N. Lytkin

发表

Reinforcement Learning Benchmarks and Bake-offs II A workshop at the 2005 NIPS conference

Nate Kohl, R. Miikkulainen, N. Lytkin, 2005 .

New methods for separating causes from effects in genomics data

Mikael Henaff, N. Lytkin, A. Statnikov, 2012, BMC Genomics.

A comprehensive assessment of methods for de-novo reverse-engineering of genome-scale regulatory networks.

N. Lytkin, A. Statnikov, C. Aliferis, 2011, Genomics.

Causal graph-based analysis of genome-wide association data in rheumatoid arthritis

N. Lytkin, A. Statnikov, C. Aliferis, 2011, Biology Direct.

Expanding the Understanding of Biases in Development of Clinical-Grade Molecular Signatures: A Case Study in Acute Respiratory Viral Infections

N. Lytkin, A. Statnikov, C. Aliferis, 2011, PloS one.

Variance-based clustering methods and higher order data transformations and their applications

N. Lytkin, C. Kulikowski, 2009 .

Information Theoretic Similarity Measures for Inter-domain Predicate Mapping

N. Lytkin, W. Pottenger, 2022 .

Improving development of the molecular signature for diagnosis of acute respiratory viral infections.

N. Lytkin, A. Statnikov, C. Aliferis, 2010, Cell host & microbe.

Using gene expression profiles from peripheral blood to identify asymptomatic responses to acute respiratory viral infections

N. Lytkin, A. Statnikov, C. Aliferis, 2010, BMC Research Notes.

New methods for separating causes from effects in genomics data

Mikael Henaff, N. Lytkin, A. Statnikov, 2012, BMC Genomics.

Ultra-scalable and efficient methods for hybrid observational and experimental local causal pathway discovery

Constantin F. Aliferis, Sisi Ma, Mikael Henaff, 2015, J. Mach. Learn. Res..

Improving the presentation of search results by multipartite graph clustering of multiple reformulated queries and a novel document representation

Leonid Perlovsky, S. Streltsov, I. Muchnik, 2005 .

Leveraging Higher Order Dependencies Between Features for Text Classification

William M. Pottenger, Murat Can Ganiz, Nikita I. Lytkin, 2009 .