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Presentation
From Kernels to Causality00:00
Early Kernel Methods17:18:18
Support-Vector Networks - 140:58:54
Support-Vector Networks - 252:53:45
Extracting Support Data for a Given Task - 166:19:32
Extracting Support Data for a Given Task - 270:54:53
Kernel PCA87:05:05
Spectral clustering180:16:40
Link to kernel PCA182:41:50
Kernel mean embedding methods - 1184:39:44
Kernel mean embedding methods - 2196:49:56
Kernel mean embedding methods - 3236:40:00
The mean map for samples250:44:14
Witness function281:46:29
The mean map for measures - 1296:33:38
The mean map for measures - 2322:41:35
The mean map for measures - 3359:25:02
Two-sample problem371:40:00
Kernel Independence Testing383:16:59
Shift-Invariant Optical Realization401:13:07
Kernels as Green’s Functions481:29:20
Non-Injectivity of Fourier Imaging - 1505:25:16
Non-Injectivity of Fourier Imaging - 2532:21:06
Algorithmic Method558:44:36
Two papers592:57:03
Shortcomings of Machine Learning605:14:19
Amazon´s recommender614:32:07
Statistical Implications of Causality637:46:40
Functional Causal Model655:06:32
Twilight of the idols702:46:26
Restricting the Functional Model714:50:57
Causal Inference with Additive Noise, 2-Variable Case748:26:51
Identifiability Result761:58:37
Alternative View776:42:51
Causal Inference Method777:14:49
Experiments - 1780:59:29
Experiments - 2786:40:57
Independence-based Regression791:15:03
Independence of input and mechanism805:59:23
Inferring deterministic causal relations817:33:49
Causal independence implies anticausal dependence - 1834:02:30
Causal independence implies anticausal dependence - 2854:45:09
80 Cause-Effect Pairs856:33:45
80 Cause-Effect Pairs - Examples858:56:53
Methods859:29:33
Causal Learning and Anticausal Learning875:00:36
Covariate Shift and Semi-Supervised Learning895:57:58
Semi-Supervised Learning919:50:49
SSL Book Benchmark Datasets928:18:21
UCI Datasets used in SSL benchmark932:01:46
Datasets, co-regularized LS regression932:17:47
Benchmark Datasets932:43:28
Self-training does not help for causal problems932:52:48
Co-regularization helps for the anticausal problems944:15:19
Co-regularizarion hardly helps for the causal problems950:44:30
From Ordinary Differential Equations to Structural Causal Models953:19:43
Thank you956:49:04