CS 7880: Foundations of Trustworthy Machine Learning

Seminar in Theoretical CS — Spring 2025

Date	Topic	Leader
Unit I — Privacy
Mon 01-06-25	Class 01: Intro Welcome / Introduction Privacy Overview	Jon
Thu 01-09-25	No Meeting	—
Mon 01-13-25	Class 02: Membership Inference Sankararaman, Obozinski, Jordan, Halperin. Genomic Privacy and Limits of Individual Detection in a Pool. Nature Genetics 2009 Dwork, Smith, Steinke, Ullman, Vadhan. Robust Traceability from Trace Amounts. FOCS 2015 Carlini, Chien, Nasr, Song, Terzis, Tramer. Membership Inference Attacks From First Principles. IEEE S&P 2022	Jon
Thu 01-16-25	Class 03: Differential Privacy Smith and Ullman. DPCourse Lecture 4 & 5	Jon
Mon 01-20-25	No Meeting (MLK Day)	—
Thu 01-23-25	Class 04: Differential Privacy Cont'd Smith and Ullman. DPCourse Lecture 4 & 5	Jon
Mon 01-27-25	Class 05: DP Machine Learning and Optimization Smith and Ullman. DPCourse Lecture 11 & 12 Abadi, Chu, Goodfellow, McMahan, Mironov, Talwar, Zhang. Deep Learning with Differential Privacy. CCS 2016	Hanna
Thu 01-30-25	Class 06: Memorization and Data Extraction Brown, Bun, Feldman, Smith, Talwar. When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning. STOC 2021 Carlini et al. Extracting Training Data from Large Language Models. USENIX 2021	Tim & Mahdi
Unit II — Fairness
Mon 02-03-25	Class 07: Individual Fairness Dwork, Hardt, Pitassi, Reingold, Zemel. Fairness Through Awareness. ITCS 2012	Jack
Thu 02-06-25	Class 08: Group and Multigroup Fairness Hardt, Price, Srebro. Equality of Opportunity in Supervised Learning. NeurIPS 2016 Kearns, Neel, Roth, Wu. Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness. ICML 2018	Michael
Mon 02-10-25	Class 09: Causality and Fairness Kilbertus et al. Avoiding Discrimination Through Causal Reasoning. NeurIPS 2017	Jeffrey
Thu 02-13-25	Class 10: Fairness Tradeoffs Kleinberg, Mullainathan, Raghavan. Inherent Trade-Offs in the Fair Determination of Risk Scores. ITCS 2017	Alenna