Calvin McCarter

Machine Learning Scientist at Tempus Labs

Publications

You can visit my Google Scholar page for my full list of publications.



preprints

Real-world Evidence of Diagnostic Testing and Treatment Patterns in US Breast Cancer Patients with Implications for Treatment Biomarkers from RNA-sequencing Data.
LE Fernandes, CG Epstein, AM Bobe, JSK Bell, MC Stumpe, ME Salazar, AA Salahudeen, A Ruth, C McCarter, BD Leibowitz, M Kase, C Igartua, R Huether, A Hafez, N Beaubier, MD Axelson, MD Pegram, SL Sammons, JA OShaughnessy, GA Palmer.
[medRxiv preprint]

peer-reviewed papers

Learning Gene Networks Underlying Clinical Phenotypes Using SNP Perturbation.
C McCarter, J Howrylak, S Kim.
PLOS Computational Biology, 2020.
[paper] [bioRxiv preprint]

Large-Scale Optimization Algorithms for Sparse Conditional Gaussian Graphical Models.
C McCarter, S Kim.
International Conference on Artificial Intelligence and Statistics (AISTATS), 2016.
[pdf] [supplement] [poster] [Acceptance rate = 30.7%]

On Sparse Gaussian Chain Graph Models.
C McCarter, S Kim.
Advances in Neural Information Processing Systems (NeurIPS), 2014.
[pdf] [poster] [Acceptance rate = 24.7%]

Active Learning with Partially Featured Data.
S Moon, C McCarter, YH Kuo.
Proceedings of the 23rd International Conference on World Wide Web (WWW), 2014.

Prediction of Glycan Motifs Using Quantitative Analysis of Multi-lectin Binding.
C McCarter, D Kletter, H Tang, K Partyka, Y Ma, S Singh, J Yadav, M Bern, BB Haab.
Proteomics Clinical Applications, 2013.

Simulation-based Signal Selection for State Restoration in Silicon Debug.
D Chatterjee, C McCarter, V Bertacco.
Proceedings of the International Conference on Computer-Aided Design (ICCAD), 2011.

selected refereed abstracts

Transcriptome background tissue correction in metastatic cancers using a correlated composition admixture model. C McCarter, B Leibowitz, J Michuda, JSK Bell, C Igartua, KP White.
Proceedings of the Annual Meeting of the American Association for Cancer Research 2020.
[abstract]

Penalised additive least squares models for high dimensional nonparametric regression and function selection.
K. Kandasamy, C. McCarter. Large-Scale Kernel Learning Workshop @ ICML, 2015.
[pdf]