In this work, a novel occlusion detection algorithm using online learning is proposed for video applications. Each frame of a video is considered as a time-step for which pixels a...
Traditional machine-learned ranking algorithms for web search are trained in batch mode, which assume static relevance of documents for a given query. Although such a batch-learni...
One of the key problems in reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large or even continuous Markov decision processes (...
Lihong Li, Michael L. Littman, Christopher R. Mans...
The timely and accurate detection of computer and network system intrusions has always been an elusive goal for system administrators and information security researchers. Existin...
This paper proposes Twin Vector Machine (TVM), a constant space and sublinear time Support Vector Machine (SVM) algorithm for online learning. TVM achieves its favorable scaling b...