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

(58:3)

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 - Ari Karchmer - Theoretical Limits of Provable Security Against Model Extraction

(12:52)

SaTML 2023 - Julien Ferry - Exploiting Fairness to Enhance Sensitive Attributes Reconstruction

(13:10)

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

(15:27)

SaTML 2023 - Nandakumar - PolyKervNets: Activation-free Neural Networks For Private Interference

(18:28)

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

(14:25)

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

(18:11)

SaTML 2023 - Nicolas Papernot - Opening Remarks

(15:41)

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

(1:38)

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

(57:9)

SaTML 2023 - Nicolas Papernot - Closing Remarks

(2:3)

SaTML 2023 - Edoardo Debenedetti - A Light Recipe to Train Robust Vision Transformers

(14:10)

SaTML 2023 - Juba Ziani - Optimal Data Acquisition with Privacy-Aware Agents

(14:23)

SaTML 2023 - Hojjat Aghakhani - VENOMAVE: Targeted Poisoning Against Speech Recognition

(14:11)

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

(15:3)

SaTML 2023 - Yingyan Zeng - ModelPred: A Framework for Predicting Trained Model from Training Data

(14:29)

SaTML 2023 - Keith Manville and Deepesh Chaudhari - Model Attribution Challenge

(1:54)