drl-recsys
Deep Reinforcement Learning in Recommendation Systems
Concepts
Offline Reinforcement Learning
Markov Decision Process
RL Tutorials
Introduction to Gym toolkit
Code-Driven Introduction to Reinforcement Learning
CartPole using Cross-Entropy
FrozenLake using Cross-Entropy
FrozenLake using Value Iteration
FrozenLake using Q-Learning
CartPole using REINFORCE in PyTorch
Cartpole in PyTorch
Q-Learning on Lunar Lander and Frozen Lake
REINFORCE
Importance Sampling
Kullback-Leibler Divergence
MDP with Dynamic Programming in PyTorch
REINFORCE in PyTorch
MDP Basics with Inventory Control
n-step algorithms and eligibility traces
Q-Learning vs SARSA and Q-Learning extensions
RecSys Tutorials
Multi-armed Bandit for Banner Ad
Contextual Recommender with Vowpal Wabbit
Top-K Off-Policy Correction for a REINFORCE Recommender System
Neural Interactive Collaborative Filtering
Batch-Constrained Deep Q-Learning
Pydeep Recsys
Recsim Catalyst
Solving Multi-armed Bandit Problems
Deep Reinforcement Learning in Large Discrete Action Spaces
Off-Policy Learning in Two-stage Recommender Systems
Comparing Simple Exploration Techniques: ε-Greedy, Annealing, and UCB
Predicting rewards with the state-value and action-value function
Real-Time Bidding in Advertising
GAN User Model for RL-based Recommendation System
Index