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Multiple-Source Adaptation with Domain Classifiers
We consider the multiple-source adaptation (MSA) problem and improve a p...
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Beyond Individual and Group Fairness
We present a new data-driven model of fairness that, unlike existing sta...
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Relative Deviation Margin Bounds
We present a series of new and more favorable margin-based learning guar...
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Adaptive Region-Based Active Learning
We present a new active learning algorithm that adaptively partitions th...
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Learning GANs and Ensembles Using Discrepancy
Generative adversarial networks (GANs) generate data based on minimizing...
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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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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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Structured Prediction Theory Based on Factor Graph Complexity
We present a general theoretical analysis of structured prediction with ...
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L2 Regularization for Learning Kernels
The choice of the kernel is critical to the success of many learning alg...
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Algorithms for Learning Kernels Based on Centered Alignment
This paper presents new and effective algorithms for learning kernels. I...
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Ensembles of Kernel Predictors
This paper examines the problem of learning with a finite and possibly l...
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New Generalization Bounds for Learning Kernels
This paper presents several novel generalization bounds for the problem ...
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