def objective(self, params):
val = self._penalty * np.sum(params**<NUM_LIT:2>)<EOL>for winner, losers in self._data:<EOL><INDENT>idx = np.append(winner, losers)<EOL>val += logsumexp(params.take(idx) - params[winner])<EOL><DEDENT>return val<EOL>
Compute the negative penalized log-likelihood.