reply on: The SN home page is an auction \ stacker news

pull down to refresh

53 sats \ 4 replies \ @k00b 11 Feb \ parent \ on: The SN home page is an auction meta

Yes that's right. I store the sum because it's like the mantissa and the time because it's like the exponent. When a new zap comes in, the time allows me to discount the old sum.

Rank_{i} \leftarrow Rank_{i} \cdot e^{- λ (zap_time_{i j_{new}} - zap_time_{ij})} + zap_amount_{i j_{new}}

I think that's right.

47 sats \ 2 replies \ @SimpleStacker 11 Feb

I think you'd have to update the rank of all the other items at the same time that item $i$ gets zapped, otherwise item $i$ 's rank relative to other items might actually go down, because its old rank gets down-weighted via the exponent.

(As an example, imagine item $i$ gets a zap of just 1 sat. Its old rank gets down-weighted for time, by the increase from the 1 sat is negligible.)

68 sats \ 1 reply \ @k00b 11 Feb

That’s not the full sort key. My bad.

I’ll try to write it in a way I understand tomorrow.

74 sats \ 0 replies \ @k00b 11 Feb

Last night what I shared as $Rank_{i}$ is hot_s.

Rank_{i} = j \sum zap_amount_{ij} e^{λ zap_time_{ij}} where λ = \frac{ln 2}{4 h} .

We store hot_t and hot_s:

Rank_{i} = e^{λ hot_t_{i}} hot_s_{i}

with

hot_t_{i} = j max zap_time_{ij}, hot_s_{i} = j \sum zap_amount_{ij} e^{λ (zap_time_{ij} - hot_t_{i})} .

Substituting those definitions directly:

Rank_{i} = e^{λ m a x_{j} zap_time_{ij}} j \sum zap_amount_{ij} e^{λ (zap_time_{ij} - m a x_{j} zap_time_{ij})} .

1 sat \ 0 replies \ @k00b 11 Feb

(This mostly MathGPT btw. I'm barely hanging on trying to read forms like this.)