This paper improves the theoretical bounds for estimating discrete probability distributions using the $\ell_\infty$ norm, resolving several open questions in the field.

The paper establishes information-theoretic lower bounds for stochastic optimization using low-bit gradients by reducing the problem to compressed Gaussian mean estimation, yielding sharp bounds on co…

This paper investigates the design of dual-function radar-communication systems for massive MIMO systems using 1-bit DACs and ADCs, optimizing the transmit signal matrix for enhanced sensing performan…

This paper derives Cramér-Rao lower bounds for cooperative MIMO integrated sensing and communication networks, considering position and velocity coupling in the Fisher information matrix.

The paper proves a stochastic comparison for Gaussian maxima, resolving the Weak Simplex Conjecture and proving the Simplex Mean Width Conjecture.

This paper analyzes direction-of-arrival estimation using a tunable receive-side lossless reciprocal MiLAC combiner for antenna arrays and shows it can achieve the digital Cramér-Rao bound with fewer…

This paper unconditionally proves the Orthogonal Vectors and Monotone Orthogonal Vectors conjectures in concrete computational models, and provides stronger lower bounds for Boolean formulas and branc…

This paper derives the Cramer-Rao lower bound for 3D localization in UAV-assisted ISAC systems and validates the results through simulations.

The paper analyzes the structured CVP distance on the log-unit lattice of cyclotomic fields, significantly reducing the conjectured CDPR factor for the ML-KEM cryptosystem from exponential to sub-poly…

This paper characterizes how estimation error in covariance matrices affects the global minimum-variance portfolio and derives a decision geometry for regret.

This paper analyzes the statistical and computational limits of learning bounded linear operators between Sobolev spaces from noisy data, and constructs a finite-resolution blockwise least-squares est…

This paper proves space lower bounds for entropy-efficient random sampling using i.i.d. uniform bits.

This paper investigates the necessity of interaction for order-optimal 1-bit mean estimation in nonparametric finite-moment classes.

This paper establishes a direct connection between Approximate Message Passing (AMP) and the Convex Gaussian Min-max Theorem (CGMT) for regularized linear regression and M-estimation.

This paper derives the Cramer-Rao lower bound for target state estimation in a distributed radar sensing system, revealing a tradeoff between update rate and quantization fidelity.

This paper studies covert communication in a scalar Gaussian model, deriving the maximal reliably transmissible covert payload and establishing first-order optimality.

This paper introduces and analyzes a consistent estimator for the sub-Gaussian parameter ($\xi_*^2$), providing convergence rates and demonstrating its applicability in large-scale biological enrichme…