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06/15/2023
Differentially Private Domain Adaptation with Theoretical Guarantees
In many applications, the labeled data at the learner's disposal is subj...
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05/10/2023
Best-Effort Adaptation
We study a problem of best-effort adaptation motivated by several applic...
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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...
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08/25/2020
Multiple-Source Adaptation with Domain Classifiers
We consider the multiple-source adaptation (MSA) problem and improve a p...
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08/21/2020
Beyond Individual and Group Fairness
We present a new data-driven model of fairness that, unlike existing sta...
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06/26/2020
Relative Deviation Margin Bounds
We present a series of new and more favorable margin-based learning guar...
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02/18/2020
Adaptive Region-Based Active Learning
We present a new active learning algorithm that adaptively partitions th...
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10/20/2019
Learning GANs and Ensembles Using Discrepancy
Generative adversarial networks (GANs) generate data based on minimizing...
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04/30/2019
AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles
AdaNet is a lightweight TensorFlow-based (Abadi et al., 2015) framework ...
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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...
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05/20/2016
Structured Prediction Theory Based on Factor Graph Complexity
We present a general theoretical analysis of structured prediction with ...
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05/09/2012
L2 Regularization for Learning Kernels
The choice of the kernel is critical to the success of many learning alg...
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03/02/2012
Algorithms for Learning Kernels Based on Centered Alignment
This paper presents new and effective algorithms for learning kernels. I...
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02/14/2012
Ensembles of Kernel Predictors
This paper examines the problem of learning with a finite and possibly l...
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12/17/2009
