International Conference On Machine Learning
| Fiscal year | Revenue | Expenses | Net | Reserve mo. | Staff % |
|---|---|---|---|---|---|
| 2018 | 4,261,207 | 2,867,303 | 1,393,904 | 5.8 | 0% |
| 2020 | 3,258,665 | 583,891 | 2,674,774 | 93.7 | 0% |
| 2021 | 878,460 | 827,606 | 50,854 | 67.3 | 0% |
| 2022 | 3,154,458 | 3,570,691 | −416,233 | 14.2 | 0% |
| 2023 | 6,132,262 | 3,684,280 | 2,447,982 | 21.7 | 0% |
In its most recent public year (2023), this organization brought in $2,447,982 more than it spent. Its reserves stood at about 21.7 months of spending, up from 5.8 in 2018. Staff pay was 0% of spending.
Reserve months = net assets ÷ average monthly spending; net assets count everything the organization owns beyond its debts — buildings and donor-restricted funds included, not just cash. Staff pay = salaries, wages, and officer compensation; it excludes benefits and payroll taxes. The IRS releases this data years after the fact — this organization's newest public year is 2023. Years refer to the calendar year in which the organization's fiscal year ended. Short-form filers do not publicly report donor-restricted balances or staffing costs. Source filings
International Conference On Machine Learning's IRS filings as a feed — one entry per filing year, through 2023. Add the address to any feed reader; in Slack, send /feed subscribe with it (pasting the link alone won't subscribe). How this feed works