Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
Most previous work on trainable language generation has focused on two paradigms: (a) using a statistical model to rank a set of generated utterances, or (b) using statistics to i...
In this article, we focus our efforts (i) on the study of how to automatically extract and exploit visual concepts and (ii) on fast visual diversity. First, in the Visual Concept D...
Sabrina Tollari, Marcin Detyniecki, Ali Fakeri-Tab...
Improving data quality is a time-consuming, labor-intensive and often domain specific operation. Existing data repair approaches are either fully automated or not efficient in int...
Mohamed Yakout, Ahmed K. Elmagarmid, Jennifer Nevi...
We have analyzed manufacturing data from several different semiconductor manufacturing plants, using decision tree induction software called Q-YIELD. The software generates rules ...