Corinna Cortes
#7,144
Most Influential Person Now
Danish-American computer scientist
Corinna Cortes's AcademicInfluence.com Rankings
Corinna Cortescomputer-science Degrees
Computer Science
#346
World Rank
#359
Historical Rank
Algorithms
#17
World Rank
#17
Historical Rank
Machine Learning
#25
World Rank
#25
Historical Rank
Artificial Intelligence
#493
World Rank
#502
Historical Rank
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Computer Science
Why Is Corinna Cortes Influential?
(Suggest an Edit or Addition)According to Wikipedia, Corinna Cortes is a Danish computer scientist known for her contributions to machine learning. She is a Vice President at Google Research in New York City. Cortes is an ACM Fellow and a recipient of the Paris Kanellakis Award for her work on theoretical foundations of support vector machines.
Corinna Cortes's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Support-Vector Networks (1995) (36586)
- The mnist database of handwritten digits (2005) (5263)
- Support-vector networks (2004) (5236)
- Comparison of learning algorithms for handwritten digit recognition (1995) (668)
- Comparison of classifier methods: a case study in handwritten digit recognition (1994) (645)
- AUC Optimization vs. Error Rate Minimization (2003) (617)
- Learning algorithms for classification: A comparison on handwritten digit recognition (1995) (492)
- Algorithms for Learning Kernels Based on Centered Alignment (2012) (425)
- Boosting and Other Ensemble Methods (1994) (375)
- Learning Non-Linear Combinations of Kernels (2009) (313)
- L2 Regularization for Learning Kernels (2009) (302)
- Sample Selection Bias Correction Theory (2008) (300)
- Learning Bounds for Importance Weighting (2010) (289)
- Boosting Decision Trees (1995) (284)
- Communities of interest (2001) (247)
- AdaNet: Adaptive Structural Learning of Artificial Neural Networks (2016) (243)
- Hancock: a language for extracting signatures from data streams (2000) (209)
- Two-Stage Learning Kernel Algorithms (2010) (201)
- Rational Kernels: Theory and Algorithms (2004) (198)
- Confidence Intervals for the Area Under the ROC Curve (2004) (185)
- Domain adaptation and sample bias correction theory and algorithm for regression (2014) (173)
- Learning with Rejection (2016) (166)
- On the Impact of Kernel Approximation on Learning Accuracy (2010) (150)
- Squashing flat files flatter (1999) (148)
- Learning Curves: Asymptotic Values and Rate of Convergence (1993) (139)
- Signature-Based Methods for Data Streams (2001) (130)
- Computational Methods for Dynamic Graphs (2003) (127)
- On Transductive Regression (2006) (121)
- Generalization Bounds for Learning Kernels (2010) (120)
- Magnitude-preserving ranking algorithms (2007) (108)
- A general regression technique for learning transductions (2005) (101)
- Limits on Learning Machine Accuracy Imposed by Data Quality (1995) (98)
- Domain Adaptation in Regression (2011) (96)
- Learning Kernels Using Local Rademacher Complexity (2013) (91)
- Margin-Based Ranking Meets Boosting in the Middle (2005) (83)
- Accuracy at the Top (2012) (79)
- Boosting with Abstention (2016) (78)
- Commercial bus speed diagnosis based on GPS-monitored data (2011) (78)
- Deep Boosting (2014) (78)
- Prediction of Generalization Ability in Learning Machines (1994) (72)
- Rational Kernels (2002) (70)
- Adaptation Based on Generalized Discrepancy (2019) (59)
- Adaptation Algorithm and Theory Based on Generalized Discrepancy (2014) (57)
- Polynomial Semantic Indexing (2009) (53)
- Structured Prediction Theory Based on Factor Graph Complexity (2016) (48)
- Positive Definite Rational Kernels (2003) (48)
- Stability of transductive regression algorithms (2008) (47)
- Multi-Class Classification with Maximum Margin Multiple Kernel (2013) (44)
- A Case Study in Handwritten Digit Recognition (1994) (42)
- LP Distance and Equivalence of Probabilistic Automata (2007) (39)
- Boosting and Other Machine Learning Algorithms (1994) (39)
- On the Computation of the Relative Entropy of Probabilistic Automata (2008) (35)
- Ensemble Methods for Structured Prediction (2014) (35)
- Invited talk: Can learning kernels help performance? (2009) (35)
- An Alternative Ranking Problem for Search Engines (2007) (34)
- Online Learning with Abstention (2017) (33)
- Relative deviation learning bounds and generalization with unbounded loss functions (2013) (32)
- Giga-Mining (1998) (31)
- Hancock: A language for analyzing transactional data streams (2004) (30)
- A General Regression Framework for Learning String-to-String Mappings (2006) (30)
- Kernel Learning: Automatic Selection of Optimal Kernels (2008) (29)
- Kernel methods for learning languages (2008) (29)
- Learning sequence kernels (2008) (28)
- Lattice kernels for spoken-dialog classification (2003) (26)
- Hierarchical associative networks (1987) (25)
- Context-Free Recognition with Weighted Automata (2000) (24)
- COMPARISON OF LEARNING ALGORITHMS FOR (1995) (23)
- On the Computation of Some Standard Distances Between Probabilistic Automata (2006) (21)
- Learning Linearly Separable Languages (2006) (20)
