A curated list of Machine Learning Surveys, Tutorials and Books.
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# Machine Learning Surveys

A curated list of Machine Learning related surveys, overviews and books.

If you want to contribute to this list (please do), check [How to Contribute](https://github.com/metrofun/machine-learning-surveys/wiki/How-to-Contribute-a-Paper) wiki or contact me [@ML_Review](https://twitter.com/ML_Review).

## Table of Contents

- [Active Learning](#active-learning)
- [Bioinformatics](#bioinformatics)
- [Classification](#classification)
- [Clustering](#clustering)
- [Computer Vision](#computer-vision)
- [Deep Learning](#deep-learning)
- [Dimensionality Reduction](#dimensionality-reduction)
- [Ensemble Learning](#ensemble-learning)
- [Metric Learning](#metric-learning)
- [Monte Carlo](#monte-carlo)
- [Multi-Armed Bandit](#multi-armed-bandit)
- [Multi-View Learning](#multi-view-learning)
- [Natural Language Processing](#natural-language-processing)
- [Physics](#physics)
- [Probabilistic Models](#probabilistic-models)
- [Recommender Systems](#recommender-systems)
- [Reinforcement Learning](#reinforcement-learning)
- [Robotics](#robotics)
- [Semi-Supervised Learning](#semi-supervised-learning)
- [Submodular Functions](#submodular-functions)
- [Transfer Learning](#transfer-learning)
- [Unsupervised Learning](#unsupervised-learning)


### Active Learning

* [Active Learning Literature Survey](https://scholar.google.com/scholar?q=%22Active%20Learning%20Literature%20Survey%22%20author%3A%22B%20Settles%22 "B Settles") (2010)
[B Settles] [67pp]  

### Bioinformatics

* [Introduction to Bioinformatics](https://scholar.google.com/scholar?q=%22Introduction%20to%20Bioinformatics%22%20author%3A%22A%20Lesk%22 "A Lesk") (2013)
[A Lesk] [255pp]  📚 
* [Bioinformatics - an Introduction for Computer Scientists](https://scholar.google.com/scholar?q=%22Bioinformatics%20-%20an%20Introduction%20for%20Computer%20Scientists%22%20author%3A%22J%20Cohen%22 "J Cohen") (2004)
[J Cohen] [37pp]  
* [Opportunities and Obstacles for Deep Learning in Biology and Medicine](https://scholar.google.com/scholar?q=%22Opportunities%20and%20Obstacles%20for%20Deep%20Learning%20in%20Biology%20and%20Medicine%22%20author%3A%22T%20Ching%22 "T Ching, DS Himmelstein, BK Beaulieu-jones") (2017)
[T Ching, DS Himmelstein, BK Beaulieu-jones] [102pp]  

### Classification

* [Supervised Machine Learning: A Review of Classification Techniques](https://scholar.google.com/scholar?q=%22Supervised%20Machine%20Learning%3A%20A%20Review%20of%20Classification%20Techniques%22%20author%3A%22SB%20Kotsiantis%22 "SB Kotsiantis, I Zaharakis, P Pintelas") (2007)
[SB Kotsiantis, I Zaharakis, P Pintelas] [20pp]  
* [Web Page Classification: Features and Algorithms](https://scholar.google.com/scholar?q=%22Web%20Page%20Classification%3A%20Features%20and%20Algorithms%22%20author%3A%22X%20Qi%22 "X Qi, BD Davison") (2009)
[X Qi, BD Davison] [31pp]  

