8 papers
Diffusion Models in Finance: A Survey
Zhuohan Wang, Carmine Ventre
Diffusion generative models have rapidly emerged as powerful tools for modeling complex financial data. Their appeal is both structural and practical: they offer stable likelihood-…
Optimal Single-Pass Streaming Lower Bounds for Approximating CSPs
Noah G. Singer, Madhur Tulsiani, Santhoshini Velusamy
For an arbitrary family of predicates and any , we prove a single-pass, linear-space streaming lower bound against the gap promise pr…
Sketching approximations and LP approximations for finite CSPs are related
Noah G. Singer, Madhur Tulsiani, Santhoshini Velusamy
We identify a connection between the approximability of CSPs in two models: (i) sublinear space streaming algorithms, and (ii) the basic LP relaxation. We show that whenever the ba…
List Decoding Expander-Based Codes up to Capacity in Near-Linear Time
Shashank Srivastava, Madhur Tulsiani
We give a new framework based on graph regularity lemmas, for list decoding and list recovery of codes based on spectral expanders. Using existing algorithms for computing regulari…
Explicit Codes approaching Generalized Singleton Bound using Expanders
Fernando Granha Jeronimo, Tushant Mittal, Shashank Srivastava +1
We construct a new family of explicit codes that are list decodable to capacity and achieve an optimal list size of . In contrast to existing explicit constructions…
Simple Norm Bounds for Polynomial Random Matrices via Decoupling
Madhur Tulsiani, June Wu
We present a new method for obtaining norm bounds for random matrices, where each entry is a low-degree polynomial in an underlying set of independent real-valued random variables.…