code: def shrink_ellips_space(hist_tasks, curr_task):
      """Shrink search space with ellipsoidal representation according to the historical knowledge"""
      hyper_param_dim = len(curr_task["space"])
      hist_opt, curr_bound = rep_task(hist_tasks, curr_task)
      matrix_a = np.zeros((hyper_param_dim, hyper_param_dim))
      vector_b = np.zeros((1, hyper_param_dim))
  
      # need to implement interior-points algorithm to solve the convex problem by CVXPY in future#
  
      return matrix_a, vector_b
  
imports: import logging
  import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: shrink_ellips_space(hist_tasks, curr_task) and returns: matrix_a,  vector_b