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06/28/2023
Ordering for Non-Replacement SGD
One approach for reducing run time and improving efficiency of machine l...
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06/21/2023
Towards Mitigating Spurious Correlations in the Wild: A Benchmark a more Realistic Dataset
Deep neural networks often exploit non-predictive features that are spur...
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06/08/2023
Robust Learning with Progressive Data Expansion Against Spurious Correlation
While deep learning models have shown remarkable performance in various ...
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06/02/2023
Towards Sustainable Learning: Coresets for Data-efficient Deep Learning
To improve the efficiency and sustainability of learning deep models, we...
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05/30/2023
Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias
Neural networks trained with (stochastic) gradient descent have an induc...
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05/25/2023
Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression
Contrastive learning (CL) has emerged as a powerful technique for repres...
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05/23/2023
Eliminating Spurious Correlations from Pre-trained Models via Data Mixing
Machine learning models pre-trained on large datasets have achieved rema...
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03/24/2023
A Self-supervised Framework for Improved Data-Driven Monitoring of Stress via Multi-modal Passive Sensing
Recent advances in remote health monitoring systems have significantly b...
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03/20/2023
High Probability Bounds for Stochastic Continuous Submodular Maximization
We consider maximization of stochastic monotone continuous submodular fu...
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03/13/2023
Robust Contrastive Language-Image Pretraining against Adversarial Attacks
Contrastive vision-language representation learning has achieved state-o...
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03/11/2023
Contrastive Learning under Heterophily
Graph Neural Networks are powerful tools for learning node representatio...
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02/18/2023
Data-Efficient Contrastive Self-supervised Learning: Easy Examples Contribute the Most
Self-supervised learning (SSL) learns high-quality representations from ...
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01/31/2023
Generating High Fidelity Synthetic Data via Coreset selection and Entropic Regularization
Generative models have the ability to synthesize data points drawn from ...
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10/18/2022
Not All Poisons are Created Equal: Robust Training against Data Poisoning
Data poisoning causes misclassification of test time target examples by ...
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10/15/2022
Data-Efficient Augmentation for Training Neural Networks
Data augmentation is essential to achieve state-of-the-art performance i...
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08/17/2022
Superior generalization of smaller models in the presence of significant label noise
The benefits of over-parameterization in achieving superior generalizati...
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08/14/2022
Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attacks
A powerful category of data poisoning attacks modify a subset of trainin...
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07/28/2022
Adaptive Second Order Coresets for Data-efficient Machine Learning
Training machine learning models on massive datasets incurs substantial ...
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01/29/2022
Investigating Why Contrastive Learning Benefits Robustness Against Label Noise
Self-supervised contrastive learning has recently been shown to be very ...
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05/06/2021
CrossWalk: Fairness-enhanced Node Representation Learning
The potential for machine learning systems to amplify social inequities ...
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11/15/2020
Coresets for Robust Training of Neural Networks against Noisy Labels
Modern neural networks have the capacity to overfit noisy labels frequen...
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06/26/2019
Selection Via Proxy: Efficient Data Selection For Deep Learning
Data selection methods such as active learning and core-set selection ar...
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06/05/2019
Data Sketching for Faster Training of Machine Learning Models
Many machine learning problems reduce to the problem of minimizing an ex...
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06/03/2019
Data Sampling for Graph Based Unsupervised Learning: Convex and Greedy Optimization
In a number of situations, collecting a function value for every data po...
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05/16/2019
On the Fairness of Time-Critical Influence Maximization in Social Networks
Influence maximization has found applications in a wide range of real-wo...
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05/27/2018
Dynamic Network Model from Partial Observations
Can evolving networks be inferred and modeled without directly observing...
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11/03/2014
