Abstract:
The goal of lifelong machine learning is to develop techniques that continuously and autonomously learn from data, potentially for years or decades. During this time, the system should autonomously improve its performance by extracting and preserving information between different learning tasks, similar to how a natural system learns more and more complex tasks over time. In my talk, I will highlight recent work from our research group in two directions: theoretical guarantees for lifelong learning and applications to computer vision problems.
