SaTML 2023 - Zico Kolter - Robustness in Machine Learning: A Five-Year Retrospective

(1:1:51)

SaTML 2023 - Katharina Beckh - SoK: Harnessing Prior Knowledge for Explainable Machine Learning

(10:45)

SaTML 2023 - Yao Qin - What Are Effective Labels for Augmented Data?

(15:57)

SaTML 2023 - Kawakami - Validity Perspec on Evaluating Justified Use of Data-driven Decision-making

(17:37)

SaTML 2023 - Krishna Acharya - Wealth Dynamics Over Generations: Analysis and Interventions

(13:8)

SaTML 2023 - Sanghyun Hong - Publishing Efficient On-device Models Increases Adversarial Vuln.

(12:51)

SaTML 2023 - Carlini \u0026 Jagielski - Improving train data extraction attacks on large language models

(58:3)

SaTML 2023 - Jacob Steinhardt - Aligning ML Systems with Human Intent

(57:9)

SaTML 2023 - Giovanni Apruzzese - Real Attackers Don’t Compute Gradients

(15:3)

1st IEEE Conference on Secure and Trustworthy Machine Learning (SaTML 2023)

(1:38)

SaTML 2023 - Teresa Datta - Position: Tensions Between the Proxies of Human Values in AI

(13:28)

SaTML 2023 - Timnit Gebru - Eugenics and the Promise of Utopia through AGI

(48:30)

SaTML 2023 - Gautam Kamath - An Introduction to Differential Privacy

(59:30)

SaTML 2023 - J. Zhang - CARE: Certifiably Robust Learning with Reasoning via Variational Inference

(14:25)

SaTML 2023 - James Bailey - Backdoor Attacks on Time Series: A Generative Approach

(15:27)

SaTML 2023 - Liu - Towards Transferable Unrestricted Adversarial Examples with Minimum Changes

(12:13)

SaTML 2023 - Stephen Casper - SoK: Toward Transparent AI: Interpreting the Inner Structures of DNNs

(18:11)

SaTML 2023 - Nicolas Papernot - Opening Remarks

(15:41)