### Clustering

* [Data Clustering: 50 Years Beyond K-Means](https://scholar.google.com/scholar?q=%22Data%20Clustering%3A%2050%20Years%20Beyond%20K-Means%22%20author%3A%22AK%20Jain%22 "AK Jain") (2010)
[AK Jain] [16pp]  ⭐
* [A Tutorial on Spectral Clustering](https://scholar.google.com/scholar?q=%22A%20Tutorial%20on%20Spectral%20Clustering%22%20author%3A%22U%20VON%20Luxburg%22 "U VON Luxburg") (2007)
[U VON Luxburg] [32pp]  
* [Handbook of Blind Source Separation: Independent Component Analysis and Applications](https://scholar.google.com/scholar?q=%22Handbook%20of%20Blind%20Source%20Separation%3A%20Independent%20Component%20Analysis%20and%20Applications%22%20author%3A%22P%20Comon%22 "P Comon, C Jutten") (2010)
[P Comon, C Jutten] [65pp]  📚 
* [Survey of Clustering Algorithms](https://scholar.google.com/scholar?q=%22Survey%20of%20Clustering%20Algorithms%22%20author%3A%22R%20Xu%22 "R Xu, D Wunsch") (2005)
[R Xu, D Wunsch] [34pp]  
* [A Survey of Clustering Data Mining Techniques](https://scholar.google.com/scholar?q=%22A%20Survey%20of%20Clustering%20Data%20Mining%20Techniques%22%20author%3A%22P%20Berkhin%22 "P Berkhin") (2006)
[P Berkhin] [56pp]  
* [Clustering](https://scholar.google.com/scholar?q=%22Clustering%22%20author%3A%22R%20Xu%22 "R Xu, D Wunsch") (2008)
[R Xu, D Wunsch] [341pp]  📚 

### Computer Vision

* [Pedestrian Detection: An Evaluation of the State of the Art](https://scholar.google.com/scholar?q=%22Pedestrian%20Detection%3A%20An%20Evaluation%20of%20the%20State%20of%20the%20Art%22%20author%3A%22P%20Dollar%22 "P Dollar, C Wojek, B Schiele") (2012)
[P Dollar, C Wojek, B Schiele] [19pp]  ⭐
* [Computer Vision: Algorithms and Applications](https://scholar.google.com/scholar?q=%22Computer%20Vision%3A%20Algorithms%20and%20Applications%22%20author%3A%22R%20Szeliski%22 "R Szeliski") (2010)
[R Szeliski] [874pp]  📚 ⭐
* [A Survey of Appearance Models in Visual Object Tracking](https://scholar.google.com/scholar?q=%22A%20Survey%20of%20Appearance%20Models%20in%20Visual%20Object%20Tracking%22%20author%3A%22X%20Li%22 "X Li") (2013)
[X Li] [42pp]  ⭐
* [Object Tracking: A Survey](https://scholar.google.com/scholar?q=%22Object%20Tracking%3A%20A%20Survey%22%20author%3A%22A%20Yilmaz%22 "A Yilmaz") (2006)
[A Yilmaz] [45pp]  
* [Head Pose Estimation in Computer Vision: A Survey](https://scholar.google.com/scholar?q=%22Head%20Pose%20Estimation%20in%20Computer%20Vision%3A%20A%20Survey%22%20author%3A%22E%20Murphy-chutorian%22 "E Murphy-chutorian, MM Trivedi") (2009)
[E Murphy-chutorian, MM Trivedi] [20pp]  
* [A Survey of Recent Advances in Face Detection](https://scholar.google.com/scholar?q=%22A%20Survey%20of%20Recent%20Advances%20in%20Face%20Detection%22%20author%3A%22C%20Zhang%22 "C Zhang, Z Zhang") (2010)
[C Zhang, Z Zhang] [17pp]  
* [Monocular Model-Based 3d Tracking of Rigid Objects: A Survey](https://scholar.google.com/scholar?q=%22Monocular%20Model-Based%203d%20Tracking%20of%20Rigid%20Objects%3A%20A%20Survey%22%20author%3A%22V%20Lepetit%22 "V Lepetit") (2005)
[V Lepetit] [91pp]  
* [A Survey on Face Detection in the Wild: Past, Present and Future](https://scholar.google.com/scholar?q=%22A%20Survey%20on%20Face%20Detection%20in%20the%20Wild%3A%20Past%2C%20Present%20and%20Future%22%20author%3A%22S%20Zafeiriou%22 "S Zafeiriou, C Zhang, Z Zhang") (2015)
[S Zafeiriou, C Zhang, Z Zhang] [50pp]  
* [A Review on Deep Learning Techniques Applied to Semantic Segmentation](https://scholar.google.com/scholar?q=%22A%20Review%20on%20Deep%20Learning%20Techniques%20Applied%20to%20Semantic%20Segmentation%22%20author%3A%22A%20Garcia-garcia%22 "A Garcia-garcia, S Orts-escolano") (2017)
[A Garcia-garcia, S Orts-escolano] [23pp]  
* [Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art](https://scholar.google.com/scholar?q=%22Computer%20Vision%20for%20Autonomous%20Vehicles%3A%20Problems%2C%20Datasets%20and%20State-of-the-Art%22%20author%3A%22D%20Russo%22 "D Russo, B VAN Roy, A Kazerouni, I Osband") (2017)
[D Russo, B VAN Roy, A Kazerouni, I Osband] [67pp]  
* [Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art](https://scholar.google.com/scholar?q=%22Computer%20Vision%20for%20Autonomous%20Vehicles%3A%20Problems%2C%20Datasets%20and%20State-of-the-Art%22%20author%3A%22J%20Janai%22 "J Janai, F Güney, A Behl, A Geiger") (2017)
[J Janai, F Güney, A Behl, A Geiger] [14pp]  

