Automated feature discovery is a fundamental problem in machine learning. Although classical feature discovery methods do not guarantee optimal solutions in general, it has been r...
— This paper introduces a product quantization based approach for approximate nearest neighbor search. The idea is to decomposes the space into a Cartesian product of low dimensi...
Network coding offers increased throughput and improved robustness to random faults in completely decentralized networks. In contrast to traditional routing schemes, however, netw...
Dan Boneh, David Freeman, Jonathan Katz, Brent Wat...
Linear subspace learning (LSL) is a popular approach to image recognition and it aims to reveal the essential features of high dimensional data, e.g., facial images, in a lower di...
—This paper presents a mathematical framework for resource reservation in TCP/IP networks by invoking a dynamic system viewpoint on the congestion monitoring processes occurring ...