Although the standard OPE and OPL methods assume the same distribution of covariate between the historical and evaluation data, a covariate shift often exists in real-world applications, i.e., the distribution of the covariate of the historical data is different from that of the evaluationdata.

Then,theadversary picks a convex loss functionℓt K R with the knowledge ofHt 1 and the iteratewt, and the learnersuffersloss ℓt(wt)andproceedstothenextround.

The 3 MMD kernel used was 0.05, 0.2 and 0.9. Table 2: Ablation Study Experimental DesignLabel Add Ω? The results indicate that adding both steps to NA (i.e., transitioning It seems that the left point's failure to find the global minimum However, if we run the whole experiment one more time, it is a different story. The invertible neural network is specially designed to have hard invertibility (full reconstruction). The conditional invertible neural network uses a similar structure as an invertible neural network.

Let (t) betheparametersofmodel(4) trained by Gradient Descent(2)withquadraticloss.

Several external factors negativelyimpact accurate estimation, such as motion artifacts [5] that arise from a person's movements and performed activities [6,7], sensor misplacement [8] or slippage during wear, and environmental conditions that change over time such as low temperatures [9] or high levels of ambient light [10].