Efficient and Provable Algorithms for Covariate Shift [PDF]
Deeksha Adil, Jarosław Błasiok
To appear at ALT 2026
Convex optimization with p-norm oracles [PDF]
Deeksha Adil, Brian Bullins, Arun Jambulapati, Aaron Sidford
To appear at ALT 2026
Balancing Gradient and Hessian Queries in Non-Convex Optimization [PDF]
Deeksha Adil, Brian Bullins, Aaron Sidford, Chenyi Zhang
NeurIPS 2025
Deeksha Adil, Shunhua Jiang, Rasmus Kyng
ICALP 2025
Decremental (1+\epsilon)-Approximate Maximum Eigenvector: Dynamic Power Method [PDF]
Deeksha Adil, Thatchaphol Saranurak
ICALP 2025
Deeksha Adil, Rasmus Kyng, Richard Peng, Sushant Sachdeva
Journal of ACM 2024
Deeksha Adil, Brian Bullins, Sushant Sachdeva
NeurIPS 2021
Almost-linear-time Weighted l_p-norm Solvers in Slightly Dense Graphs via Sparsification [PDF] [Video]
Deeksha Adil, Brian Bullins, Rasmus Kyng, Sushant Sachdeva
ICALP 2021
Faster p-norm minimizing flows, via smoothed q-norm problems [PDF]
Deeksha Adil, Sushant Sachdeva
SODA 2020
Deeksha Adil, Richard Peng, Sushant Sachdeva
NeurIPS 2019
Iterative Refinement for l_p-norm Regression [PDF]
Deeksha Adil, Rasmus Kyng, Richard Peng, Sushant Sachdeva
SODA 2019
Parameterized algorithms for stable matching with ties and incomplete lists [PDF]
Deeksha Adil, Sushmita Gupta, Sanjukta Roy, Saket Saurabh, Meirav Zehavi
Theoretical Computer Science 2018
Optimal Methods for Higher-Order Smooth Monotone Variational Inequalities [PDF]
Deeksha Adil, Arun Jambulapati, Brian Bullins, Sushant Sachdeva
2022