Showing items related by title, author, creator and subject.

• Class Incremental Learning Across Diverse Data Paradigms 

  Jayateja, Kalla

  Class Incremental Learning (CIL) is a fundamental machine learning paradigm that enables models to continuously learn new classes over time, while retaining previously acquired knowledge. Despite significant progress, ...

• Approximate Dynamic Programming and Reinforcement Learning - Algorithms, Analysis and an Application 

  Lakshminarayanan, Chandrashekar (2018-08-13)

  Problems involving optimal sequential making in uncertain dynamic systems arise in domains such as engineering, science and economics. Such problems can often be cast in the framework of Markov Decision Process (MDP). ...

• Model Extraction and Active Learning 

  Shukla, Aditya

  Machine learning models are increasingly being offered as a service by big companies such as Google, Microsoft and Amazon. They use Machine Learning as a Service (MLaaS) to expose these machine learning models to the ...