Identifying important components or factors in large amounts of noisy data is a key problem in machine learning and data mining. Motivated by a pattern decomposition problem in ma...
Stefano Ermon, Ronan Le Bras, Santosh K. Suram, Jo...
This paper proposes approaches to automatically create a large number of new bilingual dictionaries for lowresource languages, especially resource-poor and endangered languages, f...
Restricted Boltzmann Machines (RBMs) are an important class of latent variable models for representing vector data. An under-explored area is multimode data, where each data point...
Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha...
Topic modeling techniques have the benefits of modeling words and documents uniformly under a probabilistic framework. However, they also suffer from the limitations of sensitivi...
Ziqiang Cao, Sujian Li, Yang Liu, Wenjie Li, Heng ...
Bursty topics discovery in microblogs is important for people to grasp essential and valuable information. However, the task is challenging since microblog posts are particularly ...
Xiaohui Yan, Jiafeng Guo, Yanyan Lan, Jun Xu, Xueq...
In this work we give a first tractability analysis of Compressed Path Databases, space efficient oracles used to very quickly identify the first arc on a shortest path. We stud...
One of the goals of much virtual reality (VR) research is to increase realism. In particular, many techniques for locomotion in VR attempt to approximate real-world walking. Howev...
Mahdi Nabiyouni, Ayshwarya Saktheeswaran, Doug A. ...
With technological evolution, 3D virtual environments continuously increase in complexity; such is the case with multiscale environments, i.e., environments that contain groups of...