Reinforcement learning

Modeling Multiple User Interests using Hierarchical Knowledge for Conversational Recommender System

In today’s world, e-commerce has become an integral part of our lives, and the success of these platforms relies on providing personalized recommendations to users. Recommender systems, therefore, play a crucial role in providing these personalized recommendations, and are used extensively in various industries, including music, movies, and online shopping. Recommender systems utilize users’ past …

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Overcoming the Limitations of Batch Learning with Online Real-Time Recurrent Learning

Introduction Machine learning has been a hot topic in recent years and for good reason. It has the potential to revolutionize many industries, from finance and healthcare to marketing and retail. However, traditional machine learning algorithms have limitations that prevent them from being applied in real-world scenarios. One such limitation is batch learning, where models …

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From Gamification to Profit: How Oxford U’s Q-Learning is Changing the Trading Game

The world of trading has undergone a significant shift in recent years, with the advent of advanced technology and sophisticated algorithms playing a critical role in shaping the industry. One such technology that has been gaining traction is Oxford University’s Deep Double Duelling Q-Learning (DDDQL). This cutting-edge approach to Q-learning, a type of reinforcement learning, …

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