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### Pandas version checks
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsn…
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I'm seeing this failure mode in Frontier CI on latest master:
```
srun -n4 --cpus-per-task 14 --gpus-per-task 2 --cpu-bind cores --network=single_node_vni /lustre/orion/ums036/proj-shared/ci/32658…
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Running this piece of code, I get
```julia
using LinearAlgebra, SparseArrays, BenchmarkTools
function _spmatmul!(C, A, B, α, β)
size(A, 2) == size(B, 1) || throw(DimensionMismatch())
…
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Related to #239—just a place to keep notes on the thought process for supporting sparse tibbles with formula preprocessors. In #245, we see:
``` r
library(tidymodels)
sparse_hotel_rates
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Right now we basically only support binary classification. This is ok for now, but we could aim to support more complex tasks:
- [ ] Ordinal regression
- [ ] Multi-class classification
- [ ] Mul…
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https://arxiv.org/abs/1707.00225
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https://arxiv.org/abs/1902.06547 to discreminate between six different algorithms.
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I was wondering if it would be difficult by any chance to also support sparse group quantile regression, by analogy to sparse group LASSO?
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For ordinary least squares regression, we should be able to support inputs pretty easily by wrapping cusolver's `csrlsvqr` function (we should probably do this in Cupy as well).
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I have precalculated estimate of `candidate_matrix` and also `Derivative matrix`… How do i use sparse regression to solve for sparse coefficient matrix ?? `solve` on SINDy assumes basis in symbolic fo…