In this work we consider the problem of universal prediction of individual sequences where the universal predictor is a deterministic finite state machine, with a fixed, relativel...
Optimal index assignment of multiple description lattice vector quantizer (MDLVQ) can be posed as a large-scale linear assignment problem. But is this expensive algorithmic approa...
Abstract. We propose measures for compressed data structures, in which space usage is measured in a data-aware manner. In particular, we consider the fundamental dictionary problem...
An analysis is presented that examines multihypothesis motion-compensated video coding using a redundant wavelet transform to produce multiple predictions that are diverse in tran...
We investigate the optimum transmission strategy that minimizes the overall distortion for delaysensitive but distortion-tolerant data. We consider a set of source symbols residin...
We study the problem of distributed sampling and compression in sensor networks when the sensors are digital cameras that acquire a 3-D visual scene of interest from different vie...
We consider a class of algorithms related to Lempel-Ziv that incorporate restrictions on the manner in which the data can be parsed with the goal of introducing new tradeoffs betwe...
John T. Robinson, Luis Alfonso Lastras-Monta&ntild...
H.264 is currently the best way to compress media to achieve high quality at low bandwidth. Since its inception, technologies such as video-on-demand are increasingly realizable. ...
Large XML data files, or XML databases, are now a common way to distribute scientific and bibliographic data, and storing such data efficiently is an important concern. A number o...
We discuss two approaches for decoding at arbitrary rates in the Slepian-Wolf problem - time sharing and source splitting - both of which rely on constituent vertex decoders. We c...