We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a wide variety of r...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...
In this paper, we present an algorithm that can classify large-scale text data with high classification quality and fast training speed. Our method is based on a novel extension o...
Dong Zhuang, Benyu Zhang, Qiang Yang, Jun Yan, Zhe...
The recognition of events in video data is a subject of much current interest. In this paper, we address several issues related to this topic. The first one is overfitting when ...
The traditional approach for characterizing complex systems is to run standard workloads and measure the resulting performance as seen by the end user. However, unique opportuniti...
Haryadi S. Gunawi, Nitin Agrawal, Andrea C. Arpaci...
Abstract. There has been growing interest in practice in using unlabeled data together with labeled data in machine learning, and a number of different approaches have been develo...