The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...
This paper1 explores the use of a Maximal Average Margin (MAM) optimality principle for the design of learning algorithms. It is shown that the application of this risk minimizati...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
— Due to the abundant application background, the optimization of maintenance problem has been extensively studied in the past decades. Besides the well-known difficulty of larg...
Clock network is a vulnerable victim of variations as well as a main power consumer in many integrated circuits. Recently, link-based non-tree clock network attracts people's...