From c83e6ffe48145e19ca45a9c4f7245ae4328e95c1 Mon Sep 17 00:00:00 2001 From: Mehmet Hakan Satman Date: Fri, 24 Nov 2023 20:56:50 +0300 Subject: [PATCH 1/4] update bibtex --- paper/paper.bib | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/paper/paper.bib b/paper/paper.bib index 10d5221..73a63ea 100644 --- a/paper/paper.bib +++ b/paper/paper.bib @@ -192,7 +192,7 @@ @article{Richie-Halford:2021 number = {58}, pages = {3024}, author = {Adam Richie-Halford and Manjari Narayan and Noah Simon and Jason Yeatman and Ariel Rokem}, - title = {Groupyr: Sparse Group Lasso in Python}, + title = {Groupyr: Sparse Group Lasso in {P}ython}, journal = {Journal of Open Source Software} } @@ -221,7 +221,7 @@ @article{Bertrand:2022 @article{Zhu:2022, author = {Jin Zhu and Xueqin Wang and Liyuan Hu and Junhao Huang and Kangkang Jiang and Yanhang Zhang and Shiyun Lin and Junxian Zhu}, - title = {abess: A Fast Best-Subset Selection Library in Python and R}, + title = {abess: A Fast Best-Subset Selection Library in {P}ython and {R}}, journal = {Journal of Machine Learning Research}, year = {2022}, volume = {23}, @@ -314,7 +314,7 @@ @article{Xie:2023 } @article{Zhong:2022, - title = {An \$\{\textbackslash ensuremath\{\textbackslash ell\}\}\_\{0\}\{\textbackslash ensuremath\{\textbackslash ell\}\}\_\{2\}\$-Norm Regularized Regression Model for Construction of Robust Cluster Expansions in Multicomponent Systems}, + title = {An ℓ 0 ℓ 2-Norm Regularized Regression Model for Construction of Robust Cluster Expansions in Multicomponent Systems}, author = {Zhong, Peichen and Chen, Tina and Barroso-Luque, Luis and Xie, Fengyu and Ceder, Gerbrand}, year = {2022}, journaltitle = {Physical Review B}, From d6fe64a677c6898165cb4ddcdd0ed4b6b7767d42 Mon Sep 17 00:00:00 2001 From: Mehmet Hakan Satman Date: Fri, 24 Nov 2023 20:58:56 +0300 Subject: [PATCH 2/4] update bibtex --- paper/paper.bib | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/paper/paper.bib b/paper/paper.bib index 73a63ea..27e249d 100644 --- a/paper/paper.bib +++ b/paper/paper.bib @@ -314,7 +314,7 @@ @article{Xie:2023 } @article{Zhong:2022, - title = {An ℓ 0 ℓ 2-Norm Regularized Regression Model for Construction of Robust Cluster Expansions in Multicomponent Systems}, + title = {An L0 L2-Norm Regularized Regression Model for Construction of Robust Cluster Expansions in Multicomponent Systems}, author = {Zhong, Peichen and Chen, Tina and Barroso-Luque, Luis and Xie, Fengyu and Ceder, Gerbrand}, year = {2022}, journaltitle = {Physical Review B}, From f5e334c3d79a101e176a5dc4e716cd772ab9f22e Mon Sep 17 00:00:00 2001 From: Mehmet Hakan Satman Date: Fri, 24 Nov 2023 21:08:41 +0300 Subject: [PATCH 3/4] update manuscript --- paper/paper.md | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/paper/paper.md b/paper/paper.md index 3c1d0cb..de099ce 100644 --- a/paper/paper.md +++ b/paper/paper.md @@ -75,7 +75,7 @@ linear regression algorithms within a single package. Statistical regression models with structured sparsity (involving grouped covariates, sparse grouped covariates, and hierarchical relationships between covariates terms) -parametrized via Group Lasso or Best Subset Selection based objetives have been used in a +parametrized via Group Lasso or Best Subset Selection based objectives have been used in a wide range of scientific disciplines, including genomics [@Chen:2021], bioinformatics [@Ma:2007], medicine [@Kim:2012], econometrics [@Athey:2017], chemistry [@Gu:2018], and materials science [@Leong:2019]. The flexible implementation of sparse linear regression models in `sparse-lm` @@ -161,7 +161,9 @@ options are implemented. The implemented models are listed below: ## Implemented regression models The table below shows the regression models that are implemented in `sparse-lm` as well -as available implementations in other Python packages. $\checkmark$ indicates that the +as available implementations in other Python packages. $\checkmark$ indicates that the model selected +is applicable by the package located in the corresponding column. + | Model | `sparse-lm` | `celer` | `groupyr` | `group-lasso` | `skglm` | `abess` | |:-----------------------------:|:------------:|:---------:|:-----------:|:-----------:|:------------:|:------------:| From 3cb197eb820503a7dfdeafbc7047370f10a7dbc8 Mon Sep 17 00:00:00 2001 From: "pre-commit-ci[bot]" <66853113+pre-commit-ci[bot]@users.noreply.github.com> Date: Fri, 24 Nov 2023 18:13:09 +0000 Subject: [PATCH 4/4] [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --- paper/paper.md | 2 +- requirements.txt | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/paper/paper.md b/paper/paper.md index de099ce..f4be6e2 100644 --- a/paper/paper.md +++ b/paper/paper.md @@ -161,7 +161,7 @@ options are implemented. The implemented models are listed below: ## Implemented regression models The table below shows the regression models that are implemented in `sparse-lm` as well -as available implementations in other Python packages. $\checkmark$ indicates that the model selected +as available implementations in other Python packages. $\checkmark$ indicates that the model selected is applicable by the package located in the corresponding column. diff --git a/requirements.txt b/requirements.txt index 8a30e10..fef7a4c 100644 --- a/requirements.txt +++ b/requirements.txt @@ -2,4 +2,4 @@ numpy >=1.23 cvxpy >=1.2 scikit-learn > 1.2 scipy >=1.9 -joblib \ No newline at end of file +joblib