B9145: Topics in Trustworthy AI

Hongseok Namkoong, Columbia University, Spring 2025

Course Schedule

Date	Topics	Lecture Notes	Readings
Jan 30	Course Overview	Part 1: Course Overview, Part 2: Data-centric View of AI	CLIP
Feb 6	Language for Distribution Shifts	Slides, DRO	DISDE
Feb 13	Domain Adaptation	Underspecification, Tatsu Hashimoto's slides	A theory of learning from different domains
Feb 20	Invariance	Invariance, IRM, Domain Generalization	In Search of Lost Domain Generalization
Feb 27	LLM pre-training, SFT, RLHF	Overview, Finetuning, RLHF	GPT3
Mar 6	LLM reasoning, inference-time operations	Slides
Mar 27	Pre-training data and scaling laws	Pre-training Data, Scaling Laws	Chinchilla
April 3	Uncertainty quantification	Slides	List of references
April 10	Adaptive data collection: bandits	Slides
April 17	Adaptive data collection: Bayesian optimization & active learning	BayesOpt, Active Learning	Bayesian RL
April 24	Adaptive data collection: MDP view & UQ as generative modeling, LLM moderation	Part 1: Bayesian Adaptive MDP, Part 2: Autoregressive generation as posterior inference, Part 3: Moderation	Uncertainty as missing data

Email the instructor if you want access to lecture recordings.