The problem of finding the optimal set of quantized coefficients for a frame-based encoded signal is known to be of very high complexity. This paper presents an efficient method o...
Tom Ryen, Guido M. Schuster, Aggelos K. Katsaggelo...
Introducing a new concept of (, )-fairness, which allows for a bounded fairness compromise, so that a source is allocated a rate neither less than 0 1, nor more than 1, times...
Moshe Zukerman, Musa Mammadov, Liansheng Tan, Irad...
L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized...
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. N...
Power minimization under variability is formulated as a rigorous statistical robust optimization program with a guarantee of power and timing yields. Both power and timing metrics...
Content-based dissemination of XML data using the publishsubscribe paradigm is an effective means to deliver relevant data to interested data consumers. To meet the performance ch...