collaborators

7 papers

cs.DS2026

Structural Corrections to the Bethe Approximation of the Permanent

Ijay Narang, Will Perkins

We study deterministic approximation algorithms for the permanent of a nonnegative matrix through the Bethe permanent, an approximation computable in polynomial time. The tight ana…

cs.DS2026

The Hard-Core Model on Bipartite Spectral Expanders: Counting and Sampling at All Fugacities

Ijay Narang, Will Perkins

We study approximate counting and sampling algorithms for the hard-core model on -regular bipartite graphs under a spectral expansion condition. Let be the biadjacency mat…

cs.DS2026

Computational Thresholds for Balanced and Fixed-Slice Independent Sets in Bipartite Graphs

Ijay Narang, Will Perkins, Yuzhou Wang +1

Motivated by recent work of Kocurek, Oveis Gharan, and Tjowasi, which gives an efficient sampling algorithm for the hard-core model on random regular bipartite graphs by decomposin…

math.CO2026

Schrijver Number Quasi-Tensorization and Multicolor Ramsey Bounds via Robust OR Polynomials

Ijay Narang, Yukai Tang

We introduce a robust OR polynomial framework for composing positive semidefinite certificates across OR constraints. We demonstrate the power of this method in two applications. T…

math.ST2026

Optimal detection of planted stars via a random energy model

Ijay Narang, Will Perkins, Timothy L. H. Wee

We study the problem of detecting a planted star in the Erd{ő}s--R{é}nyi random graph , formulated as a hypothesis test. We determine the scaling window for critical detect…

cs.LG2026

Constant-Stepsize Stochastic Approximation: Finite-Time Convergence, Gaussian Approximation, and Tail Bounds

Zedong Wang, Yuyang Wang, Ijay Narang +3

Constant-stepsize stochastic approximation (SA) is widely used in learning for computational efficiency, yet the distribution of the iterates is typically intractable. Classical as…