1 citations · 1 across the 8 of their papers we have counts for
8 papers
Estimating Distributions with Failure Rate Properties from Noisy Quantile Data
Timothy C. Y. Chan, Ningyuan Chen, Craig Fernandes +1
Estimating an unknown cumulative distribution function (cdf) from data, either as a statistical object of interest or as an input to a downstream optimization problem, is fundament…
Agentic Property-Based Testing: Finding Bugs Across the Python Ecosystem
Muhammad Maaz, Liam DeVoe, Zac Hatfield-Dodds +1
Property-based testing (PBT) is a lightweight formal method, typically implemented as a randomized testing framework. Users specify the input domain for their test using combinator…
A new method for reducing algebraic programs to polynomial programs
Muhammad Maaz, Adam W. Strzeboński
We consider a generalization of polynomial programs: algebraic programs, which are optimization or feasibility problems with algebraic objectives or constraints. Algebraic function…
Formal Verification of Markov Processes with Learned Parameters
Muhammad Maaz, Timothy C. Y. Chan
We introduce the problem of formally verifying properties of Markov processes where the parameters are given by the output of machine learning models. For a broad class of machine…
Exact sensitivity analysis of Markov reward processes via algebraic geometry
Timothy C. Y. Chan, Muhammad Maaz
We introduce a new approach for deterministic sensitivity analysis of Markov reward processes, commonly used in cost-effectiveness analyses, via reformulation into a polynomial sys…
On Orderings of Probability Vectors and Unsupervised Performance Estimation
Muhammad Maaz, Rui Qiao, Yiheng Zhou +1
Unsupervised performance estimation, or evaluating how well models perform on unlabeled data is a difficult task. Recently, a method was proposed by Garg et al. [2022] which perfor…
Saturating stable matchings
Muhammad Maaz
I relate bipartite graph matchings to stable matchings. I prove a necessary and sufficient condition for the existence of a saturating stable matching, where every agent on one sid…
Viability of machine learning to reduce workload in systematic review screenings in the health sciences: a working paper
Muhammad Maaz
Systematic reviews, which summarize and synthesize all the current research in a specific topic, are a crucial component to academia. They are especially important in the biomedica…