Corinna Cortes

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Head of Google Research NY at Google, Inc., Sponsorship at NIPS 2014, MTS at Bell Labs/AT&T Laboratories from 1989-2003

research

∙ 09/20/2021

Inconsistency in Conference Peer Review: Revisiting the 2014 NeurIPS Experiment

In this paper we revisit the 2014 NeurIPS experiment that examined incon...

Corinna Cortes, et al. ∙

research

∙ 08/25/2020

Multiple-Source Adaptation with Domain Classifiers

We consider the multiple-source adaptation (MSA) problem and improve a p...

Corinna Cortes, et al. ∙

research

∙ 08/21/2020

Beyond Individual and Group Fairness

We present a new data-driven model of fairness that, unlike existing sta...

Pranjal Awasthi, et al. ∙

research

∙ 06/26/2020

Relative Deviation Margin Bounds

We present a series of new and more favorable margin-based learning guar...

Corinna Cortes, et al. ∙

research

∙ 02/18/2020

Adaptive Region-Based Active Learning

We present a new active learning algorithm that adaptively partitions th...

Corinna Cortes, et al. ∙

research

∙ 10/20/2019

Learning GANs and Ensembles Using Discrepancy

Generative adversarial networks (GANs) generate data based on minimizing...

Ben Adlam, et al. ∙

research

∙ 04/30/2019

AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles

AdaNet is a lightweight TensorFlow-based (Abadi et al., 2015) framework ...

Charles Weill, et al. ∙

research

∙ 04/18/2018

Online Non-Additive Path Learning under Full and Partial Information

We consider the online path learning problem in a graph with non-additiv...

Corinna Cortes, et al. ∙

research

∙ 05/20/2016

Structured Prediction Theory Based on Factor Graph Complexity

We present a general theoretical analysis of structured prediction with ...

Corinna Cortes, et al. ∙

research

∙ 05/09/2012

L2 Regularization for Learning Kernels

The choice of the kernel is critical to the success of many learning alg...

Corinna Cortes, et al. ∙

research

∙ 03/02/2012

Algorithms for Learning Kernels Based on Centered Alignment

This paper presents new and effective algorithms for learning kernels. I...

Corinna Cortes, et al. ∙

research

∙ 02/14/2012

Ensembles of Kernel Predictors

This paper examines the problem of learning with a finite and possibly l...

Corinna Cortes, et al. ∙

research

∙ 12/17/2009

New Generalization Bounds for Learning Kernels

This paper presents several novel generalization bounds for the problem ...

Corinna Cortes, et al. ∙

Corinna Cortes

Featured Co-authors

Yishay Mansour

Mehryar Mohri

Neil D. Lawrence

Ananda Theertha Suresh

Pranjal Awasthi

Manfred K. Warmuth

Claudio Gentile

Afshin Rostamizadeh

Ben Adlam

Ghassen Jerfel

Ningshan Zhang

Inconsistency in Conference Peer Review: Revisiting the 2014 NeurIPS Experiment

Multiple-Source Adaptation with Domain Classifiers

Beyond Individual and Group Fairness

Relative Deviation Margin Bounds

Adaptive Region-Based Active Learning

Learning GANs and Ensembles Using Discrepancy

AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles

Online Non-Additive Path Learning under Full and Partial Information

Structured Prediction Theory Based on Factor Graph Complexity

L2 Regularization for Learning Kernels

Algorithms for Learning Kernels Based on Centered Alignment

Ensembles of Kernel Predictors

New Generalization Bounds for Learning Kernels