In this work we consider the problem of monitoring information streams for anomalies in a scalable and efficient manner. We study the problem in the context of network streams wher...
Transferring knowledge from one domain to another is challenging due to a number of reasons. Since both conditional and marginal distribution of the training data and test data ar...
— This paper presents an important outcome of a research programme which focuses on the development of a method for synthesizing, under controlled conditions in the laboratory, t...
Starting with a similarity function between objects, it is possible to define a distance metric (the kernel distance) on pairs of objects, and more generally on probability distr...
Sarang C. Joshi, Raj Varma Kommaraju, Jeff M. Phil...
Contextual bandit learning is a reinforcement learning problem where the learner repeatedly receives a set of features (context), takes an action and receives a reward based on th...