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11/09/2022
Accelerating Adversarial Perturbation by 50 Propagation
Adversarial perturbation plays a significant role in the field of advers...
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09/30/2022
Differentially Private Optimization on Large Model at Small Cost
Differentially private (DP) optimization is the standard paradigm to lea...
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09/30/2022
Differentially Private Bias-Term only Fine-tuning of Foundation Models
We study the problem of differentially private (DP) fine-tuning of large...
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06/14/2022
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger
Per-example gradient clipping is a key algorithmic step that enables pra...
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05/21/2022
Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy
Large convolutional neural networks (CNN) can be difficult to train in t...
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02/25/2022
Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity
Interpretable machine learning has demonstrated impressive performance w...
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07/02/2021
Asymptotic Statistical Analysis of Sparse Group LASSO via Approximate Message Passing Algorithm
Sparse Group LASSO (SGL) is a regularized model for high-dimensional lin...
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06/20/2021
Privacy Amplification via Iteration for Shuffled and Online PNSGD
In this paper, we consider the framework of privacy amplification via it...
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06/17/2021
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting
We show that adding differential privacy to Explainable Boosting Machine...
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05/27/2021
Characterizing the SLOPE Trade-off: A Variational Perspective and the Donoho-Tanner Limit
Sorted l1 regularization has been incorporated into many methods for sol...
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02/14/2021
Efficient Designs of SLOPE Penalty Sequences in Finite Dimension
In linear regression, SLOPE is a new convex analysis method that general...
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02/05/2021
Fast and Memory Efficient Differentially Private-SGD via JL Projections
Differentially Private-SGD (DP-SGD) of Abadi et al. (2016) and its varia...
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10/25/2020
A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks
When equipped with efficient optimization algorithms, the over-parameter...
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07/21/2020
The Complete Lasso Tradeoff Diagram
A fundamental problem in the high-dimensional regression is to understan...
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11/26/2019
Deep Learning with Gaussian Differential Privacy
Deep learning models are often trained on datasets that contain sensitiv...
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07/17/2019
