Table of Contents

• Probabilistic Models

  • Introduction to Probability Models
  • Graphical Models, Exponential Families, and Variational Inference
  • An Introduction to Conditional Random Fields
  • An Introduction to Conditional Random Fields for Relational Learning
  • An Introduction to Mcmc for Machine Learning

• Recommender Systems

  • Introduction to Recommender Systems Handbook
  • Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions
  • Matrix Factorization Techniques for Recommender Systems
  • A Survey of Collaborative Filtering Techniques

• Submodular Functions

  • Submodular Function Maximization
  • Learning With Submodular Functions: A Convex Optimization Perspective

• Transfer Learning

  • A Survey on Transfer Learning
  • Transfer Learning for Reinforcement Learning Domains: A Survey

• Natural Language Processing

  • Survey of the State of the Art in Natural Language Generation: Core Tasks, Applications and Evaluation
  • Opinion Mining and Sentiment Analysis
  • Neural Machine Translation and Sequence-to-Sequence Models: A Tutorial
  • Machine Learning in Automated Text Categorization
  • Statistical Machine Translation
  • Statistical Machine Translation
  • Machine Transliteration Survey
  • A Primer on Neural Network Models for Natural Language Processing
  • Probabilistic Topic Models
  • Natural Language Processing (Almost) From Scratch
  • Opinion Mining and Sentiment Analysis

• Physics

  • Machine Learning & Artificial Intelligence in the Quantum Domain

• Robotics

  • Reinforcement Learning in Robotics: A Survey
  • A Survey of Robot Learning From Demonstration

• Reinforcement Learning

  • Reinforcement Learning: An Introduction
  • Bayesian Reinforcement Learning: A Survey
  • Reinforcement Learning: A Survey
  • Deep Learning for Video Game Playing
  • Deep Reinforcement Learning: An Overview
  • Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art

• Semi-Supervised Learning

  • Semi-Supervised Learning Literature Survey

• Active Learning

  • Active Learning Literature Survey

• Bioinformatics

  • Introduction to Bioinformatics
  • Bioinformatics - an Introduction for Computer Scientists

• Deep Learning

  • Opportunities and Obstacles for Deep Learning in Biology and Medicine
  • A Review on Deep Learning Techniques Applied to Semantic Segmentation
  • Deep Learning
  • Deep Learning in Neural Networks: An Overview
  • Learning Deep Architectures for Ai
  • NIPS 2016 Tutorial: Generative Adversarial Networks
  • Deep Learning Techniques for Music Generation

• Classification

  • Supervised Machine Learning: A Review of Classification Techniques
  • Web Page Classification: Features and Algorithms

• Clustering

  • Data Clustering: 50 Years Beyond K-Means
  • A Tutorial on Spectral Clustering
  • Handbook of Blind Source Separation: Independent Component Analysis and Applications
  • Survey of Clustering Algorithms
  • A Survey of Clustering Data Mining Techniques
  • Clustering

• Computer Vision

  • Pedestrian Detection: An Evaluation of the State of the Art
  • Computer Vision: Algorithms and Applications
  • A Survey of Appearance Models in Visual Object Tracking
  • Object Tracking: A Survey
  • Head Pose Estimation in Computer Vision: A Survey
  • A Survey of Recent Advances in Face Detection
  • Monocular Model-Based 3d Tracking of Rigid Objects: A Survey
  • A Survey on Face Detection in the Wild: Past, Present and Future
  • Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art

• Multi-Armed Bandit

  • A Survey of Online Experiment Design With the Stochastic Multi-Armed Bandit
  • Regret Analysis of Stochastic and Nonstochastic Multi-Armed Bandit Problems
  • A Tutorial on Thompson Sampling

• Unsupervised Learning

  • Tutorial on Variational Autoencoders

• Dimensionality Reduction

  • Dimensionality Reduction: A Comparative Review
  • Dimension Reduction: A Guided Tour

• Ensemble Learning

  • Ensemble Methods: Foundations and Algorithms
  • Ensemble Approaches for Regression: A Survey

• Metric Learning

  • A Survey on Metric Learning for Feature Vectors and Structured Data
  • Metric Learning: A Survey

• Monte Carlo

  • Geometric Integrators and the Hamiltonian Monte Carlo Method

• Multi-View Learning

  • A Survey on Multi-View Learning
  • A Survey of Multi-View Machine Learning