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Using a set of binary classifiers to solve multiclass classification problems has been a popular approach over the years. The decision boundaries learnt by binary classifiers (also called base classifiers) are much simpler than those learnt by multiclass classifiers. This paper proposes a new classification framework, termed binarization with boosting and(More)
Consider a teacher designing a good lecture for students, or a hacker drafting a poisonous text input against Tay the chatterbot. Both cases can be formulated as a task of constructing special training data, such that a known learning algorithm taking the constructed data will arrive at a prespecified target model. This task is known as optimal teaching,(More)
  • Ayon Sen, Ashwin Karthi Narayanaswamy, Anubhavnidhi Abhashkumar
  • 2014
—Linear classifiers, even though very simple, are popular for classification tasks. By nature they can only differentiate between two classes. But it is possible to extend their usage into the domain of multi-class problems. These classifiers are known to perfrom very well for many practical scenarios (both binary and multi-class). In this paper, we examine(More)
Faculty members are often busy with various research work and thus have little time to prepare lectures. Advances in technology offer a solution to this problem. That is, they can record the lectures and reuse them over semesters. It is common for these lecture videos to include an inset frame of the instructor giving the lecture. However, little research(More)
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