Corinna Cortes
39 papers · 2004–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π Conference Polyglot (7) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (15) π Academic Marathon (21)
πΊοΈ
Taxonomy Completionist
(15)
π
Renaissance Researcher
(7)
π§
Keyword Pioneer
π
Keyword Trendsetter Combo
(3)
π€
Dynamic Duo
(37)
π
Keyword Champion
π¬
Deep Specialist
(15)
π₯
Unstoppable
(10)
ποΈ
Keyword Collector
(72)
π
Trend Setter
π
Conference Pioneer
β‘
Prolific Year
(7)
π
Century Club
(39)
Conferences
ICML (14)
NIPS (14)
AISTATS (5)
JMLR (3)
ACL (1)
ALT (1)
COLT (1)
Top co-authors
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