Intelligent systems that learn interactively from their end-users are quickly becoming
widespread. Until recently, this progress has been fueled mostly by advances in machine …

End-user interactive machine learning is a promising tool for enhancing human capabilities
with large data. Recent work has shown that we can create end-user interactive machine …

Interactive Machine Learning (IML) seeks to complement human perception and intelligence
by tightly integrating these strengths with the computational power and speed of computers …

Modern systems can augment people's capabilities by using machine-learned models to
surface intelligent behaviors. Unfortunately, building these models remains challenging and …

Interactive user interfaces need to continuously evolve based on the interactions that a user
has (or does not have) with the system. This may require constant exploration of various …

Interactive machine learning (IML) is an iterative learning process that tightly couples a
human with a machine learner, which is widely used by researchers and practitioners to …

In this paper we examine the notion of adaptive user interfaces, interactive systems that
invoke machine learning to improve their interaction with humans. We review some previous …

Human-centered approaches to machine learning have established theoretical foundations,
design principles and interaction techniques to facilitate end-user interaction with machine …

Interactive reinforcement learning (RL) has been successfully used in various applications in
different fields, which has also motivated HCI researchers to contribute in this area. In this …

Much contemporary rhetoric regards the prospects and pitfalls of using artificial intelligence
techniques to automate an increasing range of tasks, especially those once considered the …