World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
52
Citations
67791
World Ranking
4932
National Ranking
2291

Research.com Recognitions

  • 2008 - ACM Paris Kanellakis Theory and Practice Award For the development of Support Vector Machines, a highly effective algorithm for classification and related machine learning problems.

Overview

Corinna Cortes is affiliated with Google in the United States and specializes in computer science, with a focus on artificial intelligence. Their research portfolio includes contributions to machine learning, domain adaptation, algorithms, and related fields.

The main fields of study for this researcher include:

  • Computer Science

Within these fields, the subfields of study are:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Management Science and Operations Research
  • Computer Networks and Communications
  • Atomic and Molecular Physics, and Optics

The primary research topics covered encompass:

  • Domain Adaptation and Few-Shot Learning
  • Machine Learning and Algorithms
  • Machine Learning and Data Classification
  • Multimodal Machine Learning Applications
  • Algorithms and Data Compression
  • Advanced Bandit Algorithms Research
  • Optimization and Search Problems

Their publication record demonstrates contributions to various academic venues, particularly:

  • arXiv (Cornell University)
  • Annals of Mathematics and Artificial Intelligence
  • Serials Review
  • Clinical Lymphoma Myeloma & Leukemia

Recent papers include:

  • "Inconsistency in Conference Peer Review: Revisiting the 2014 NeurIPS Experiment" (2021) published in arXiv (Cornell University)
  • "A Discriminative Technique for Multiple-Source Adaptation" (2020) published in arXiv (Cornell University)
  • "Theory and algorithms for learning with rejection in binary classification" (2023) published in Annals of Mathematics and Artificial Intelligence
  • "Beyond Individual and Group Fairness" (2020) published in arXiv (Cornell University)
  • "Adaptive Region-Based Active Learning" (2020) published in arXiv (Cornell University)

Frequent collaborators in their work include:

  • Mehryar Mohri
  • Pranjal Awasthi
  • Giulia DeSalvo
  • Yishay Mansour
  • Ananda Theertha Suresh

A notable award received by Corinna Cortes is the ACM Paris Kanellakis Theory and Practice Award in 2008, which recognized their involvement in the development of Support Vector Machines, an algorithm used for classification and machine learning tasks.

Best Publications

  • Support-Vector Networks

    Corinna Cortes;Vladimir Vapnik

  • Comparison of classifier methods: a case study in handwritten digit recognition

    L. Bottou;C. Cortes;C. Cortes;J.S. Denker;J.S. Denker;H. Drucker;H. Drucker

  • Learning algorithms for classification: A comparison on handwritten digit recognition

    Yann Lecun;L.D. Jackel;Leon Bottou;Leon Bottou;Corinna Cortes;Corinna Cortes

  • Comparison of learning algorithms for handwritten digit recognition

    Yann Lecun;L.D. Jackel;Leon Bottou;Leon Bottou;A. Brunot

  • AUC Optimization vs. Error Rate Minimization

    Corinna Cortes;Mehryar Mohri

  • Algorithms for learning kernels based on centered alignment

    Corinna Cortes;Mehryar Mohri;Afshin Rostamizadeh

  • Boosting and other ensemble methods

    Harris Drucker;Corinna Cortes;L. D. Jackel;Yann LeCun

  • L 2 regularization for learning kernels

    Corinna Cortes;Mehryar Mohri;Afshin Rostamizadeh

  • Boosting Decision Trees

    Harris Drucker;Corinna Cortes

  • Sample Selection Bias Correction Theory

    Corinna Cortes;Mehryar Mohri;Michael Riley;Afshin Rostamizadeh

  • Learning Non-Linear Combinations of Kernels

    Corinna Cortes;Mehryar Mohri;Afshin Rostamizadeh

  • Learning Bounds for Importance Weighting

    Corinna Cortes;Yishay Mansour;Mehryar Mohri

  • Hancock: a language for extracting signatures from data streams

    Corinna Cortes;Kathleen Fisher;Daryl Pregibon;Anne Rogers

  • AdaNet: adaptive structural learning of artificial neural networks

    Corinna Cortes;Xavier Gonzalvo;Vitaly Kuznetsov;Mehryar Mohri

  • Rational Kernels: Theory and Algorithms

    Corinna Cortes;Patrick Haffner;Mehryar Mohri

  • Two-Stage Learning Kernel Algorithms

    Corinna Cortes;Mehryar Mohri;Afshin Rostamizadeh

  • Domain adaptation and sample bias correction theory and algorithm for regression

    Corinna Cortes;Mehryar Mohri

  • Confidence Intervals for the Area Under the ROC Curve

    Corinna Cortes;Mehryar Mohri

  • Communities of Interest

    Corinna Cortes;Daryl Pregibon;Chris Volinsky

  • Learning with Rejection

    Corinna Cortes;Giulia DeSalvo;Mehryar Mohri;Mehryar Mohri

Frequent Co-Authors

Mehryar Mohri
Mehryar Mohri Google (United States)
Afshin Rostamizadeh
Afshin Rostamizadeh Google (United States)
Vladimir Vapnik
Vladimir Vapnik Princeton University
Claudio Gentile
Claudio Gentile Google (United States)
John S. Denker
John S. Denker Nokia (United States)
Patrice Y. Simard
Patrice Y. Simard Microsoft (United States)
Patrick Haffner
Patrick Haffner Interactions Corporation
Michael Riley
Michael Riley Google (United States)
Yann LeCun
Yann LeCun Facebook (United States)
Léon Bottou
Léon Bottou Facebook (United States)

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