Work

Does Knowing More Make You Easier to Trick? Adversarial Robustness of Multi-Target Regression

Year: 2025

Type: conference-paper

Abstract: Following the rapid rise of deep learning (DL) and generative artificial intelligence (GenAI), it is imperative that we gain a better understanding of how these machine learning (ML) systems actually learn. What information are DL models retaining from the training data? What reasoning capabilities do these models have? In my proposed project, I aim to tackle these pressing questions through use of an adversarial lens.

Source: Proceedings of the AAAI Conference on Artificial Intelligence

DOI: 10.1609/aaai.v39i28.35328

Author: Soyon Choi

Institution: Amherst College

Language: English

Topic: Adversarial Robustness in Machine Learning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4409381732

FWCI:

Cites: 9

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Related to: 10