### Deep Learning

* [Deep Learning](https://scholar.google.com/scholar?q=%22Deep%20Learning%22%20author%3A%22IJ%20Goodfellow%22 "IJ Goodfellow, Y Bengio, A Courville") (2016)
[IJ Goodfellow, Y Bengio, A Courville] [800pp]  📚 ⭐⭐
* [Deep Learning in Neural Networks: An Overview](https://scholar.google.com/scholar?q=%22Deep%20Learning%20in%20Neural%20Networks%3A%20An%20Overview%22%20author%3A%22J%20Schmidhuber%22 "J Schmidhuber") (2015)
[J Schmidhuber] [88pp]  ⭐⭐
* [Learning Deep Architectures for Ai](https://scholar.google.com/scholar?q=%22Learning%20Deep%20Architectures%20for%20Ai%22%20author%3A%22Y%20Bengio%22 "Y Bengio") (2009)
[Y Bengio] [71pp]  ⭐
* [Tutorial on Variational Autoencoders](https://scholar.google.com/scholar?q=%22Tutorial%20on%20Variational%20Autoencoders%22%20author%3A%22C%20Doersch%22 "C Doersch") (2016)
[C Doersch] [65pp]  ⭐
* [Deep Reinforcement Learning: An Overview](https://scholar.google.com/scholar?q=%22Deep%20Reinforcement%20Learning%3A%20An%20Overview%22%20author%3A%22%20Y%20Li%22 " Y Li") (2017)
[ Y Li] [30pp]  
* [NIPS 2016 Tutorial: Generative Adversarial Networks](https://scholar.google.com/scholar?q=%22NIPS%202016%20Tutorial%3A%20Generative%20Adversarial%20Networks%22%20author%3A%22I%20Goodfellow%22 "I Goodfellow") (2016)
[I Goodfellow] [57pp]  
* [Opportunities and Obstacles for Deep Learning in Biology and Medicine](https://scholar.google.com/scholar?q=%22Opportunities%20and%20Obstacles%20for%20Deep%20Learning%20in%20Biology%20and%20Medicine%22%20author%3A%22T%20Ching%22 "T Ching, DS Himmelstein, BK Beaulieu-jones") (2017)
[T Ching, DS Himmelstein, BK Beaulieu-jones] [102pp]  
* [A Review on Deep Learning Techniques Applied to Semantic Segmentation](https://scholar.google.com/scholar?q=%22A%20Review%20on%20Deep%20Learning%20Techniques%20Applied%20to%20Semantic%20Segmentation%22%20author%3A%22A%20Garcia-garcia%22 "A Garcia-garcia, S Orts-escolano") (2017)
[A Garcia-garcia, S Orts-escolano] [23pp]  
* [Deep Learning for Video Game Playing](https://scholar.google.com/scholar?q=%22Deep%20Learning%20for%20Video%20Game%20Playing%22%20author%3A%22N%20Justesen%22 "N Justesen, P Bontrager, J Togelius, S Risi") (2017)
[N Justesen, P Bontrager, J Togelius, S Risi] [16pp]  
* [Deep Learning Techniques for Music Generation](https://scholar.google.com/scholar?q=%22Deep%20Learning%20Techniques%20for%20Music%20Generation%22%20author%3A%22JP%20Briot%22 "JP Briot, G Hadjeres, F PACHET ") (2017)
[JP Briot, G Hadjeres, F PACHET ] [108pp]  

