SlowGuess/NeurIPS_2023_OCR huggingface dataset:
$\mathcal{A}_L$  Concatenation of closed-loop dynamics matrices—see Proposition 3
A Dynamics matrix
$H$  Observation matrix
$m_0$  Initial state mean vector
$P$  Error covariance matrix
$P_0$  Initial state covariance matrix
$Q$  State noise covariance matrix
$R$  Output (measurement) noise covariance matrix
Combined noise vector
$\hat{x}$  Estimation of state vector
$\hat{y}$  Estimation of output vector
$\mathcal{C}_{\tau}$ $s_0 / \tau$  -neighborhood of the globally optimal policy  $L^{*}$
$\mathcal{M}_L$  Concatenated matrix regarding the differential of  $\varepsilon (L,\mathcal{Y}_T)$  -see Proposition 3
$\mathcal{N}_L$  Concatenated matrix regarding the differential of  $\varepsilon (L,\mathcal{Y}_T)$  -see Proposition 3
Set of Schur stabilizing policies
$\mathcal{S}_{\alpha}$ $\alpha$  -sublevel set of  $J$  contained in  $\mathcal{S}$
$\mathcal{U}$  Trajectory of adjoint input vector
$\mathcal{X}_L$  Concatenated matrix regarding the differential of  $\varepsilon (L,\mathcal{Y}_T)$  -see Proposition 3
$\mathcal{V}$  Trajectory of output vectors
$\nabla \widehat{J}$  Estimation of gradient of cost function
$\nabla J$  Gradient of cost function
Output (measurement) noise vector
$\partial S$  Boundary of the set of Schur stabilizing policies
$\varepsilon(L, \mathcal{Y}_T)$  Squared-norm of the estimation error vector of policy  $L$  for trajectory  $\mathcal{Y}_T$
$\vec{\eta}$  Concatenated combined noise vector
$\vec{\omega}$  Concatenated measurement noise vector
$\vec{\xi}^{\prime}$  Concatenated state noise vector
$\hat{J}_T$  Estimation of the cost function on length  $T$  trajectory
$\xi$  State (dynamics) noise vector
$e_{T}(L)$  Estimation error vector of policy  $L$  for trajectory  $\mathcal{V}_T$
$J$  Cost function
$J_{T}$  Cost function on length  $T$  trajectory
$L$  Filtering policy matrix
$u$  （204 Adjoint input vector
$X$  Cost matrix
$x$  State vector
$X_{T}$  Cost matrix on length  $T$  trajectory
$Y$  Auxiliary cost matrix
$y$  Output (measurement) vector
$z$  Adjoint state vector