Praneeth Kacham

According to our database, Praneeth Kacham authored at least 18 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

LevAttention: Time, Space, and Streaming Efficient Algorithm for Heavy Attentions.

Ravindran Kannan, Chiranjib Bhattacharyya, Praneeth Kacham, David P. Woodruff

CoRR, 2024

Optimal Communication for Classic Functions in the Coordinator Model and Beyond.

Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong

CoRR, 2024

Optimal Communication Bounds for Classic Functions in the Coordinator Model and Beyond.

Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong

Proceedings of the 56th Annual ACM Symposium on Theory of Computing, 2024

PolySketchFormer: Fast Transformers via Sketching Polynomial Kernels.

Praneeth Kacham, Vahab Mirrokni, Peilin Zhong

Proceedings of the Forty-first International Conference on Machine Learning, 2024

High-Dimensional Geometric Streaming for Nearly Low Rank Data.

Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Faster Algorithms for Schatten-p Low Rank Approximation.

Praneeth Kacham, David P. Woodruff

Proceedings of the Approximation, 2024

2023

PolySketchFormer: Fast Transformers via Sketches for Polynomial Kernels.

Praneeth Kacham, Vahab Mirrokni, Peilin Zhong

CoRR, 2023

Lower Bounds on Adaptive Sensing for Matrix Recovery.

Praneeth Kacham, David P. Woodruff

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation.

Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Pseudorandom Hashing for Space-bounded Computation with Applications in Streaming.

Praneeth Kacham, Rasmus Pagh, Mikkel Thorup, David P. Woodruff

Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

2022

Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation.

Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou

CoRR, 2022

Near-Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time.

Nadiia Chepurko, Kenneth L. Clarkson, Praneeth Kacham, David P. Woodruff

Proceedings of the 2022 ACM-SIAM Symposium on Discrete Algorithms, 2022

Sketching Algorithms and Lower Bounds for Ridge Regression.

Praneeth Kacham, David P. Woodruff

Proceedings of the International Conference on Machine Learning, 2022

2021

Dimensionality Reduction for the Sum-of-Distances Metric.

Zhili Feng, Praneeth Kacham, David P. Woodruff

Proceedings of the 38th International Conference on Machine Learning, 2021

Reduced-Rank Regression with Operator Norm Error.

Praneeth Kacham, David P. Woodruff

Proceedings of the Conference on Learning Theory, 2021

2020

Robust k-means++.

Amit Deshpande, Praneeth Kacham, Rameshwar Pratap

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Optimal Deterministic Coresets for Ridge Regression.

Praneeth Kacham, David P. Woodruff

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Strong Coresets for Subspace Approximation and k-Median in Nearly Linear Time.

Zhili Feng, Praneeth Kacham, David P. Woodruff

CoRR, 2019