### Dimensionality Reduction

* [Dimensionality Reduction: A Comparative Review](https://scholar.google.com/scholar?q=%22Dimensionality%20Reduction%3A%20A%20Comparative%20Review%22%20author%3A%22L%20VAN%20DER%20Maaten%22 "L VAN DER Maaten, E Postma") (2009)
[L VAN DER Maaten, E Postma] [36pp]  
* [Dimension Reduction: A Guided Tour](https://scholar.google.com/scholar?q=%22Dimension%20Reduction%3A%20A%20Guided%20Tour%22%20author%3A%22CJC%20Burges%22 "CJC Burges") (2010)
[CJC Burges] [64pp]  

### Ensemble Learning

* [Ensemble Methods: Foundations and Algorithms](https://scholar.google.com/scholar?q=%22Ensemble%20Methods%3A%20Foundations%20and%20Algorithms%22%20author%3A%22ZH%20Zhou%22 "ZH Zhou") (2012)
[ZH Zhou] [234pp]  
* [Ensemble Approaches for Regression: A Survey](https://scholar.google.com/scholar?q=%22Ensemble%20Approaches%20for%20Regression%3A%20A%20Survey%22%20author%3A%22J%20Mendes-moreira%22 "J Mendes-moreira, C Soares, AM Jorge") (2012)
[J Mendes-moreira, C Soares, AM Jorge] [40pp]  

### Metric Learning

* [A Survey on Metric Learning for Feature Vectors and Structured Data](https://scholar.google.com/scholar?q=%22A%20Survey%20on%20Metric%20Learning%20for%20Feature%20Vectors%20and%20Structured%20Data%22%20author%3A%22A%20Bellet%22 "A Bellet") (2014)
[A Bellet] [59pp]  
* [Metric Learning: A Survey](https://scholar.google.com/scholar?q=%22Metric%20Learning%3A%20A%20Survey%22%20author%3A%22B%20Kulis%22 "B Kulis") (2012)
[B Kulis] [80pp]  

### Monte Carlo

* [Geometric Integrators and the Hamiltonian Monte Carlo Method](https://scholar.google.com/scholar?q=%22Geometric%20Integrators%20and%20the%20Hamiltonian%20Monte%20Carlo%20Method%22%20author%3A%22N%20Bou-rabee%22 "N Bou-rabee, JM Sanz-serna") (2017)
[N Bou-rabee, JM Sanz-serna] [92pp]  

### Multi-Armed Bandit

* [Regret Analysis of Stochastic and Nonstochastic Multi-Armed Bandit Problems](https://scholar.google.com/scholar?q=%22Regret%20Analysis%20of%20Stochastic%20and%20Nonstochastic%20Multi-Armed%20Bandit%20Problems%22%20author%3A%22S%20Bubeck%22 "S Bubeck, N Cesa-bianchi") (2012)
[S Bubeck, N Cesa-bianchi] [130pp]  ⭐
* [A Survey of Online Experiment Design With the Stochastic Multi-Armed Bandit](https://scholar.google.com/scholar?q=%22A%20Survey%20of%20Online%20Experiment%20Design%20With%20the%20Stochastic%20Multi-Armed%20Bandit%22%20author%3A%22G%20Burtini%22 "G Burtini, J Loeppky, R Lawrence") (2015)
[G Burtini, J Loeppky, R Lawrence] [49pp]  
* [A Tutorial on Thompson Sampling](https://scholar.google.com/scholar?q=%22A%20Tutorial%20on%20Thompson%20Sampling%22%20author%3A%22D%20Russo%22 "D Russo, B VAN Roy, A Kazerouni, I Osband") (2017)
[D Russo, B VAN Roy, A Kazerouni, I Osband] [39pp]  

