Conformal Prediction and Learning
Graduate Course, IISc, 2024
This is a self-taught course. The topics are designed by myself mostly following the book: Algorithmic learning in a random world by V.Vovk, A.Gammerman, and G.Shafer.
- Lec-1: Introduction and Probability review.
- Lec-2: Confidence Predictors.
- Lec-3: Conformal Predictors.
- Lec-4: Conformalized Ridge & Nearest Neighbors Regression.
- Lec-5: Efficiency of CRR Algorithm.
- Lec-6: Conformal Transducers - coming soon
- Lec-7: Conformal Prediction: criteria of efficiency - coming soon
- Lec-8: Non-conformity scores - coming soon
- Lec-9: Weak Teachers - coming soon
- Lec-10: Inductive Conformal Predictors - coming soon
- Lec-11: Non-concformity scores: further ways - coming soon
- Lec-12: Cross & Transductive Conformal Predictors - coming soon
- Lec-13: Conditional Conformal Predictors - coming soon
- Lec-14: Training Conditional Validity - coming soon
- Lec-15: Conformal Test Martingles
- Lec-16: Multi-stage Randomness Detection
- Lec-17: Testing in Anti-Causal Classification - coming soon
- Lec-18: Efficiency of Conformal Testing - coming soon
- Lec-19: Further Topics in Test Martingles - coming soon
- Lec-20: Impossibility of Estimation: Binary & Multiclass Case - coming soon
- Lec-21: Online Compression Models - coming soon
- Lec-22: Exchangeability Models - coming soon
- Lec-23: Gaussian Models - coming soon
- Lec-24: Inductive Learning - coming soon
- Lec-25: Transductive Learning - coming soon
- Lec-26: Bayesian Learning and Beyond - coming soon