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Praneeth Kacham
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2020 – today
- 2024
- [c13]Praneeth Kacham, David P. Woodruff:
Faster Algorithms for Schatten-p Low Rank Approximation. APPROX/RANDOM 2024: 55:1-55:19 - [c12]Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong:
High-Dimensional Geometric Streaming for Nearly Low Rank Data. ICML 2024 - [c11]Praneeth Kacham, Vahab Mirrokni, Peilin Zhong:
PolySketchFormer: Fast Transformers via Sketching Polynomial Kernels. ICML 2024 - [c10]Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong:
Optimal Communication Bounds for Classic Functions in the Coordinator Model and Beyond. STOC 2024: 1911-1922 - [i11]Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong:
Optimal Communication for Classic Functions in the Coordinator Model and Beyond. CoRR abs/2403.20307 (2024) - [i10]Hossein Esfandiari, Vahab Mirrokni, Praneeth Kacham, David P. Woodruff, Peilin Zhong:
High-Dimensional Geometric Streaming for Nearly Low Rank Data. CoRR abs/2406.02910 (2024) - [i9]Praneeth Kacham, David P. Woodruff:
Faster Algorithms for Schatten-p Low Rank Approximation. CoRR abs/2407.11959 (2024) - 2023
- [c9]Praneeth Kacham, Rasmus Pagh, Mikkel Thorup, David P. Woodruff:
Pseudorandom Hashing for Space-bounded Computation with Applications in Streaming. FOCS 2023: 1515-1550 - [c8]Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou:
Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation. ICLR 2023 - [c7]Praneeth Kacham, David P. Woodruff:
Lower Bounds on Adaptive Sensing for Matrix Recovery. NeurIPS 2023 - [i8]Praneeth Kacham, Rasmus Pagh, Mikkel Thorup, David P. Woodruff:
Pseudorandom Hashing for Space-bounded Computation with Applications in Streaming. CoRR abs/2304.06853 (2023) - [i7]Praneeth Kacham, Vahab Mirrokni, Peilin Zhong:
PolySketchFormer: Fast Transformers via Sketches for Polynomial Kernels. CoRR abs/2310.01655 (2023) - [i6]Praneeth Kacham, David P. Woodruff:
Lower Bounds on Adaptive Sensing for Matrix Recovery. CoRR abs/2311.17281 (2023) - 2022
- [c6]Praneeth Kacham, David P. Woodruff:
Sketching Algorithms and Lower Bounds for Ridge Regression. ICML 2022: 10539-10556 - [c5]Nadiia Chepurko, Kenneth L. Clarkson, Praneeth Kacham, David P. Woodruff:
Near-Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. SODA 2022: 3043-3068 - [i5]Praneeth Kacham, David P. Woodruff:
Sketching Algorithms and Lower Bounds for Ridge Regression. CoRR abs/2204.06653 (2022) - [i4]Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou:
Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation. CoRR abs/2212.00642 (2022) - 2021
- [c4]Praneeth Kacham, David P. Woodruff:
Reduced-Rank Regression with Operator Norm Error. COLT 2021: 2679-2716 - [c3]Zhili Feng, Praneeth Kacham, David P. Woodruff:
Dimensionality Reduction for the Sum-of-Distances Metric. ICML 2021: 3220-3229 - [i3]Nadiia Chepurko, Kenneth L. Clarkson, Praneeth Kacham, David P. Woodruff:
Near-Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. CoRR abs/2107.08090 (2021) - 2020
- [c2]Praneeth Kacham, David P. Woodruff:
Optimal Deterministic Coresets for Ridge Regression. AISTATS 2020: 4141-4150 - [c1]Amit Deshpande, Praneeth Kacham, Rameshwar Pratap:
Robust k-means++. UAI 2020: 799-808 - [i2]Praneeth Kacham, David P. Woodruff:
Reduced-Rank Regression with Operator Norm Error. CoRR abs/2011.04564 (2020)
2010 – 2019
- 2019
- [i1]Zhili Feng, Praneeth Kacham, David P. Woodruff:
Strong Coresets for Subspace Approximation and k-Median in Nearly Linear Time. CoRR abs/1912.12003 (2019)
Coauthor Index
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