← Authors

Corinna Cortes

39 papers · 2004–2025 · 7 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (21) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (9) πŸ—ΊοΈ Taxonomy Completionist (15) 🌈 Renaissance Researcher (7) 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (3) 🀝 Dynamic Duo (37) πŸ† Keyword Champion πŸ”¬ Deep Specialist (15) πŸ”₯ Unstoppable (10) πŸ—ƒοΈ Keyword Collector (72) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer ⚑ Prolific Year (7) πŸ’Ž Century Club (39)

Conferences

ICML (14) NIPS (14) AISTATS (5) JMLR (3) ACL (1) ALT (1) COLT (1)

Top co-authors

Mehryar Mohri (37) Vitaly Kuznetsov (8) Giulia DeSalvo (8) Claudio Gentile (6) Ningshan Zhang (6) Scott Yang (5) Dmitry Storcheus (4) Afshin Rostamizadeh (4) Anqi Mao (3) Ananda Theertha Suresh (3)

Keywords

rademacher complexity (7) kernel methods (6) online learning (6) ensemble learning (5) convex optimization (4) domain adaptation (4) regret bound (4) generalization bound (4) structured prediction (3) label complexity (3) learning theory (3) multi-class classification (3) margin bound (3) transfer learning (3) kernel learning (3) feedback graph (3) binary classification (2) active learning (2) multiple kernel learning (2) feature selection (2)

Papers

Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data ICML 2025
Differentially Private Domain Adaptation with Theoretical Guarantees ICML 2024
Cardinality-Aware Set Prediction and Top-$k$ Classification NIPS 2024
Theory and Algorithm for Batch Distribution Drift Problems AISTATS 2023
Relative Deviation Margin Bounds ICML 2021
Boosting with Multiple Sources NIPS 2021
A Discriminative Technique for Multiple-Source Adaptation ICML 2021
Online Learning with Dependent Stochastic Feedback Graphs ICML 2020
Agnostic Learning with Multiple Objectives NIPS 2020
Adaptive Region-Based Active Learning ICML 2020
Understanding the Effects of Batching in Online Active Learning AISTATS 2020
Adaptation Based on Generalized Discrepancy JMLR 2019
Regularized Gradient Boosting NIPS 2019
Learning GANs and Ensembles Using Discrepancy NIPS 2019
Region-Based Active Learning AISTATS 2019
Online Non-Additive Path Learning under Full and Partial Information ALT 2019
Online Learning with Sleeping Experts and Feedback Graphs ICML 2019
Active Learning with Disagreement Graphs ICML 2019
Online Learning with Abstention ICML 2018
Efficient Gradient Computation for Structured Output Learning with Rational and Tropical Losses NIPS 2018
AdaNet: Adaptive Structural Learning of Artificial Neural Networks ICML 2017
Boosting with Abstention NIPS 2016
Structured Prediction Theory Based on Factor Graph Complexity NIPS 2016
On-Line Learning Algorithms for Path Experts with Non-Additive Losses COLT 2015
Structural Maxent Models ICML 2015
Deep Boosting ICML 2014
Learning Ensembles of Structured Prediction Rules ACL 2014
Ensemble Methods for Structured Prediction ICML 2014
Multi-Class Classification with Maximum Margin Multiple Kernel ICML 2013
Learning Kernels Using Local Rademacher Complexity NIPS 2013
Algorithms for Learning Kernels Based on Centered Alignment JMLR 2012
Accuracy at the Top NIPS 2012
Learning Bounds for Importance Weighting NIPS 2010
Half Transductive Ranking AISTATS 2010
On the Impact of Kernel Approximation on Learning Accuracy AISTATS 2010
Learning Non-Linear Combinations of Kernels NIPS 2009
Polynomial Semantic Indexing NIPS 2009
On Transductive Regression NIPS 2006
Rational Kernels: Theory and Algorithms JMLR 2004