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Found 4 papers, 1 papers with code
Mixture Density Networks for Classification with an Application to Product Bundling
The Gaussian mixture representation of the learnt WTP distributions is then exploited to obtain the WTP distribution of the bundle consisting of both the products.
Practical First-Order Bayesian Optimization Algorithms
Such methods assume Gaussian process (GP) models for both, the function and its gradient, and use them to construct an acquisition function that identifies the next query point.
Bayesian Optimization for Function Compositions with Applications to Dynamic Pricing
Bayesian Optimization (BO) is used to find the global optima of black box functions.
Reinforcement Learning algorithms for regret minimization in structured Markov Decision Processes
A recent goal in the Reinforcement Learning (RL) framework is to choose a sequence of actions or a policy to maximize the reward collected or minimize the regret incurred in a finite time horizon.
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