| 2025 | ICLR | LevAttention: Time, Space and Streaming Efficient Algorithm for Heavy Attentions. | Ravindran Kannan, Chiranjib Bhattacharyya, Praneeth Kacham, David P. Woodruff |
| 2024 | ICML | High-Dimensional Geometric Streaming for Nearly Low Rank Data. | Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong |
| 2024 | ICML | PolySketchFormer: Fast Transformers via Sketching Polynomial Kernels. | Praneeth Kacham, Vahab Mirrokni, Peilin Zhong |
| 2024 | STOC | Optimal Communication Bounds for Classic Functions in the Coordinator Model and Beyond. | Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong |
| 2023 | FOCS | Pseudorandom Hashing for Space-bounded Computation with Applications in Streaming. | Praneeth Kacham, Rasmus Pagh, Mikkel Thorup, David P. Woodruff |
| 2023 | ICLR | Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation. | Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou |
| 2022 | ICML | Sketching Algorithms and Lower Bounds for Ridge Regression. | Praneeth Kacham, David P. Woodruff |
| 2022 | SODA | Near-Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. | Nadiia Chepurko, Kenneth L. Clarkson, Praneeth Kacham, David P. Woodruff |
| 2021 | COLT | Reduced-Rank Regression with Operator Norm Error. | Praneeth Kacham, David P. Woodruff |
| 2021 | ICML | Dimensionality Reduction for the Sum-of-Distances Metric. | Zhili Feng, Praneeth Kacham, David P. Woodruff |
| 2020 | AISTATS | Optimal Deterministic Coresets for Ridge Regression. | Praneeth Kacham, David P. Woodruff |
| 2020 | UAI | Robust k-means++. | Amit Deshpande, Praneeth Kacham, Rameshwar Pratap |