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03/02/2023
GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces
In this paper we focus on the problem of generating high-quality, privat...
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01/06/2023
TrojanPuzzle: Covertly Poisoning Code-Suggestion Models
With tools like GitHub Copilot, automatic code suggestion is no longer a...
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10/20/2022
Balanced Adversarial Training: Balancing Tradeoffs between Fickleness and Obstinacy in NLP Models
Traditional (fickle) adversarial examples involve finding a small pertur...
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09/02/2022
Are Attribute Inference Attacks Just Imputation?
Models can expose sensitive information about their training data. In an...
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05/25/2022
Memorization in NLP Fine-tuning Methods
Large language models are shown to present privacy risks through memoriz...
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06/07/2021
Formalizing Distribution Inference Risks
Property inference attacks reveal statistical properties about a trainin...
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04/30/2021
Stealthy Backdoors as Compression Artifacts
In a backdoor attack on a machine learning model, an adversary produces ...
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03/24/2021
Improved Estimation of Concentration Under â„“_p-Norm Distance Metrics Using Half Spaces
Concentration of measure has been argued to be the fundamental cause of ...
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11/03/2020
Finding Friends and Flipping Frenemies: Automatic Paraphrase Dataset Augmentation Using Graph Theory
Most NLP datasets are manually labeled, so suffer from inconsistent labe...
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06/30/2020
Model-Targeted Poisoning Attacks: Provable Convergence and Certified Bounds
Machine learning systems that rely on training data collected from untru...
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05/25/2020
Pointwise Paraphrase Appraisal is Potentially Problematic
The prevailing approach for training and evaluating paraphrase identific...
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05/21/2020
Revisiting Membership Inference Under Realistic Assumptions
Membership inference attacks on models trained using machine learning ha...
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04/21/2020
Certifying Joint Adversarial Robustness for Model Ensembles
Deep Neural Networks (DNNs) are often vulnerable to adversarial examples...
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03/20/2020
One Neuron to Fool Them All
Despite vast research in adversarial examples, the root causes of model ...
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03/01/2020
Understanding the Intrinsic Robustness of Image Distributions using Conditional Generative Models
Starting with Gilmer et al. (2018), several works have demonstrated the ...
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02/26/2020
Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization
Training machine learning models to be robust against adversarial inputs...
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12/10/2019
Advances and Open Problems in Federated Learning
Federated learning (FL) is a machine learning setting where many clients...
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10/30/2019
Efficient Privacy-Preserving Nonconvex Optimization
While many solutions for privacy-preserving convex empirical risk minimi...
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08/19/2019
Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries
In a black-box setting, the adversary only has API access to the target ...
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05/29/2019
Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness
Many recent works have shown that adversarial examples that fool classif...
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02/24/2019
When Relaxations Go Bad: "Differentially-Private" Machine Learning
Differential privacy is becoming a standard notion for performing privac...
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01/28/2019
Context-aware Monitoring in Robotic Surgery
Robotic-assisted minimally invasive surgery (MIS) has enabled procedures...
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12/28/2018
EPPA for two-graphs and antipodal metric spaces
We prove that the class of two-graphs has the extension property for par...
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10/22/2018
Cost-Sensitive Robustness against Adversarial Examples
Several recent works have developed methods for training classifiers tha...
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05/06/2018
Smoothing and Mapping using Multiple Robots
Mapping expansive regions is an arduous and often times incomplete when ...
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05/05/2018
AutoTiering: Automatic Data Placement Manager in Multi-Tier All-Flash Datacenter
In the year of 2017, the capital expenditure of Flash-based Solid State ...
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01/26/2018
Learning to Evade Static PE Machine Learning Malware Models via Reinforcement Learning
Machine learning is a popular approach to signatureless malware detectio...
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12/23/2017
Query-limited Black-box Attacks to Classifiers
We study black-box attacks on machine learning classifiers where each qu...
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04/04/2017