2018 - Fellow of the American Association for the Advancement of Science (AAAS)
Steven Skiena mostly deals with Artificial intelligence, Natural language processing, Combinatorics, Sentiment analysis and Language model. His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning, Literal and Pattern recognition. The Machine learning study combines topics in areas such as Class, Anomaly detection and Training set.
His work carried out in the field of Natural language processing brings together such families of science as Polyglot, Word and Knowledge graph. His Combinatorics research focuses on subjects like Discrete mathematics, which are linked to Flexibility. His Language model research includes themes of Feature learning and Point.
Steven Skiena mainly investigates Artificial intelligence, Combinatorics, Algorithm, Natural language processing and Theoretical computer science. His work on Artificial intelligence is being expanded to include thematically relevant topics such as Machine learning. His Combinatorics research is multidisciplinary, incorporating perspectives in Discrete mathematics and Upper and lower bounds.
Steven Skiena combines subjects such as Word and Key with his study of Natural language processing.
The scientist’s investigation covers issues in Artificial intelligence, Natural language processing, Theoretical computer science, Embedding and Graph. His research integrates issues of Machine learning and Task in his study of Artificial intelligence. Particularly relevant to Deep learning is his body of work in Machine learning.
His studies in Deep learning integrate themes in fields like Class, Anomaly detection and Statistical model. His Natural language processing study incorporates themes from Word, Structure, Social media, Key and Data set. His Graph study combines topics from a wide range of disciplines, such as Matrix, Graph, Algorithm and Transitive relation.
Steven Skiena spends much of his time researching Artificial intelligence, Natural language processing, Theoretical computer science, Feature learning and Language model. His Artificial intelligence study combines topics in areas such as Social network, Machine learning, ENCODE and Personalized search. His Machine learning research integrates issues from Class and Anomaly detection, Data mining.
His biological study spans a wide range of topics, including Word, Reading, The Internet, Homophily and Social media. His research integrates issues of Hierarchy, Maxima and minima, Embedding, Set and Unsupervised learning in his study of Feature learning. His work deals with themes such as Word usage, Language change, Null model, Variation and Semantics, which intersect with Language model.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
DeepWalk: online learning of social representations
Bryan Perozzi;Rami Al-Rfou;Steven Skiena.
knowledge discovery and data mining (2014)
The Algorithm Design Manual
Steven S. Skiena.
Large-Scale Sentiment Analysis for News and Blogs
Namrata Godbole;Manjunath Srinivasaiah;Steven Skiena.
international conference on weblogs and social media (2007)
Implementing Discrete Mathematics: Combinatorics And Graph Theory With Mathematica
Virus attenuation by genome-scale changes in codon pair bias.
J. Robert Coleman;Dimitris Papamichail;Steven Skiena;Bruce Futcher.
Computational Discrete Mathematics: Combinatorics and Graph Theory with Mathematica ®
Sriram Pemmaraju;Steven Skiena.
Statistically Significant Detection of Linguistic Change
Vivek Kulkarni;Rami Al-Rfou;Bryan Perozzi;Steven Skiena.
the web conference (2015)
Optimizing triangle strips for fast rendering
Francine Evans;Steven Skiena;Amitabh Varshney.
ieee visualization (1996)
Reduction of the Rate of Poliovirus Protein Synthesis through Large-Scale Codon Deoptimization Causes Attenuation of Viral Virulence by Lowering Specific Infectivity
Steffen Mueller;Dimitris Papamichail;J. Robert Coleman;Steven Skiena.
Journal of Virology (2006)
Polyglot: Distributed Word Representations for Multilingual NLP
Rami Al-Rfou;Bryan Perozzi;Steven Skiena.
conference on computational natural language learning (2013)
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