4 papers
Efficient reductions from a Gaussian source with applications to statistical-computational tradeoffs
Mengqi Lou, Guy Bresler, Ashwin Pananjady
Given a single observation from a Gaussian distribution with unknown mean , we design computationally efficient procedures that can approximately generate an observation from a…
Accurate, provable and fast polychromatic tomographic reconstruction: A variational inequality approach
Mengqi Lou, Kabir Aladin Verchand, Sara Fridovich-Keil +1
We consider the problem of signal reconstruction for computed tomography (CT) under a nonlinear forward model that accounts for exponential signal attenuation, a polychromatic X-ra…
Hyperparameter tuning via trajectory predictions: Stochastic prox-linear methods in matrix sensing
Mengqi Lou, Kabir Aladin Verchand, Ashwin Pananjady
Motivated by the desire to understand stochastic algorithms for nonconvex optimization that are robust to their hyperparameter choices, we analyze a mini-batched prox-linear iterat…
Computationally efficient reductions between some statistical models
Mengqi Lou, Guy Bresler, Ashwin Pananjady
We study the problem of approximately transforming a sample from a source statistical model to a sample from a target statistical model without knowing the parameters of the source…