Oct 15, 2007 · In this paper, we propose to use a new optimization method, i.e., semidefinite programming (SDP), to solve the large-margin estimation (LME) ...

In this paper, we study a new semidefinite programming (SDP) formulation to improve optimization efficiency for large margin estimation (LME) of HMMs in speech ...

ABSTRACT. In this paper, we propose to use a new optimization method, i.e., semidefinite programming (SDP), to solve large margin estima-.

Abstract—In this paper, we propose to use a new optimiza- tion method, i.e., semidefinite programming (SDP), to solve the large-margin estimation (LME) ...

A fast optimization method for large margin estimation of HMMs based on second order cone programming · Maximum mutual information estimation via second order ...

We study the problem of parameter estimation in continuous density hidden. Markov models (CD-HMMs) for automatic speech recognition (ASR). As in sup-.

Abstract. Large margin learning of Continuous Density. HMMs with a partially labeled dataset has been extensively studied in the speech and.

Solving Large-Margin Hidden Markov Model Estimation via Semidefinite Programming. In this paper, we propose to use a new optimization method, i.e., semidefinite ...

In this paper, we study a new semidefinite programming (SDP) formulation to improve optimization efficiency for large margin estimation (LME) of HMMs in ...

We present a dual-scaling interior-point algorithm and show how it exploits the structure and sparsity of some large-scale problems.