TLBBD (Sp2018) Video Lectures
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WeekBefore
* signifies a required lecture
Link(s)Scribed Notes
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1: 16-18 Jan.- Lec 01* Roadmap of Statistical Learning (13 min)https://berkeley.box.com/v/tlbbd-sp2018-lec01https://www.overleaf.com/10706541nzjnzyhkmjwt#/40157503/
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2: 23–25 Jan.- Lec 02* Examples of Data Generating Experiments (30 min)
- Lec 03* Traditional Data Analysis (36 min)
- Read Ch. 1 of vdL&R (2011)
https://berkeley.box.com/v/tlbbd-sp2018-lec02
https://berkeley.box.com/v/tlbbd-sp2018-lec03
https://www.overleaf.com/13367195rxzqjzvdfbky#/51536702/

https://www.overleaf.com/13368740nqwrtvjqcfmc#/51543485/
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3: 30 Jan.–01 Feb.- Lec 04* SCM, Causal Quantity, Identification (59 min)
- Read Ch. 2 of vdL&R (2011)
https://berkeley.box.com/v/tlbbd-sp2018-lec04https://www.overleaf.com/13396898tsmpkdxpkzgb#/51667449/
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4: 06–08 Feb.- Lec 05* Interventions - Optimal, Stochastic, Multiple Time-Point (30 min)https://berkeley.box.com/v/tlbbd-sp2018-lec05https://www.overleaf.com/13601441wzdxjdkzbhxq#/52574194/
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5: 13–15 Feb.- Lec 06* Understanding Nonparametric Density Estimation - Super Learning of a Density (58 min)
- Read Ch. 3 of vdL&R (2011)
https://berkeley.box.com/v/tlbbd-sp2018-lec06https://www.overleaf.com/13762857qwyhncyzrjjs#/53278280/
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6: 20–22 Feb.- Lec 07* Super Learning and the Oracle Inequality; Application to Optimal Individualized Treatment Rule and Prediction of Survival Curve (51 min)https://berkeley.box.com/v/tlbbd-sp2018-lec07https://www.overleaf.com/13878335ydyhdmhthsjd#/53773954/
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7: 27 Feb.–01 Mar.- Lec 08* Super Learning of a Conditional Density or Conditional Multinomial Distribution (17 min)
- Read Ch. 18 of vdL&R (2018)
https://berkeley.box.com/v/tlbbd-sp2018-lec08https://www.overleaf.com/14050565schpmxvzygyz#/54482115/
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8: 06–08 Mar.- Lec 09* Integrals w.r.t. Measures (36 min)
- Lec 10* Highly Adaptive Lasso (HAL) (32 min)
- Lec 11 Online Super Learning (30 min)
- Read Ch. 6 of vdL&R (2018)
https://berkeley.box.com/v/tlbbd-sp2018-lec09
https://berkeley.box.com/v/tlbbd-sp2018-lec10
https://berkeley.box.com/v/tlbbd-sp2018-lec11
https://www.overleaf.com/14276868vytcbtqqzgsm#/55035699/

https://www.overleaf.com/14321441qhpxvfcmhbjd#/55149258/
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9: 13–15 Mar.- Lec 12 Empirical Probability Measure (43 min)
- Lec 13 Functional CLT for Empirical Processes (20 min)
- Lec 14* Asymptotic Linearity of an Estimator (29 min)
- Lec 15 Functional Delta Method (62 min)
- Read A.1 - A.3 of vdL&R (2011)
https://berkeley.box.com/v/tlbbd-sp2018-lec12
https://berkeley.box.com/v/tlbbd-sp2018-lec13
https://berkeley.box.com/v/tlbbd-sp2018-lec14
https://berkeley.box.com/v/tlbbd-sp2018-lec15
https://www.overleaf.com/14443463rvncychbjbgr#/55461173/
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10: 20–22 Mar.- Lec 16* Canonical Gradient/Efficient Influence Curve (46 min)
- Lec 17* Tools for Computing Projections and Canonical Gradient (36 min)
- Read A.4 of vdL&R (2011)
https://berkeley.box.com/v/tlbbd-sp2018-lec16
https://berkeley.box.com/v/tlbbd-sp2018-lec17
https://www.overleaf.com/14706687sybfmrxkkwqg#/56143425/

https://www.overleaf.com/14800248hsxtdzrdbjzb#/56388148/
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11: 03–05 Apr.- Lec 18* Efficiency Theory (41 min)
- Lec 19 Efficiency of NPMLE (40 min)
- Read A.5 of vdL&R (2011)
https://berkeley.box.com/v/tlbbd-sp2018-lec18
https://berkeley.box.com/v/tlbbd-sp2018-lec19
https://www.overleaf.com/15232254xhdcnjtzswgd#/57612583/
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12: 10–12 Apr.- Lec 20* One-Step Estimation (59 min)https://berkeley.box.com/v/tlbbd-sp2018-lec20https://www.overleaf.com/15425954hkvbsvbdtkxb#/58480939/
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13: 17–19 Apr.- Lec 21* TMLE (54 min)
- Read Ch.4 – 6 and A.6 of vdL&R (2011)
https://berkeley.box.com/v/tlbbd-sp2018-lec21https://www.overleaf.com/15600439jmvjxjzkshsn#/59257584/
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14: 24–26 Apr.ex/ Counterfactual Treatment-Specific Survival Curve:
- Lec 22 Causal Model for the Counterfactual Treatment-Specific Survival Curve (30 min)
- Lec 23 Canonical Gradient for the Counterfactual Treatment Specific Survival Curve (19 min)
- Lec 24 Super Learner of the Conditional Hazard (20 min)
- Lec 25 TMLE of the Counterfactual Treatment-Specific Survival Curve (36 min)

ex/ Longitudinal Data with Multiple Time-Point Interventions:
- Lec 26* Causal Model for Longitudinal Data with Multiple Time-Point Interventions (44 min)
- Lec 27* Sequential Regression Representation of the Target Parameter (27 min)
- Lec 28* Efficient Influence Curve for Intervention-Specific Survival Curve based on Sequential Regression (21 min)
- Lec 29* TMLE of the Intervention-Specific Survival Curve based on Sequential Regression (22 min)

CV-TMLE:
- Lec 30 CV-TMLE of a Data Adaptive Target Parameter (43 min)

- Read Ch. 3 – 4 of vdL&R (2018)
ex/ Counterfactual Treatment-Specific Survival Curve:
https://berkeley.box.com/v/tlbbd-sp2018-lec22
https://berkeley.box.com/v/tlbbd-sp2018-lec23
https://berkeley.box.com/v/tlbbd-sp2018-lec24
https://berkeley.box.com/v/tlbbd-sp2018-lec25

ex/ Longitudinal Data with Multiple Time-Point Interventions:
https://berkeley.box.com/v/tlbbd-sp2018-lec26
https://berkeley.box.com/v/tlbbd-sp2018-lec27
https://berkeley.box.com/v/tlbbd-sp2018-lec28
https://berkeley.box.com/v/tlbbd-sp2018-lec29

CV-TMLE:
https://berkeley.box.com/v/tlbbd-sp2018-lec29
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