Praneeth Kacham

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 21

Top Topics

Previously Computed

Ridge Regression

Kernel Density Estimation

Top Venues

Publications

Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong
Optimal Communication for Classic Functions in the Coordinator Model and Beyond. CoRR (2024)
Praneeth Kacham, David P. Woodruff
Faster Algorithms for Schatten-p Low Rank Approximation. CoRR (2024)
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)
Hossein Esfandiari, Vahab Mirrokni, Praneeth Kacham, David P. Woodruff, Peilin Zhong
High-Dimensional Geometric Streaming for Nearly Low Rank Data. CoRR (2024)
Praneeth Kacham, Rasmus Pagh, Mikkel Thorup, David P. Woodruff
Pseudorandom Hashing for Space-bounded Computation with Applications in Streaming. CoRR (2023)
Praneeth Kacham, Vahab Mirrokni, Peilin Zhong
PolySketchFormer: Fast Transformers via Sketches for Polynomial Kernels. CoRR (2023)
Praneeth Kacham, Rasmus Pagh, Mikkel Thorup, David P. Woodruff
Pseudorandom Hashing for Space-bounded Computation with Applications in Streaming. FOCS (2023)
Praneeth Kacham, David P. Woodruff
Lower Bounds on Adaptive Sensing for Matrix Recovery. CoRR (2023)
Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation. ICLR (2023)
Praneeth Kacham, David P. Woodruff
Lower Bounds on Adaptive Sensing for Matrix Recovery. NeurIPS (2023)
Praneeth Kacham, David P. Woodruff
Sketching Algorithms and Lower Bounds for Ridge Regression. CoRR (2022)
Praneeth Kacham, David P. Woodruff
Sketching Algorithms and Lower Bounds for Ridge Regression. ICML (2022)
Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation. CoRR (2022)
Nadiia Chepurko, Kenneth L. Clarkson, Praneeth Kacham, David P. Woodruff
Near-Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. SODA (2022)
Praneeth Kacham, David P. Woodruff
Reduced-Rank Regression with Operator Norm Error. COLT (2021)
Nadiia Chepurko, Kenneth L. Clarkson, Praneeth Kacham, David P. Woodruff
Near-Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. CoRR (2021)
Zhili Feng, Praneeth Kacham, David P. Woodruff
Dimensionality Reduction for the Sum-of-Distances Metric. ICML (2021)
Amit Deshpande, Praneeth Kacham, Rameshwar Pratap
Robust k-means++. UAI (2020)
Praneeth Kacham, David P. Woodruff
Optimal Deterministic Coresets for Ridge Regression. AISTATS (2020)
Praneeth Kacham, David P. Woodruff
Reduced-Rank Regression with Operator Norm Error. CoRR (2020)
Zhili Feng, Praneeth Kacham, David P. Woodruff
Strong Coresets for Subspace Approximation and k-Median in Nearly Linear Time. CoRR (2019)