- Efficient Computation of the Relative Entropy of Probabilistic Automata (2006) (19)
- Discrepancy-Based Algorithms for Non-Stationary Rested Bandits (2017) (19)
- Active Learning with Disagreement Graphs (2019) (18)
- Learning Languages with Rational Kernels (2007) (17)
- AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles (2019) (17)
- Region-Based Active Learning (2019) (16)
- Online Learning with Sleeping Experts and Feedback Graphs (2019) (15)
- Properties of mortar and pervious concrete with co-utilization of coal fly ash and waste glass powder as partial cement replacements (2021) (14)
- Ensembles of Kernel Predictors (2011) (14)
- Beyond Individual and Group Fairness (2020) (13)
- Adaptive Region-Based Active Learning (2020) (13)
- Inconsistency in Conference Peer Review: Revisiting the 2014 NeurIPS Experiment (2021) (13)
- Stability Analysis and Learning Bounds for Transductive Regression Algorithms (2009) (12)
- A Machine Learning Framework for Spoken-Dialog Classification (2008) (11)
- Linear and non linear models for ozone generators considering electrodes losses (2004) (11)
- New Generalization Bounds for Learning Kernels (2009) (10)
- Weighted automata kernels - general framework and algorithms (2003) (10)
- Information mining platforms: an infrastructure for KDD rapid deployment (1999) (9)
- Capacity and Complexity Control in Predicting the Spread Between Borrowing and Lending Interest Rates (1995) (9)
- Hancock (2000) (8)
- Learning with Weighted Transducers (2009) (8)
- Relative Deviation Margin Bounds (2020) (8)
- Distribution kernels based on moments of counts (2004) (7)
- Understanding the Effects of Batching in Online Active Learning (2020) (7)
- Large-Scale Training of SVMs with Automata Kernels (2010) (7)
- Regularized Gradient Boosting (2019) (7)
- Learning GANs and Ensembles Using Discrepancy (2019) (6)
- Learning Ensembles of Structured Prediction Rules (2014) (6)
- Agnostic Learning with Multiple Objectives (2020) (6)
- On-Line Learning Algorithms for Path Experts with Non-Additive Losses (2015) (6)
- Online Learning with Dependent Stochastic Feedback Graphs (2020) (5)
- Moment Kernels for Regular Distributions (2005) (5)
- Diagnosis of milling systems performance based on operating window and mill consumption correlations (1996) (5)
- Multi-Armed Bandits with Non-Stationary Rewards (2017) (4)
- Kernel Extraction via Voted Risk Minimization (2015) (4)
- On-line Learning with Abstention (2017) (4)
- A Discriminative Technique for Multiple-Source Adaptation (2021) (4)
- A Dual Coordinate Descent Algorithm for SVMs Combined with Rational Kernels (2011) (3)
- Large-scale Distributed Optimization for Improving Accuracy at the Top (2012) (3)
- Intake and digestion of fatty acids by dairy cows fed whole flaxseed and Ca salts of flaxseed oil (2011) (3)
- Half Transductive Ranking (2010) (2)
- Structural Maxent Models (2015) (2)
- Efficient Gradient Computation for Structured Output Learning with Rational and Tropical Losses (2018) (2)
- MASCULINIZACIÓN DEL DERECHO. GIRO DEL DISCURSO JURÍDICO TRADICIONAL HACIA EL ENFOQUE DE GÉNERO 1 LAW AS A MALE STRUCTURE: TURN TOWARD THE LEGAL APPROACH TO THE GENDER (2012) (2)
- Boosting with Multiple Sources (2021) (2)
- Finite-State Transducers in Computational Biology (2005) (1)
- Multiple-Source Adaptation with Domain Classifiers (2020) (1)
- Associative memory based real-valued pattern recall (2004) (1)
- SVM Optimization for Lattice Kernels (2010) (1)
- Predicting transportpath degradation/failure based on recent performance history (1994) (0)
- Online Non-Additive Path Learning under Full and Partial Information (2018) (0)
- Des algorithmes d'apprentissage pour mieux classifier (2009) (0)
- BATCH normalization STROKE (2016) (0)
- Relative deviation learning bounds and generalization with unbounded loss functions (2019) (0)
- Handwritten Digit Recognition Using TensorFlow Lite Micro on i.MX RT devices (2021) (0)
- Generalized Discrepancy for Domain Adaptation (2015) (0)
- Air carrier liability and automation issues (2002) (0)
- Radiochemical Separation and Measurement by Mass Spectrometry with Magnetic Sector with Inductively Coupled Plasma source (ICP-SFMS) of Plutonium Isotopes in Soil Samples (2016) (0)
- Structured Prediction Theory and Voted Risk Minimization (2016) (0)
- Voted Kernel Regularization (2015) (0)
- On-line Learning Approach to Ensemble Methods for Structured Prediction (2014) (0)
- Tutorial HandOuts – Weighted Finite-State Transducers in Computational Biology (2005) (0)
- Measuring Learnability in Structured Prediction using Factor Graph Complexity ∗ (2016) (0)
- In Memoriam, Doctor Saúl Rugeles Moreno (1994) (0)
- Boosting Ensembles of Structured Prediction Rules ∗ (2014) (0)
- Effect of supplementation with sunflower oil ( SO ) or seeds ( SS ) combined or not with fish oil ( FO ) on conjugated linoleic acid ( CLA ) in milk from grazing dairy cows (2008) (0)
- A Theoretical Framework for Structured Prediction using Factor Graph Complexity ∗ (2016) (0)
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