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Deeksha Adil
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Journal Articles
- 2018
- [j1]Deeksha Adil, Sushmita Gupta, Sanjukta Roy, Saket Saurabh, Meirav Zehavi:
Parameterized algorithms for stable matching with ties and incomplete lists. Theor. Comput. Sci. 723: 1-10 (2018)
Conference and Workshop Papers
- 2021
- [c5]Deeksha Adil, Brian Bullins, Rasmus Kyng, Sushant Sachdeva:
Almost-Linear-Time Weighted 𝓁p-Norm Solvers in Slightly Dense Graphs via Sparsification. ICALP 2021: 9:1-9:15 - [c4]Deeksha Adil, Brian Bullins, Sushant Sachdeva:
Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization. NeurIPS 2021: 19122-19133 - 2020
- [c3]Deeksha Adil, Sushant Sachdeva:
Faster p-norm minimizing flows, via smoothed q-norm problems. SODA 2020: 892-910 - 2019
- [c2]Deeksha Adil, Richard Peng, Sushant Sachdeva:
Fast, Provably convergent IRLS Algorithm for p-norm Linear Regression. NeurIPS 2019: 14166-14177 - [c1]Deeksha Adil, Rasmus Kyng, Richard Peng, Sushant Sachdeva:
Iterative Refinement for ℓp-norm Regression. SODA 2019: 1405-1424
Informal and Other Publications
- 2024
- [i9]Deeksha Adil, Thatchaphol Saranurak:
Decremental (1+ε)-Approximate Maximum Eigenvector: Dynamic Power Method. CoRR abs/2402.17929 (2024) - [i8]Deeksha Adil, Shunhua Jiang, Rasmus Kyng:
Acceleration Meets Inverse Maintenance: Faster ℓ∞-Regression. CoRR abs/2409.20030 (2024) - 2022
- [i7]Deeksha Adil, Brian Bullins, Arun Jambulapati, Sushant Sachdeva:
Optimal Methods for Higher-Order Smooth Monotone Variational Inequalities. CoRR abs/2205.06167 (2022) - [i6]Deeksha Adil, Rasmus Kyng, Richard Peng, Sushant Sachdeva:
Fast Algorithms for 𝓁p-Regression. CoRR abs/2211.03963 (2022) - 2021
- [i5]Deeksha Adil, Brian Bullins, Rasmus Kyng, Sushant Sachdeva:
Almost-linear-time Weighted 𝓁p-norm Solvers in Slightly Dense Graphs via Sparsification. CoRR abs/2102.06977 (2021) - [i4]Deeksha Adil, Brian Bullins, Sushant Sachdeva:
Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization. CoRR abs/2107.02432 (2021) - 2019
- [i3]Deeksha Adil, Rasmus Kyng, Richard Peng, Sushant Sachdeva:
Iterative Refinement for 𝓁p-norm Regression. CoRR abs/1901.06764 (2019) - [i2]Deeksha Adil, Richard Peng, Sushant Sachdeva:
Fast, Provably convergent IRLS Algorithm for p-norm Linear Regression. CoRR abs/1907.07167 (2019) - [i1]Deeksha Adil, Sushant Sachdeva:
Faster p-norm minimizing flows, via smoothed q-norm problems. CoRR abs/1910.10571 (2019)
Coauthor Index
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