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, ...

• Efficient Algorithms for Structured Output Learning 

  Balamurugan, P (2018-05-08)

  Structured output learning is the machine learning task of building a classifier to predict structured outputs. Structured outputs arise in several contexts in diverse applications like natural language processing, computer ...

• On Learning k-Parities and the Complexity of k-Vector-SUM 

  Gadekar, Ameet (2018-02-06)

  In this work, we study two problems: first is one of the central problem in learning theory of learning sparse parities and the other k-Vector-SUM is an extension of the not oriousk-SUM problem. We first consider the problem ...