Strong self-concordance and sampling. - Aditi Laddha; Yin Tat Lee; Santosh S. Vempala (STOC, 2020)

Reducing Isotropy and Volume to KLS: An O(n3ψ2) Volume Algorithm. - He Jia; Aditi Laddha; Yin Tat Lee; Santosh S. Vempala (CoRR, 2020)

Reducing isotropy and volume to KLS: an o*(n3ψ2) volume algorithm. - He Jia; Aditi Laddha; Yin Tat Lee; Santosh S. Vempala (STOC, 2021)

A Unified Approach to Discrepancy Minimization. - Nikhil Bansal 001; Aditi Laddha; Santosh S. Vempala (APPROX/RANDOM, 2022)

Determinant Maximization via Matroid Intersection Algorithms. - Adam Brown; Aditi Laddha; Madhusudhan Pittu; Mohit Singh; Prasad Tetali (FOCS, 2022)

Efficient Determinant Maximization for All Matroids. - Adam Brown; Aditi Laddha; Madhusudhan Pittu; Mohit Singh (CoRR, 2022)

Socially fair network design via iterative rounding. - Aditi Laddha; Mohit Singh; Santosh S. Vempala (Oper. Res. Lett., 2022)

High-Dimensional Markov Chains and Applications. - Aditi Laddha (2023)

Convergence of Gibbs Sampling: Coordinate Hit-and-Run Mixes Fast. - Aditi Laddha; Santosh S. Vempala (Discret. Comput. Geom., 2023)

Approximation Algorithms for the Weighted Nash Social Welfare via Convex and Non-Convex Programs. - Adam Brown; Aditi Laddha; Madhusudhan Reddy Pittu; Mohit Singh (SODA, 2024)

Maximizing the Minimum Eigenvalue in Constant Dimension. - Adam Brown; Aditi Laddha; Mohit Singh (CoRR, 2024)

Fast algorithms for maximizing the minimum eigenvalue in fixed dimension. - Adam Brown; Aditi Laddha; Mohit Singh (Oper. Res. Lett., 2024)