Computational Advertising Architect
Exploration and Exploitation
A Contextual-Bandit Approach to Personalized News Article Recommendation(LinUCB).pdf
A Fast and Simple Algorithm for Contextual Bandits.pdf
An Empirical Evaluation of Thompson Sampling.pdf
Analysis of Thompson Sampling for the Multi-armed Bandit Problem.pdf
Bandit Algorithms Continued- UCB1.pdf
Bandit based Monte-Carlo Planning.pdf
Customer Acquisition via Display Advertising Using MultiArmed Bandit Experiments.pdf
Dynamic Online Pricing with Incomplete Information Using Multi-Armed Bandit Experiments.pdf
Exploitation and Exploration in a Performance based Contextual Advertising System.pdf
Exploration and Exploitation Problem by Wang Zhe.pptx
Exploration exploitation in Go UCT for Monte-Carlo Go.pdf
Exploring compact reinforcement-learning representations with linear regression.pdf
Finite-time Analysis of the Multiarmed Bandit Problem.pdf
Hierarchical Deep Reinforcement Learning- Integrating Temporal Abstraction and Intrinsic Motivation.pdf
Incentivizting Exploration in Reinforcement Learning with Deep Predictive Models.pdf
Mastering the game of Go with deep neural networks and tree search.pdf
Random Forest for the Contextual Bandit Problem.pdf
Thompson Sampling PPT.pdf
Unifying Count-Based Exploration and Intrinsic Motivation.pdf
Using Confidence Bounds for Exploitation-Exploration Trade-offs.pdf
Machine Learning Tutorial
You can’t perform that action at this time.
