We demonstrate an approach to predict latent personal attributes including user demographics, online personality, emotions and sentiments from texts published on Twitter. We rely ...
Svitlana Volkova, Yoram Bachrach, Michael Armstron...
Information diffusion, which studies how information is propagated in social networks, has attracted considerable research effort recently. However, most existing approaches do no...
Yang Yang, Jie Tang, Cane Wing-ki Leung, Yizhou Su...
Current algorithms for the standard multi-armed bandit problem have good empirical performance and optimal regret bounds. However, real-world problems often differ from the standa...
Travis Mandel, Yun-En Liu, Emma Brunskill, Zoran P...
Is it possible to maximize a monotone submodular function faster than the widely used lazy greedy algorithm (also known as accelerated greedy), both in theory and practice? In thi...
We consider the problem of learning deep representation when target labels are available. In this paper, we show that there exists intrinsic relationship between target coding and...
Shuo Yang, Ping Luo, Chen Change Loy, Kenneth W. S...
In many real-world situations a decision maker may make decisions across many separate reinforcement learning tasks in parallel, yet there has been very little work on concurrent ...
Modern organizations (e.g., hospitals, social networks, government agencies) rely heavily on audit to detect and punish insiders who inappropriately access and disclose confident...
Jeremiah Blocki, Nicolas Christin, Anupam Datta, A...
Pronoun resolution and common noun phrase resolution are the two most challenging subtasks of coreference resolution. While a lot of work has focused on pronoun resolution, common...
Motivated by problems such as molecular energy prediction, we derive an (improper) kernel between geometric inputs, that is able to capture the relevant rotational and translation...