Scott Reed

Learning Deep Representations of Fine-grained Visual Descriptions

2016 · arXiv (Cornell University)

State-of-the-art methods for zero-shot visual recognition formulate learning as a joint embedding problem of images and side information. In these formulations the current best complement to visual features are attributes: manually encoded vectors describing shared …

Scaling data-driven robotics with reward sketching and batch reinforcement learning

2019 · arXiv (Cornell University)

We present a framework for data-driven robotics that makes use of a large dataset of recorded robot experience and scales to several tasks using learned reward functions. We show how to apply this framework to …