### Multi-View Learning

* [A Survey on Multi-View Learning](https://scholar.google.com/scholar?q=%22A%20Survey%20on%20Multi-View%20Learning%22%20author%3A%22C%20Xu%22 "C Xu") (2013)
[C Xu] [59pp]  
* [A Survey of Multi-View Machine Learning](https://scholar.google.com/scholar?q=%22A%20Survey%20of%20Multi-View%20Machine%20Learning%22%20author%3A%22S%20Sun%22 "S Sun") (2013)
[S Sun] [13pp]  

### Natural Language Processing

* [A Primer on Neural Network Models for Natural Language Processing](https://scholar.google.com/scholar?q=%22A%20Primer%20on%20Neural%20Network%20Models%20for%20Natural%20Language%20Processing%22%20author%3A%22Y%20Goldberg%22 "Y Goldberg") (2016)
[Y Goldberg] [76pp]  ⭐
* [Probabilistic Topic Models](https://scholar.google.com/scholar?q=%22Probabilistic%20Topic%20Models%22%20author%3A%22DM%20Blei%22 "DM Blei") (2012)
[DM Blei] [16pp]  ⭐
* [Natural Language Processing (Almost) From Scratch](https://scholar.google.com/scholar?q=%22Natural%20Language%20Processing%20%28Almost%29%20From%20Scratch%22%20author%3A%22R%20Collobert%22 "R Collobert") (2011)
[R Collobert] [45pp]  ⭐
* [Opinion Mining and Sentiment Analysis](https://scholar.google.com/scholar?q=%22Opinion%20Mining%20and%20Sentiment%20Analysis%22%20author%3A%22B%20Pang%22 "B Pang, L Lee") (2008)
[B Pang, L Lee] [94pp]  ⭐
* [Survey of the State of the Art in Natural Language Generation: Core Tasks, Applications and Evaluation](https://scholar.google.com/scholar?q=%22Survey%20of%20the%20State%20of%20the%20Art%20in%20Natural%20Language%20Generation%3A%20Core%20Tasks%2C%20Applications%20and%20Evaluation%22%20author%3A%22A%20Gatt%22 "A Gatt, E Krahmer") (2017)
[A Gatt, E Krahmer] [111pp]  ⭐
* [Opinion Mining and Sentiment Analysis](https://scholar.google.com/scholar?q=%22Opinion%20Mining%20and%20Sentiment%20Analysis%22%20author%3A%22B%20Liu%22 "B Liu, L Zhang") (2012)
[B Liu, L Zhang] [38pp]  
* [Neural Machine Translation and Sequence-to-Sequence Models: A Tutorial](https://scholar.google.com/scholar?q=%22Neural%20Machine%20Translation%20and%20Sequence-to-Sequence%20Models%3A%20A%20Tutorial%22%20author%3A%22G%20Neubig%22 "G Neubig") (2017)
[G Neubig] [65pp]  
* [Machine Learning in Automated Text Categorization](https://scholar.google.com/scholar?q=%22Machine%20Learning%20in%20Automated%20Text%20Categorization%22%20author%3A%22F%20Sebastiani%22 "F Sebastiani") (2002)
[F Sebastiani] [55pp]  
* [Statistical Machine Translation](https://scholar.google.com/scholar?q=%22Statistical%20Machine%20Translation%22%20author%3A%22P%20Koehn%22 "P Koehn") (2009)
[P Koehn] [149pp]  📚 
* [Statistical Machine Translation](https://scholar.google.com/scholar?q=%22Statistical%20Machine%20Translation%22%20author%3A%22A%20Lopez%22 "A Lopez") (2008)
[A Lopez] [55pp]  
* [Machine Transliteration Survey](https://scholar.google.com/scholar?q=%22Machine%20Transliteration%20Survey%22%20author%3A%22S%20Karimi%22 "S Karimi, F Scholer, A Turpin") (2011)
[S Karimi, F Scholer, A Turpin] [46pp]  
* [Neural Machine Translation and Sequence-to-Sequence Models: A Tutorial](https://scholar.google.com/scholar?q=%22Neural%20Machine%20Translation%20and%20Sequence-to-Sequence%20Models%3A%20A%20Tutorial%22%20author%3A%22G%20Neubig%22 "G Neubig") (2017)
[G Neubig] [57pp]  

