16 citations · 31 across the 6 of their papers we have counts for
6 papers
Techniques Toward Optimizing Viewability in RTB Ad Campaigns Using Reinforcement Learning
Michael Tashman, John Hoffman, Jiayi Xie +4
Reinforcement learning (RL) is an effective technique for training decision-making agents through interactions with their environment. The advent of deep learning has been associat…
Online and Scalable Model Selection with Multi-Armed Bandits
Jiayi Xie, Michael Tashman, John Hoffman +2
Many online applications running on live traffic are powered by machine learning models, for which training, validation, and hyper-parameter tuning are conducted on historical data…
Dynamic Bidding Strategies with Multivariate Feedback Control for Multiple Goals in Display Advertising
Michael Tashman, Jiayi Xie, John Hoffman +2
Real-Time Bidding (RTB) display advertising is a method for purchasing display advertising inventory in auctions that occur within milliseconds. The performance of RTB campaigns is…
Downward shift of infrared conductivity spectral weight at the DDW transition: role of anisotropy
Rouzbeh Gerami, Chetan Nayak
We consider the motion of conductivity spectral weight at a finite-temperature phase transition at which density-wave (DDW) order develops. We show that there is a sh…
Criticality and oscillatory behavior in non-Markovian Contact Process
Rouzbeh Gerami
A Non-Markovian generalization of one-dimensional Contact Process (CP) is being introduced in which every particle has an age and will be annihilated at its maximum age . There…
A History-Dependent Stochastic Predator-Prey Model : Chaos and its Elimination
Rouzbeh Gerami, Mohammad R. Ejtehadi
A non-Markovian stochastic predator-prey model is introduced in which the prey are immobile plants and predators are diffusing herbivors. The model is studied by both mean-field ap…