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06/28/2023
On information captured by neural networks: connections with memorization and generalization
Despite the popularity and success of deep learning, there is limited un...
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06/22/2023
Identifying and Disentangling Spurious Features in Pretrained Image Representations
Neural networks employ spurious correlations in their predictions, resul...
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03/02/2023
A Meta-Learning Approach to Predicting Performance and Data Requirements
We propose an approach to estimate the number of samples required for a ...
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01/28/2023
Supervision Complexity and its Role in Knowledge Distillation
Despite the popularity and efficacy of knowledge distillation, there is ...
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10/04/2021
Information-theoretic generalization bounds for black-box learning algorithms
We derive information-theoretic generalization bounds for supervised lea...
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01/17/2021
Estimating informativeness of samples with Smooth Unique Information
We define a notion of information that an individual sample provides to ...
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02/19/2020
Improving Generalization by Controlling Label-Noise Information in Neural Network Weights
In the presence of noisy or incorrect labels, neural networks have the u...
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05/30/2019
Efficient Covariance Estimation from Temporal Data
Estimating the covariance structure of multivariate time series is a fun...
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04/30/2019
MixHop: Higher-Order Graph Convolution Architectures via Sparsified Neighborhood Mixing
Existing popular methods for semi-supervised learning with Graph Neural ...
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03/22/2017
