Selective sampling, a form of active learning, reduces the cost of labeling training data by asking only for the labels of the most informative unlabeled examples. We introduce a ...
We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our m...
We propose Recursive Compositional Models (RCMs) for simultaneous multi-view multi-object detection and parsing (e.g. view estimation and determining the positions of the object s...
Long Zhu, Yuanhao Chen, Antonio Torralba, William ...
Pictorial structure (PS) models are extensively used for part-based recognition of scenes, people, animals and multi-part objects. To achieve tractability, the structure and param...
This paper addresses the problem of learning to map sentences to logical form, given training data consisting of natural language sentences paired with logical representations of ...
Tom Kwiatkowksi, Luke S. Zettlemoyer, Sharon Goldw...