1 citations · 1 across the 4 of their papers we have counts for
5 papers
Decoupled Descent: Exact Test Error Tracking Via Approximate Message Passing
Max Lovig
In modern parametric model training, full-batch gradient descent (and its variants) suffers due to progressively stronger biasing towards the exact realization of training data; th…
On Universality of Non-Separable Approximate Message Passing Algorithms
Max Lovig, Tianhao Wang, Zhou Fan
Mean-field characterizations of first-order iterative algorithms -- including Approximate Message Passing (AMP), stochastic and proximal gradient descent, and Langevin diffusions -…
Almost-Optimal Local-Search Methods for Sparse Tensor PCA
Max Lovig, Conor Sheehan, Konstantinos Tsirkas +1
Local-search methods are widely employed in statistical applications, yet interestingly, their theoretical foundations remain rather underexplored, compared to other classes of est…
On The MCMC Performance In Bernoulli Group Testing And The Random Max Set-Cover Problem
Maxwell Lovig, Ilias Zadik
The group testing problem is a canonical inference task where one seeks to identify infected individuals out of a population of people, based on the outcomes of group t…
Conformal prediction for text infilling and part-of-speech prediction
Neil Dey, Jing Ding, Jack Ferrell +4
Modern machine learning algorithms are capable of providing remarkably accurate point-predictions; however, questions remain about their statistical reliability. Unlike conventiona…