input: Write a function to optimize a given multivariate function using an initial guess for the parameters. The function should return the optimized parameters.
  import scipy.optimize as opt 
    
  def optimize_function(function, initial_guess): 
      result = opt.minimize(function, initial_guess) 
      return result.x
  
  assert list(optimize_function(lambda x: x[0]**2 + x[1]**2, [1, 1]))==[0.0, 0.0]
  assert list(optimize_function(lambda x: (x[0]-2)**2 + (x[1]+3)**2, [0, 0]))==[2.0, -3.0]
  assert list(optimize_function(lambda x: (x[0]-1)**2 + (x[1]-1)**2, [5, 5]))==[1.0, 1.0]
output: def optimize_function(function, initial_guess): 
      result = opt.minimize(function, initial_guess) 
      return result.x