Feat/consider short term schedule [WIP]

[L-M-Sherlock]

Algorithm	Log Loss	RMSE (bins)	Parameters
FSRS-4.5	0.3236±0.1512	0.0433±0.0310	17
FSRS-4.5 + short-term	0.3206±0.1489	0.0425±0.0302	17
FSRS-4.5 + short-term + w[17]	0.3204±0.1487	0.0424±0.0299	18
FSRS-4.5 + short-term + w[17] + w[18]	0.3195±0.1483	0.0415±0.0297	19
FSRS-4.5 + short-term + w[17] + w[18] + w[19]	0.3194±0.1482	0.0415±0.0298	20

Algorithm	Log Loss	RMSE (bins)	Parameters
FSRS-4.5	0.3461±0.1681	0.0628±0.0455	17
FSRS-4.5 + short-term	0.3417±0.1650	0.0608±0.0442	17
FSRS-4.5 + short-term + w[17]	0.3418±0.1650	0.0608±0.0439	18
FSRS-4.5 + short-term + w[17] + w[18]	0.3411±0.1648	0.0600±0.0439	19
FSRS-4.5 + short-term + w[17] + w[18] + w[19]	0.3410±0.1648	0.0600±0.0439	20

Related code:

    def stability_short_term(self, state: Tensor, rating: Tensor) -> Tensor:
        new_s = state[:, 0] * torch.exp(self.w[17] * (rating - 3 + self.w[18]))
        return new_s

    def next_d_short_term(self, state: Tensor, rating: Tensor) -> Tensor:
        new_d = state[:, 1] - self.w[19] * (rating - 3)
        return new_d

@Expertium, I finished the benchmarking of four candidates considering short-term reviews. I prefer the FSRS-4.5 + short-term because it doesn't introduce any extra parameters and reduce the RMSE(bins) 3.2% (weighted by ln(number of reviews)). What do you think of?