Search Results for author: Erik Kruus

Found 8 papers, 1 papers with code

Fast Few-shot Debugging for NLU Test Suites

1 code implementation DeeLIO (ACL) 2022 Christopher Malon, Kai Li, Erik Kruus

We study few-shot debugging of transformer based natural language understanding models, using recently popularized test suites to not just diagnose but correct a problem.

Natural Language Understanding

SplitBrain: Hybrid Data and Model Parallel Deep Learning

no code implementations31 Dec 2021 Farley Lai, Asim Kadav, Erik Kruus

The recent success of deep learning applications has coincided with those widely available powerful computational resources for training sophisticated machine learning models with huge datasets.

Improving Neural Network Robustness through Neighborhood Preserving Layers

no code implementations28 Jan 2021 Bingyuan Liu, Christopher Malon, Lingzhou Xue, Erik Kruus

Finally, we empirically show that our designed network architecture is more robust against state-of-art gradient descent based attacks, such as a PGD attack on the benchmark datasets MNIST and CIFAR10.

Adversarial Attack

Defending Against Adversarial Examples by Regularized Deep Embedding

no code implementations25 Sep 2019 Yao Li, Martin Renqiang Min, Wenchao Yu, Cho-Jui Hsieh, Thomas Lee, Erik Kruus

Recent studies have demonstrated the vulnerability of deep convolutional neural networks against adversarial examples.

Adversarial Attack Adversarial Robustness

ASAP: Asynchronous Approximate Data-Parallel Computation

no code implementations27 Dec 2016 Asim Kadav, Erik Kruus

Emerging workloads, such as graph processing and machine learning are approximate because of the scale of data involved and the stochastic nature of the underlying algorithms.

BIG-bench Machine Learning

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