generation (2017) [JP Briot, G Hadjeres, F PACHET ] [108pp]

Dimensionality Reduction

  • Dimensionality Reduction: A Comparative Review (2009) [L VAN DER Maaten, E Postma] [36pp]

  • Dimension Reduction: A Guided Tour (2010) [CJC Burges] [64pp]

Ensemble Learning

  • Ensemble Methods: Foundations and Algorithms (2012) [ZH Zhou] [234pp]

  • Ensemble Approaches for Regression: A Survey (2012) [J Mendes-moreira, C Soares, AM Jorge] [40pp]

Metric Learning

  • A Survey on Metric Learning for Feature Vectors and Structured Data (2014) [A Bellet] [59pp]

  • Metric Learning: A Survey (2012) [B Kulis] [80pp]

Monte Carlo

  • Geometric Integrators and the Hamiltonian Monte Carlo Method (2017) [N Bou-rabee, JM Sanz-serna] [92pp]

Multi-Armed Bandit

  • Regret Analysis of Stochastic and Nonstochastic Multi-Armed Bandit Problems (2012) [S Bubeck, N Cesa-bianchi] [130pp] ⭐

  • A Survey of Online Experiment Design With the Stochastic Multi-Armed Bandit (2015) [G Burtini, J Loeppky, R Lawrence] [49pp]

  • A Tutorial on Thompson Sampling (2017) [D Russo, B VAN Roy, A Kazerouni, I Osband] [39pp]

Multi-View Learning

  • A Survey on Multi-View Learning (2013) [C Xu] [59pp]

  • A Survey of Multi-View Machine Learning (2013) [S Sun] [13pp]

Natural Language Processing

  • A Primer on Neural Network Models for Natural Language Processing (2016) [Y Goldberg] [76pp] ⭐

  • Probabilistic Topic Models (2012) [DM Blei] [16pp] ⭐

  • Natural Language Processing (Almost) From Scratch (2011) [R Collobert] [45pp] ⭐

  • Opinion Mining and Sentiment Analysis (2008) [B Pang, L Lee] [94pp] ⭐

  • Survey of the State of the Art in Natural Language Generation: Core Tasks, Applications and Evaluation (2017) [A Gatt, E Krahmer] [111pp] ⭐

  • Opinion Mining and Sentiment Analysis (2012) [B Liu, L Zhang] [38pp]

  • Neural Machine Translation and Sequence-to-Sequence Models: A Tutorial (2017) [G Neubig] [65pp]

  • Machine Learning in Automated Text Categorization (2002) [F Sebastiani] [55pp]

  • Statistical Machine Translation (2009) [P Koehn] [149pp] 

    📚
  • Statistical Machine Translation (2008) [A Lopez] [55pp]

  • Machine Transliteration Survey (2011) [S Karimi, F Scholer, A Turpin] [46pp]

  • Neural Machine Translation and Sequence-to-Sequence Models: A Tutorial (2017) [G Neubig] [57pp]

Physics

  • Machine Learning & Artificial Intelligence in the Quantum Domain (2017) [V Dunjko, HJ Briegel] [106pp]

Probabilistic Models

  • Graphical Models, Exponential Families, and Variational Inference (2008) [MJ Wainwright, MI Jordan] [305pp]

  • An Introduction to Conditional Random Fields (2011) [C Sutton] [90pp]

  • An Introduction to Conditional Random Fields for Relational Learning (2006) [C Sutton] [35pp]

  • An Introduction to Mcmc for Machine Learning (2003) [C Andrieu, N DE Freitas, A Doucet, MI Jordan] [39pp]

  • Introduction to Probability Models (2014) [SM Ross] [801pp] 

    📚

Recommender Systems

  • Introduction to Recommender Systems Handbook (2011) [F Ricci, L Rokach, B Shapira] [845pp] 

    📚

     ⭐

  • Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions (2008) [G Adomavicius, A Tuzhilin] [43pp] ⭐

  • Matrix Factorization Techniques for Recommender Systems (2009) [Y Koren, R Bell, C Volinsky] [8pp] ⭐

  • A Survey of Collaborative Filtering Techniques (2009) [X Su, TM Khoshgoftaar] [20pp]

Reinforcement Learning

  • Reinforcement Learning in Robotics: A Survey (2013) [J Kober, JA Bagnell, J Peterskober] [74pp] ⭐

  • Deep Reinforcement Learning: An Overview (2017) [ Y Li] [30pp]

  • Reinforcement Learning: An Introduction (2016) [RS Sutton, AG Barto] [398pp] 

    📚
  • Bayesian Reinforcement Learning: A Survey (2016) [M Ghavamzadeh, S Mannor, J Pineau] [147pp]

  • Reinforcement Learning: A Survey (1996) [LP Kaelbling, ML Littman, AW Moore] [49pp]

  • Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art (2017) [J Janai, F Güney, A Behl, A Geiger] [14pp]

  • Deep Learning for Video Game Playing (2017) [N Justesen, P Bontrager, J Togelius, S Risi] [16pp]

Robotics

  • Reinforcement Learning in Robotics: A Survey (2013) [J Kober, JA Bagnell, J Peterskober] [74pp] ⭐

  • A Survey of Robot Learning From Demonstration (2009) [BD Argall, S Chernova, M Veloso] [15pp]

Semi-Supervised Learning

  • Semi-Supervised Learning Literature Survey (2008) [X Zhu] [59pp]

Submodular Functions

  • Learning With Submodular Functions: A Convex Optimization Perspective (2013) [F Bach] [173pp]

  • Submodular Function Maximization (2012) [A Krause, D Golovin] [28pp]

Transfer Learning

  • A Survey on Transfer Learning (2010) [SJ Pan, Q Yang] [15pp] ⭐

  • Transfer Learning for Reinforcement Learning Domains: A Survey (2009) [ME Taylor, P Stone] [53pp]

Unsupervised Learning

  • Tutorial on Variational Autoencoders (2016) [C Doersch] [65pp] ⭐






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