Most existing works on federated bandits take it for granted that all clients are altruistic about
sharing their data with the server for the collective good whenever needed. Despite their …

Hashmap is a fundamental data structure in computer science. There has been extensive
research on constructing hashmaps that minimize the number of collisions leading to …

In collaborative active learning, where multiple agents try to learn labels from a common
hypothesis, we introduce an innovative framework for incentivized collaboration. Here …

Recent advances in federated learning (FL) enable collaborative training of machine
learning (ML) models from large-scale and widely dispersed clients while protecting their …

There is a large amount of work constructing hashmaps to minimize the number of collisions.
However, to the best of our knowledge no known hashing technique guarantees group …

Data-driven Artificial Intelligence (AI) systems trained using Machine Learning (ML) are
shaping an ever-increasing (in size and importance) portion of our lives, including, but not …

For a federated learning model to perform well, it is crucial to have a diverse and
representative dataset. However, the data contributors may only be concerned with the …