We consider an online learning scenario in which the learner can make predictions on the basis of a fixed set of experts. We derive upper and lower relative loss bounds for a cla...
In this paper, we study an online learning algorithm in Reproducing Kernel Hilbert Spaces (RKHS) and general Hilbert spaces. We present a general form of the stochastic gradient m...
We present a novel dynamic programming framework that allows one to compute tight upper bounds for the p-values of gapped local alignments in pseudo–polynomial time. Our algorith...
We study the problem of sorting binary sequences and permutations by length-weighted reversals. We consider a wide class of cost functions, namely f( ) = for all 0, where is the...
Michael A. Bender, Dongdong Ge, Simai He, Haodong ...
In this paper, the training sequence design for multiple-input multiple-output (MIMO) orthogonal frequencydivision multiplexing (OFDM) systems under the minimum mean square error (...
Hoang Duong Tuan, Ha Hoang Kha, Ha H. Nguyen, Viet...