H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 47 Citations 8,447 101 World Ranking 3258 National Ranking 1693

Overview

What is she best known for?

The fields of study she is best known for:

  • Computer network
  • The Internet
  • Statistics

The scientist’s investigation covers issues in Data mining, Anomaly detection, Artificial intelligence, Backbone network and Inference. Nina Taft combines subjects such as Kalman filter, Network planning and design and Internet traffic with her study of Data mining. Her Anomaly detection research incorporates themes from Flow, Detector, Flow network, Residual and Principal component analysis.

As a part of the same scientific study, Nina Taft usually deals with the Artificial intelligence, concentrating on Machine learning and frequently concerns with Differential privacy. Her Backbone network research is multidisciplinary, relying on both Internet backbone, Autoregressive integrated moving average and Econometrics. The various areas that Nina Taft examines in her Inference study include Recommender system and World Wide Web.

Her most cited work include:

  • Traffic matrix estimation: existing techniques and new directions (485 citations)
  • Structural analysis of network traffic flows (432 citations)
  • Combining filtering and statistical methods for anomaly detection (266 citations)

What are the main themes of her work throughout her whole career to date?

Her primary areas of study are Computer network, Data mining, Anomaly detection, Distributed computing and The Internet. Host and Service provider is closely connected to Computer security in her research, which is encompassed under the umbrella topic of Computer network. Her Data mining study integrates concerns from other disciplines, such as Anomaly, Detector, Internet traffic and Artificial intelligence.

Her Anomaly detection research is multidisciplinary, incorporating elements of Real-time computing, Principal component analysis and Residual. Her work is dedicated to discovering how Distributed computing, Routing are connected with Covariance, Internet protocol suite and Telecommunications network and other disciplines. As part of one scientific family, Nina Taft deals mainly with the area of Traffic engineering, narrowing it down to issues related to the Simulation, and often Algorithm.

She most often published in these fields:

  • Computer network (24.77%)
  • Data mining (19.27%)
  • Anomaly detection (14.68%)

What were the highlights of her more recent work (between 2012-2016)?

  • Data mining (19.27%)
  • Recommender system (7.34%)
  • Inference (7.34%)

In recent papers she was focusing on the following fields of study:

Her primary scientific interests are in Data mining, Recommender system, Inference, Matrix decomposition and Encryption. Her Data mining research is multidisciplinary, incorporating perspectives in Machine learning, Survey data collection, Artificial intelligence and Joint probability distribution. Nina Taft undertakes multidisciplinary studies into Inference and Context in her work.

Her Encryption research includes themes of Algorithm, Computation and Privacy preserving. Her work in Homomorphic encryption addresses issues such as Ridge, which are connected to fields such as Information privacy, Cryptography, Regression and Big data. Her Oblivious transfer study is associated with Computer network.

Between 2012 and 2016, her most popular works were:

  • Privacy-Preserving Ridge Regression on Hundreds of Millions of Records (263 citations)
  • Privacy-preserving matrix factorization (188 citations)
  • Recommending with an agenda: active learning of private attributes using matrix factorization (32 citations)

In her most recent research, the most cited papers focused on:

  • Computer network
  • The Internet
  • Statistics

Her scientific interests lie mostly in Recommender system, Matrix decomposition, Inference, Leverage and Machine learning. Her Recommender system research includes elements of Privacy preserving, Database and Profiling. Her biological study spans a wide range of topics, including Theoretical computer science, Bayesian probability and Internet privacy.

Her studies in Machine learning integrate themes in fields like Construct, The Internet and Artificial intelligence. Her research brings together the fields of Data mining and Construct. Nina Taft carries out multidisciplinary research, doing studies in Artificial intelligence and Context.

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.

Top Publications

Traffic matrix estimation: existing techniques and new directions

A. Medina;N. Taft;K. Salamatian;S. Bhattacharyya.
acm special interest group on data communication (2002)

763 Citations

Structural analysis of network traffic flows

Anukool Lakhina;Konstantina Papagiannaki;Mark Crovella;Christophe Diot.
measurement and modeling of computer systems (2004)

640 Citations

Combining filtering and statistical methods for anomaly detection

Augustin Soule;Kavé Salamatian;Nina Taft.
internet measurement conference (2005)

411 Citations

Privacy-Preserving Ridge Regression on Hundreds of Millions of Records

V. Nikolaenko;U. Weinsberg;S. Ioannidis;M. Joye.
ieee symposium on security and privacy (2013)

362 Citations

ANTIDOTE: understanding and defending against poisoning of anomaly detectors

Benjamin I.P. Rubinstein;Blaine Nelson;Ling Huang;Anthony D. Joseph.
internet measurement conference (2009)

318 Citations

Traffic matrices: balancing measurements, inference and modeling

Augustin Soule;Anukool Lakhina;Nina Taft;Konstantina Papagiannaki.
measurement and modeling of computer systems (2005)

259 Citations

Privacy-preserving matrix factorization

Valeria Nikolaenko;Stratis Ioannidis;Udi Weinsberg;Marc Joye.
computer and communications security (2013)

257 Citations

Long-term forecasting of Internet backbone traffic: observations and initial models

K. Papagiannaki;N. Taft;Z.-L. Zhang;C. Diot.
international conference on computer communications (2003)

242 Citations

In-Network PCA and Anomaly Detection

Ling Huang;Long Nguyen;Minos Garofalakis;Michael I. Jordan.
neural information processing systems (2006)

220 Citations

The problem of synthetically generating IP traffic matrices: initial recommendations

Antonio Nucci;Ashwin Sridharan;Nina Taft.
acm special interest group on data communication (2005)

201 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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