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03/22/2023
Sparks of Artificial General Intelligence: Early experiments with GPT-4
Artificial intelligence (AI) researchers have been developing and refini...
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10/17/2022
Verifiable and Provably Secure Machine Unlearning
Machine unlearning aims to remove points from the training dataset of a ...
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08/06/2022
On the Fundamental Limits of Formally (Dis)Proving Robustness in Proof-of-Learning
Proof-of-learning (PoL) proposes a model owner use machine learning trai...
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07/26/2022
Generative Extraction of Audio Classifiers for Speaker Identification
It is perhaps no longer surprising that machine learning models, especia...
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06/10/2022
Hierarchical Federated Learning with Privacy
Federated learning (FL), where data remains at the federated clients, an...
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01/08/2022
CONFIDANT: A Privacy Controller for Social Robots
As social robots become increasingly prevalent in day-to-day environment...
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09/27/2021
Unrolling SGD: Understanding Factors Influencing Machine Unlearning
Machine unlearning is the process through which a deployed machine learn...
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09/20/2021
SoK: Machine Learning Governance
The application of machine learning (ML) in computer systems introduces ...
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08/03/2021
On the Exploitability of Audio Machine Learning Pipelines to Surreptitious Adversarial Examples
Machine learning (ML) models are known to be vulnerable to adversarial e...
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03/09/2021
Proof-of-Learning: Definitions and Practice
Training machine learning (ML) models typically involves expensive itera...
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07/29/2020
Detecting Anomalous Inputs to DNN Classifiers By Joint Statistical Testing at the Layers
Detecting anomalous inputs, such as adversarial and out-of-distribution ...
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03/19/2020
Face-Off: Adversarial Face Obfuscation
Advances in deep learning have made face recognition increasingly feasib...
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02/26/2020
On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping
Machine learning algorithms are vulnerable to data poisoning attacks. Pr...
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12/09/2019
Machine Unlearning
Once users have shared their data online, it is generally difficult for ...
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10/02/2019
Generating Semantic Adversarial Examples with Differentiable Rendering
Machine learning (ML) algorithms, especially deep neural networks, have ...
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05/26/2019
Enhancing ML Robustness Using Physical-World Constraints
Recent advances in Machine Learning (ML) have demonstrated that neural n...
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12/01/2018
Characterizing Privacy Perceptions of Voice Assistants: A Technology Probe Study
The increasing pervasiveness of voice assistants in the home poses sever...
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11/05/2018