### Physics

* [Machine Learning & Artificial Intelligence in the Quantum Domain](https://scholar.google.com/scholar?q=%22Machine%20Learning%20%26%20Artificial%20Intelligence%20in%20the%20Quantum%20Domain%22%20author%3A%22V%20Dunjko%22 "V Dunjko, HJ Briegel") (2017)
[V Dunjko, HJ Briegel] [106pp]  

### Probabilistic Models

* [Graphical Models, Exponential Families, and Variational Inference](https://scholar.google.com/scholar?q=%22Graphical%20Models%2C%20Exponential%20Families%2C%20and%20Variational%20Inference%22%20author%3A%22MJ%20Wainwright%22 "MJ Wainwright, MI Jordan") (2008)
[MJ Wainwright, MI Jordan] [305pp]  
* [An Introduction to Conditional Random Fields](https://scholar.google.com/scholar?q=%22An%20Introduction%20to%20Conditional%20Random%20Fields%22%20author%3A%22C%20Sutton%22 "C Sutton") (2011)
[C Sutton] [90pp]  
* [An Introduction to Conditional Random Fields for Relational Learning](https://scholar.google.com/scholar?q=%22An%20Introduction%20to%20Conditional%20Random%20Fields%20for%20Relational%20Learning%22%20author%3A%22C%20Sutton%22 "C Sutton") (2006)
[C Sutton] [35pp]  
* [An Introduction to Mcmc for Machine Learning](https://scholar.google.com/scholar?q=%22An%20Introduction%20to%20Mcmc%20for%20Machine%20Learning%22%20author%3A%22C%20Andrieu%22 "C Andrieu, N DE Freitas, A Doucet, MI Jordan") (2003)
[C Andrieu, N DE Freitas, A Doucet, MI Jordan] [39pp]  
* [Introduction to Probability Models](https://scholar.google.com/scholar?q=%22Introduction%20to%20Probability%20Models%22%20author%3A%22SM%20Ross%22 "SM Ross") (2014)
[SM Ross] [801pp]  📚 

### Recommender Systems

* [Introduction to Recommender Systems Handbook](https://scholar.google.com/scholar?q=%22Introduction%20to%20Recommender%20Systems%20Handbook%22%20author%3A%22F%20Ricci%22 "F Ricci, L Rokach, B Shapira") (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](https://scholar.google.com/scholar?q=%22Toward%20the%20Next%20Generation%20of%20Recommender%20Systems%3A%20A%20Survey%20of%20the%20State-of-the-Art%20and%20Possible%20Extensions%22%20author%3A%22G%20Adomavicius%22 "G Adomavicius, A Tuzhilin") (2008)
[G Adomavicius, A Tuzhilin] [43pp]  ⭐
* [Matrix Factorization Techniques for Recommender Systems](https://scholar.google.com/scholar?q=%22Matrix%20Factorization%20Techniques%20for%20Recommender%20Systems%22%20author%3A%22Y%20Koren%22 "Y Koren, R Bell, C Volinsky") (2009)
[Y Koren, R Bell, C Volinsky] [8pp]  ⭐
* [A Survey of Collaborative Filtering Techniques](https://scholar.google.com/scholar?q=%22A%20Survey%20of%20Collaborative%20Filtering%20Techniques%22%20author%3A%22X%20Su%22 "X Su, TM Khoshgoftaar") (2009)
[X Su, TM Khoshgoftaar] [20pp]  

