Cooperative multicast is an effective solution to address the bottleneck problem of single-hop broadcast in wireless networks. By incorporating with the random linear network coding technique, the existing schemes can reduce the retransmission overhead significantly. However, the receivers may incur large decoding delay and complexity due to the batch decoding scheme. In addition, the dependenc...

A recursive method is presented for recovering 3D object shape and camera motion under orthography from an extended sequence of video images. This may be viewed as a natural extension of both the original [9] and the sequential [7] factorization methods. A critical aspect of these factorization approaches is the estimation of the so-called shape space [7], and they may in part be characterized ...

19 Recent empirical work on plant-level employment dynamics, described in Davis, Haltiwanger, and Schuh (DHS, 1996), represents a challenge to conventional ways of thinking about business cycles. The plant-level data provide concrete evidence against the broad applicability of the representative agent construct. Moreover, the behavior of the macro aggregates based on the plant-level data seem h...

The NITE Query Language (NQL) has been used successfully for analysis of a number of heavily cross-annotated data sets, and users especially value its elegance and flexibility. However, when using the current implementation, many of the more complicated queries that users have formulated must be run in batch mode. For a re-implementation, we require the query processor to be capable of handling...

Yu-Ting Chen, Jason Cong, Zhenman Fang, Jie Lei and Peng Wei {ytchen, cong, zhenman, jielei and peng.wei.prc}@cs.ucla.edu University of California, Los Angeles Abstract FPGA-enabled datacenters have shown great potential for providing performance and energy efficiency improvement. In this paper we aim to answer one key question: how can we efficiently integrate FPGAs into stateof-the-art big-da...

Caused by powerful sensors, advanced digitalisation techniques, and dramatically increased storage capabilities, big data in the sense of large or streaming data sets, very high dimensionality, or complex data formats constitute one of the major challenges faced by machine learning today. In this realm, a couple of typical assumptions of machine learning can no longer be met, such as e.g. the p...

Recent work on simultaneous trajectory estimation and mapping (STEAM) for mobile robots has found success by representing the trajectory as a Gaussian process. Gaussian processes can represent a continuous-time trajectory, elegantly handle asynchronous and sparse measurements, and allow the robot to query the trajectory to recover its estimated position at any time of interest. A major drawback...