2.5k citations · 3.3k across the 61 of their papers we have counts for
74 papers
Data Attribution via Sketched Metadifferentiation
Yuxi Chen, Hamza Golubovic, Han Tong +2
Data attribution seeks to quantify how individual training examples shape a model's predictions and underpins problems including data valuation, machine unlearning, and model inter…
Instance Optimal Sparse Recovery from Nonlinear Observations: A Unified Framework
Junren Chen, Arian Maleki
This paper develops a unified framework for instance optimal sparse recovery from nonlinear observations. The main ingredient is a signal-dependent restricted approximate invertibi…
High-Dimensional Statistics: Reflections on Progress and Open Problems
Arian Maleki, Subhabrata Sen, Sivaraman Balakrishnan +9
Over the past two decades, the field of high-dimensional statistics has experienced substantial progress, driven largely by technological advances that have dramatically reduced th…
Maximum Likelihood Reconstruction for Multi-Look Digital Holography with Markov-Modeled Speckle Correlation
Xi Chen, Arian Maleki, Shirin Jalali
Multi-look acquisition is a widely used strategy for reducing speckle noise in coherent imaging systems such as digital holography. By acquiring multiple measurements, speckle can…
Monte Carlo Maximum Likelihood Reconstruction for Digital Holography with Speckle
Xi Chen, Arian Maleki, Shirin Jalali
In coherent imaging, speckle is statistically modeled as multiplicative noise, posing a fundamental challenge for image reconstruction. While maximum likelihood estimation (MLE) pr…
Imperfect Influence, Preserved Rankings: A Theory of TRAK for Data Attribution
Han Tong, Shubhangi Ghosh, Haolin Zou +1
Data attribution, tracing a model's prediction back to specific training data, is an important tool for interpreting sophisticated AI models. The widely used TRAK algorithm address…