H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 83 Citations 27,046 555 World Ranking 364 National Ranking 1

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Machine learning

Lawrence Carin spends much of his time researching Artificial intelligence, Pattern recognition, Bayesian probability, Machine learning and Optics. Many of his studies involve connections with topics such as Computer vision and Artificial intelligence. His studies deal with areas such as Algorithm, Logistic regression, Nonparametric statistics and Bayesian inference as well as Pattern recognition.

The study incorporates disciplines such as Inference, Data mining and Statistical model in addition to Bayesian probability. His study looks at the intersection of Machine learning and topics like Adversarial system with Matching. His Optics research includes themes of Function, Method of moments, Computational physics and Time domain.

His most cited work include:

  • Bayesian Compressive Sensing (1732 citations)
  • Sparse multinomial logistic regression: fast algorithms and generalization bounds (733 citations)
  • Multi-Task Learning for Classification with Dirichlet Process Priors (427 citations)

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

Lawrence Carin mainly focuses on Artificial intelligence, Pattern recognition, Machine learning, Algorithm and Optics. In most of his Artificial intelligence studies, his work intersects topics such as Computer vision. Pattern recognition is closely attributed to Contextual image classification in his research.

His Artificial neural network study in the realm of Machine learning interacts with subjects such as Multi-task learning. In his study, Applied mathematics is inextricably linked to Mathematical optimization, which falls within the broad field of Algorithm. His Optics study incorporates themes from Time domain, Computational physics and Method of moments.

He most often published in these fields:

  • Artificial intelligence (46.41%)
  • Pattern recognition (20.53%)
  • Machine learning (18.58%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (46.41%)
  • Machine learning (18.58%)
  • Artificial neural network (5.95%)

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

His primary areas of study are Artificial intelligence, Machine learning, Artificial neural network, Theoretical computer science and Deep learning. His Artificial intelligence research integrates issues from Natural language processing and Pattern recognition. The Feature, Leverage, Transfer of learning and Regularization research he does as part of his general Machine learning study is frequently linked to other disciplines of science, such as Forgetting, therefore creating a link between diverse domains of science.

His study in Artificial neural network is interdisciplinary in nature, drawing from both Interpretability, Monte Carlo method, Reinforcement learning and Benchmark. His Theoretical computer science research is multidisciplinary, incorporating perspectives in Autoencoder, Embedding, Inference, Sentence and Graph. The Image study which covers Upper and lower bounds that intersects with Algorithm.

Between 2018 and 2021, his most popular works were:

  • Digital technology and COVID-19. (349 citations)
  • Certified Adversarial Robustness with Additive Noise (61 citations)
  • Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing (54 citations)

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

  • Artificial intelligence
  • Statistics
  • Machine learning

Lawrence Carin mostly deals with Artificial intelligence, Machine learning, Artificial neural network, Theoretical computer science and Algorithm. His Artificial intelligence study combines topics in areas such as Pattern recognition and Natural language processing. Lawrence Carin has included themes like Simple and Invertible matrix in his Pattern recognition study.

His Machine learning study combines topics from a wide range of disciplines, such as Adversarial system, Generator and Constant. His research integrates issues of Embedding, Matching, Sentence, Interpretability and Graph in his study of Theoretical computer science. As a part of the same scientific study, Lawrence Carin usually deals with the Algorithm, concentrating on Focus and frequently concerns with Distribution.

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

Bayesian Compressive Sensing

Shihao Ji;Ya Xue;L. Carin.
IEEE Transactions on Signal Processing (2008)

2123 Citations

Sparse multinomial logistic regression: fast algorithms and generalization bounds

B. Krishnapuram;L. Carin;M.A.T. Figueiredo;A.J. Hartemink.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2005)

914 Citations

Multi-Task Learning for Classification with Dirichlet Process Priors

Ya Xue;Xuejun Liao;Lawrence Carin;Balaji Krishnapuram.
Journal of Machine Learning Research (2007)

569 Citations

Multitask Compressive Sensing

S. Ji;D. Dunson;L. Carin.
IEEE Transactions on Signal Processing (2009)

486 Citations

Exploiting Structure in Wavelet-Based Bayesian Compressive Sensing

Lihan He;L. Carin.
IEEE Transactions on Signal Processing (2009)

478 Citations

Nonparametric Bayesian Dictionary Learning for Analysis of Noisy and Incomplete Images

Mingyuan Zhou;Haojun Chen;John Paisley;Lu Ren.
IEEE Transactions on Image Processing (2012)

379 Citations

Gene Expression Signatures Diagnose Influenza and Other Symptomatic Respiratory Viral Infections in Humans

Aimee K. Zaas;Minhua Chen;Jay Varkey;Timothy Veldman.
Cell Host & Microbe (2009)

327 Citations

Compressive Coded Aperture Spectral Imaging: An Introduction

Gonzalo R. Arce;David J. Brady;Lawrence Carin;Henry Arguello.
IEEE Signal Processing Magazine (2014)

317 Citations

Probabilistic Topic Models

David Blei;Lawrence Carin;David Dunson.
IEEE Signal Processing Magazine (2010)

302 Citations

Nonparametric factor analysis with beta process priors

John Paisley;Lawrence Carin.
international conference on machine learning (2009)

298 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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