5 citations · 7 across the 3 of their papers we have counts for
3 papers
Towards Data-Driven Offline Simulations for Online Reinforcement Learning
Shengpu Tang, Felipe Vieira Frujeri, Dipendra Misra +4
Modern decision-making systems, from robots to web recommendation engines, are expected to adapt: to user preferences, changing circumstances or even new tasks. Yet, it is still un…
Contextual Bandit Applications in Customer Support Bot
Sandra Sajeev, Jade Huang, Nikos Karampatziakis +3
Virtual support agents have grown in popularity as a way for businesses to provide better and more accessible customer service. Some challenges in this domain include ambiguous use…
Lessons from Contextual Bandit Learning in a Customer Support Bot
Nikos Karampatziakis, Sebastian Kochman, Jade Huang +3
In this work, we describe practical lessons we have learned from successfully using contextual bandits (CBs) to improve key business metrics of the Microsoft Virtual Agent for cust…