Machine Learning Scientist at Tempus Labs
You can visit my Google Scholar page for my full list of publications.
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.
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%]
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.
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.
Penalised additive least squares models for high dimensional nonparametric regression and function selection.
K. Kandasamy, C. McCarter. Large-Scale Kernel Learning Workshop @ ICML, 2015.