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...
Conditional Value at Risk (CVaR) is a prominent risk measure that is being used extensively in various domains. We develop a new formula for the gradient of the CVaR in the form o...
Bayesian decision-theory underpins robust decisionmaking in applications ranging from plant control to robotics where hedging action selection against state uncertainty is critica...
Living organisms adapt to challenges through evolution and adaptation. This has proven to be a key difficulty in developing therapies, since the organisms develop resistance. I p...
Recent advances in Symbolic Dynamic Programming (SDP) combined with the extended algebraic decision diagram (XADD) have provided exact solutions for expressive subclasses of fini...
Luis Gustavo Rocha Vianna, Leliane N. de Barros, S...
Given a data set from a union of multiple linear subspaces, a robust subspace clustering algorithm fits each group of data points with a low-dimensional subspace and then cluster...
This paper describes a novel combination of Java program analysis and automated learning and planning architecture to the domain of Java vulnerability analysis. The key feature of...
Ugur Kuter, Mark H. Burstein, J. Benton, Daniel Br...