We consider the problem of learning a sparse multi-task regression, where the structure in the outputs can be represented as a tree with leaf nodes as outputs and internal nodes a...
In this paper, we propose a novel solution for multi-view object detection. Given a set of training examples at different views, we select examples at a few key views and train on...
The Self Organizing Map (SOM) involves neural networks, that learns the features of input data thorough unsupervised, competitive neighborhood learning. In the SOM learning algorit...
This brief presents an efficient and scalable online learning algorithm for recurrent neural networks (RNNs). The approach is based on the real-time recurrent learning (RTRL) algor...
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...