In order to improve the estimation accuracy and convergence speed of millimeter-wave multiple-input multiple-output （MIMO） cascaded channel assisted by intelligent reflective surface （IRS）， the conventional bilinear alternating least squares （BALS） algorithm is improved to ω-BALS algorithm with relaxation factor and regularized T-BALS， to speeds up the convergence speed and stability based on parallel factor （PARAFAC） decomposition. When one of the numbers of array antennas on the base station， IRS element or user side is large， an improved （Singular value decomposition，svd）-BALS algorithm is proposed. The algorithm reconstructs the mode-n matrices by compressing it into a low-dimensional core tensor via singular value decomposition. Simulation results show that the normalized mean squared error performance of the algorithm is improved and the convergence speed is accelerated.