### Reinforcement Learning

* [Reinforcement Learning in Robotics: A Survey](https://scholar.google.com/scholar?q=%22Reinforcement%20Learning%20in%20Robotics%3A%20A%20Survey%22%20author%3A%22J%20Kober%22 "J Kober, JA Bagnell, J Peterskober") (2013)
[J Kober, JA Bagnell, J Peterskober] [74pp]  ⭐
* [Deep Reinforcement Learning: An Overview](https://scholar.google.com/scholar?q=%22Deep%20Reinforcement%20Learning%3A%20An%20Overview%22%20author%3A%22%20Y%20Li%22 " Y Li") (2017)
[ Y Li] [30pp]  
* [Reinforcement Learning: An Introduction](https://scholar.google.com/scholar?q=%22Reinforcement%20Learning%3A%20An%20Introduction%22%20author%3A%22RS%20Sutton%22 "RS Sutton, AG Barto") (2016)
[RS Sutton, AG Barto] [398pp]  📚 
* [Bayesian Reinforcement Learning: A Survey](https://scholar.google.com/scholar?q=%22Bayesian%20Reinforcement%20Learning%3A%20A%20Survey%22%20author%3A%22M%20Ghavamzadeh%22 "M Ghavamzadeh, S Mannor, J Pineau") (2016)
[M Ghavamzadeh, S Mannor, J Pineau] [147pp]  
* [Reinforcement Learning: A Survey](https://scholar.google.com/scholar?q=%22Reinforcement%20Learning%3A%20A%20Survey%22%20author%3A%22LP%20Kaelbling%22 "LP Kaelbling, ML Littman, AW Moore") (1996)
[LP Kaelbling, ML Littman, AW Moore] [49pp]  
* [Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art](https://scholar.google.com/scholar?q=%22Computer%20Vision%20for%20Autonomous%20Vehicles%3A%20Problems%2C%20Datasets%20and%20State-of-the-Art%22%20author%3A%22J%20Janai%22 "J Janai, F Güney, A Behl, A Geiger") (2017)
[J Janai, F Güney, A Behl, A Geiger] [14pp]  
* [Deep Learning for Video Game Playing](https://scholar.google.com/scholar?q=%22Deep%20Learning%20for%20Video%20Game%20Playing%22%20author%3A%22N%20Justesen%22 "N Justesen, P Bontrager, J Togelius, S Risi") (2017)
[N Justesen, P Bontrager, J Togelius, S Risi] [16pp]  

### Robotics

* [Reinforcement Learning in Robotics: A Survey](https://scholar.google.com/scholar?q=%22Reinforcement%20Learning%20in%20Robotics%3A%20A%20Survey%22%20author%3A%22J%20Kober%22 "J Kober, JA Bagnell, J Peterskober") (2013)
[J Kober, JA Bagnell, J Peterskober] [74pp]  ⭐
* [A Survey of Robot Learning From Demonstration](https://scholar.google.com/scholar?q=%22A%20Survey%20of%20Robot%20Learning%20From%20Demonstration%22%20author%3A%22BD%20Argall%22 "BD Argall, S Chernova, M Veloso") (2009)
[BD Argall, S Chernova, M Veloso] [15pp]  

### Semi-Supervised Learning

* [Semi-Supervised Learning Literature Survey](https://scholar.google.com/scholar?q=%22Semi-Supervised%20Learning%20Literature%20Survey%22%20author%3A%22X%20Zhu%22 "X Zhu") (2008)
[X Zhu] [59pp]  

### Submodular Functions

* [Learning With Submodular Functions: A Convex Optimization Perspective](https://scholar.google.com/scholar?q=%22Learning%20With%20Submodular%20Functions%3A%20A%20Convex%20Optimization%20Perspective%22%20author%3A%22F%20Bach%22 "F Bach") (2013)
[F Bach] [173pp]  
* [Submodular Function Maximization](https://scholar.google.com/scholar?q=%22Submodular%20Function%20Maximization%22%20author%3A%22A%20Krause%22 "A Krause, D Golovin") (2012)
[A Krause, D Golovin] [28pp]  

### Transfer Learning

* [A Survey on Transfer Learning](https://scholar.google.com/scholar?q=%22A%20Survey%20on%20Transfer%20Learning%22%20author%3A%22SJ%20Pan%22 "SJ Pan, Q Yang") (2010)
[SJ Pan, Q Yang] [15pp]  ⭐
* [Transfer Learning for Reinforcement Learning Domains: A Survey](https://scholar.google.com/scholar?q=%22Transfer%20Learning%20for%20Reinforcement%20Learning%20Domains%3A%20A%20Survey%22%20author%3A%22ME%20Taylor%22 "ME Taylor, P Stone") (2009)
[ME Taylor, P Stone] [53pp]  

### Unsupervised Learning

* [Tutorial on Variational Autoencoders](https://scholar.google.com/scholar?q=%22Tutorial%20on%20Variational%20Autoencoders%22%20author%3A%22C%20Doersch%22 "C Doersch") (2016)
[C Doersch] [65pp]  ⭐

