abhi1345 / deep-q-rank
A deep reinforcement learning approach to search engine ranking (PyTorch). Final Project for UC Berkeley's CS 285: Deep Reinforcement Learning, Decision Making, and Control
☆27Updated last year
Alternatives and similar repositories for deep-q-rank:
Users that are interested in deep-q-rank are comparing it to the libraries listed below
- paper list in the area of reinforcenment learning for recommendation systems☆24Updated 4 years ago
- Implementing LinUCB and HybridLinUCB in Python.☆48Updated 6 years ago
- A toolkit of Reinforcement Learning based Recommendation (RL4Rec)☆23Updated 3 years ago
- Predict and recommend the news articles, user is most likely to click in real time.☆31Updated 7 years ago
- A PyTorch implementation of REINFORCE Learning To Rank on OSHUMED, MQ, etc. dataset. Basic idea also appears in SIGIR'17 Reinforcement Le…☆18Updated 7 years ago
- A comparison of Google SlateQ algorithm with traditional Reinforcement Learning algorithms☆35Updated 2 years ago
- A set of RL experiments. Currently including: (1) the MDP rank experiment, based on policy gradient algorithm☆27Updated 3 years ago
- Explore the potential of recommendation system using reinforcement learning☆15Updated 5 years ago
- Code associated with the NeurIPS19 paper "Weighted Linear Bandits in Non-Stationary Environments"☆17Updated 5 years ago
- ☆51Updated last year
- Off-policy Learning in Two-stage Recommender Systems. https://dl.acm.org/doi/pdf/10.1145/3366423.3380130☆29Updated 4 years ago
- A collection of research and survey papers of reforcement learning (RL) based recommender system techniques.☆72Updated 5 years ago
- A TensorFlow implementation of SOFA, the Simulator for OFfline LeArning and evaluation.☆21Updated 4 years ago
- Thompson Sampling Tutorial☆53Updated 6 years ago
- ☆14Updated 4 years ago
- ☆17Updated 4 years ago
- Source code for our paper "Joint Policy-Value Learning for Recommendation" published at KDD 2020.☆22Updated last year
- A pytorch implementation of A Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation.☆40Updated 5 years ago
- Implementation for our paper in NeurIPS 2019☆48Updated 5 years ago
- Study NeuralUCB and regret analysis for contextual bandit with neural decision☆94Updated 3 years ago
- A python implementation of Dueling Bandit Gradient Descent (DBGD)☆23Updated 6 years ago
- Offline evaluation of multi-armed bandit algorithms☆23Updated 4 years ago
- Code of ICML-2020 paper Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising☆26Updated 4 years ago
- Code for the experiments of Matrix Factorization Bandit☆24Updated 6 years ago
- Multi Armed Bandits implementation using the Yahoo! Front Page Today Module User Click Log Dataset☆99Updated 3 years ago
- Ranking Policy Gradient☆23Updated 5 years ago
- A lightweight contextual bandit & reinforcement learning library designed to be used in production Python services.☆66Updated 3 years ago
- Bootstrap (Linear) Thompson Sampling☆13Updated 8 years ago
- In this notebook several classes of multi-armed bandits are implemented. This includes epsilon greedy, UCB, Linear UCB (Contextual bandit…☆85Updated 4 years ago
- ☆15Updated 5 years ago