We present a reinforcement learning game player that can interact with a General Game Playing system and transfer knowledge learned in one game to expedite learning in many other ...
Related objects may look similar at low-resolutions; differences begin to emerge naturally as the resolution is increased. By learning across multiple resolutions of input, knowle...
Transfer learning allows knowledge to be extracted from auxiliary domains and be used to enhance learning in a target domain. For transfer learning to be successful, it is critica...
Despite popular belief, boosting algorithms and related coordinate descent methods are prone to overfitting. We derive modifications to AdaBoost and related gradient-based coordin...
Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...