We propose a novel algorithm for sentiment summarization that takes account of informativeness and readability, simultaneously. Our algorithm generates a summary by selecting and ...
The recently proposed ImageNet dataset consists of several million images, each annotated with a single object category. However, these annotations may be imperfect, in the sense t...
We present new algorithms for inverse optimal control (or inverse reinforcement learning, IRL) within the framework of linearlysolvable MDPs (LMDPs). Unlike most prior IRL algorit...
The explosion of Web opinion data has made essential the need for automatic tools to analyze and understand people’s sentiments toward different topics. In most sentiment analy...
An intuitive approach to utilizing unlabeled data in kernel-based classification algorithms is to simply treat unknown labels as additional optimization variables. For marginbased...
Vikas Sindhwani, S. Sathiya Keerthi, Olivier Chape...