11 papers
Leave a Window Out: Modifying the Jackknife for Predictive Inference in Time Series
Hanyang Jiang, Rina Foygel Barber, Ashwin Pananjady +1
Conformal prediction methods enjoy strong theoretical and empirical predictive inference performance, provided the data is exchangeable and is treated symmetrically during training…
Instance-optimal stochastic convex optimization: Can we improve upon sample-average and robust stochastic approximation?
Liwei Jiang, Ashwin Pananjady
We study the unconstrained minimization of a smooth and strongly convex population loss function under a stochastic oracle that introduces both additive and multiplicative noise; t…
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…
Perfusion Imaging and Single Material Reconstruction in Polychromatic Photon Counting CT
Namhoon Kim, Ashwin Pananjady, Amir Pourmorteza +1
Background: Perfusion computed tomography (CT) images the dynamics of a contrast agent through the body over time, and is one of the highest X-ray dose scans in medical imaging. Re…
Predictive inference for time series: why is split conformal effective despite temporal dependence?
Rina Foygel Barber, Ashwin Pananjady
We consider the problem of uncertainty quantification for prediction in a time series: if we use past data to forecast the next time point, can we provide valid prediction interval…
Multiscale replay: A robust algorithm for stochastic variational inequalities with a Markovian buffer
Milind Nakul, Tianjiao Li, Ashwin Pananjady
We introduce the Multiscale Experience Replay (MER) algorithm for solving a class of stochastic variational inequalities (VIs) in settings where samples are generated from a Markov…