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Found 5 papers, 1 papers with code
Using Error Decay Prediction to Overcome Practical Issues of Deep Active Learning for Named Entity Recognition
Existing deep active learning algorithms achieve impressive sampling efficiency on natural language processing tasks.
Interactive Learning from Multiple Noisy Labels
Interactive learning is a process in which a machine learning algorithm is provided with meaningful, well-chosen examples as opposed to randomly chosen examples typical in standard supervised learning.
Comparing Nonparametric Bayesian Tree Priors for Clonal Reconstruction of Tumors
Statistical machine learning methods, especially nonparametric Bayesian methods, have become increasingly popular to infer clonal population structure of tumors.
Reconstructing subclonal composition and evolution from whole genome sequencing of tumors
Tumors often contain multiple subpopulations of cancerous cells defined by distinct somatic mutations.
Inferring clonal evolution of tumors from single nucleotide somatic mutations
High-throughput sequencing allows the detection and quantification of frequencies of somatic single nucleotide variants (SNV) in heterogeneous tumor cell populations.
