Praneeth Kacham

33 papers A* 12A 3Journal 17
YearRankTypeTitle / Venue / Authors
2025 J jnl
ATLAS: Learning to Optimally Memorize the Context at Test Time.
CoRR
Ali Behrouz, Zeman Li, Praneeth Kacham, Majid Daliri, Yuan Deng, Peilin Zhong, Meisam Razaviyayn, Vahab Mirrokni
2025 A* conf
LevAttention: Time, Space and Streaming Efficient Algorithm for Heavy Attentions.
ICLR
Ravindran Kannan, Chiranjib Bhattacharyya, Praneeth Kacham, David P. Woodruff
2025 J jnl
PolarQuant: Quantizing KV Caches with Polar Transformation.
CoRR
Insu Han, Praneeth Kacham, Amin Karbasi, Vahab Mirrokni, Amir Zandieh
2025 J jnl
TNT: Improving Chunkwise Training for Test-Time Memorization.
CoRR
Zeman Li, Ali Behrouz, Yuan Deng, Peilin Zhong, Praneeth Kacham, Mahdi Karami, Meisam Razaviyayn, Vahab Mirrokni
2025 J jnl
Trellis: Learning to Compress Key-Value Memory in Attention Models.
CoRR
Mahdi Karami, Ali Behrouz, Praneeth Kacham, Vahab Mirrokni
2024 A* conf
Approximating the Top Eigenvector in Random Order Streams.
NeurIPS
Praneeth Kacham, David P. Woodruff
2024 J jnl
Approximating the Top Eigenvector in Random Order Streams.
CoRR
Praneeth Kacham, David P. Woodruff
2024 A conf
Faster Algorithms for Schatten-p Low Rank Approximation.
APPROX/RANDOM
Praneeth Kacham, David P. Woodruff
2024 J jnl
Faster Algorithms for Schatten-p Low Rank Approximation.
CoRR
Praneeth Kacham, David P. Woodruff
2024 A* conf
High-Dimensional Geometric Streaming for Nearly Low Rank Data.
ICML
Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong
2024 J jnl
High-Dimensional Geometric Streaming for Nearly Low Rank Data.
CoRR
Hossein Esfandiari, Vahab Mirrokni, Praneeth Kacham, David P. Woodruff, Peilin Zhong
2024 J jnl
LevAttention: Time, Space, and Streaming Efficient Algorithm for Heavy Attentions.
CoRR
Ravindran Kannan, Chiranjib Bhattacharyya, Praneeth Kacham, David P. Woodruff
2024 — —
On Efficient Sketching Algorithms
Praneeth Kacham
2024 A* conf
Optimal Communication Bounds for Classic Functions in the Coordinator Model and Beyond.
STOC
Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong
2024 J jnl
Optimal Communication for Classic Functions in the Coordinator Model and Beyond.
CoRR
Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni, David P. Woodruff, Peilin Zhong
2024 A* conf
PolySketchFormer: Fast Transformers via Sketching Polynomial Kernels.
ICML
Praneeth Kacham, Vahab Mirrokni, Peilin Zhong
2023 A* conf
Lower Bounds on Adaptive Sensing for Matrix Recovery.
NeurIPS
Praneeth Kacham, David P. Woodruff
2023 J jnl
Lower Bounds on Adaptive Sensing for Matrix Recovery.
CoRR
Praneeth Kacham, David P. Woodruff
2023 J jnl
PolySketchFormer: Fast Transformers via Sketches for Polynomial Kernels.
CoRR
Praneeth Kacham, Vahab Mirrokni, Peilin Zhong
2023 A* conf
Pseudorandom Hashing for Space-bounded Computation with Applications in Streaming.
FOCS
Praneeth Kacham, Rasmus Pagh, Mikkel Thorup, David P. Woodruff
2023 J jnl
Pseudorandom Hashing for Space-bounded Computation with Applications in Streaming.
CoRR
Praneeth Kacham, Rasmus Pagh, Mikkel Thorup, David P. Woodruff
2023 A* conf
Subquadratic Algorithms for Kernel Matrices via Kernel Density Estimation.
ICLR
Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
2022 A* conf
Near-Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time.
SODA
Nadiia Chepurko, Kenneth L. Clarkson, Praneeth Kacham, David P. Woodruff
2022 A* conf
Sketching Algorithms and Lower Bounds for Ridge Regression.
ICML
Praneeth Kacham, David P. Woodruff
2022 J jnl
Sketching Algorithms and Lower Bounds for Ridge Regression.
CoRR
Praneeth Kacham, David P. Woodruff
2022 J jnl
Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation.
CoRR
Ainesh Bakshi, Piotr Indyk, Praneeth Kacham, Sandeep Silwal, Samson Zhou
2021 A* conf
Dimensionality Reduction for the Sum-of-Distances Metric.
ICML
Zhili Feng, Praneeth Kacham, David P. Woodruff
2021 J jnl
Near-Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time.
CoRR
Nadiia Chepurko, Kenneth L. Clarkson, Praneeth Kacham, David P. Woodruff
2021 A* conf
Reduced-Rank Regression with Operator Norm Error.
COLT
Praneeth Kacham, David P. Woodruff
2020 A conf
Optimal Deterministic Coresets for Ridge Regression.
AISTATS
Praneeth Kacham, David P. Woodruff
2020 J jnl
Reduced-Rank Regression with Operator Norm Error.
CoRR
Praneeth Kacham, David P. Woodruff
2020 A conf
Robust k-means++.
UAI
Amit Deshpande, Praneeth Kacham, Rameshwar Pratap
2019 J jnl
Strong Coresets for Subspace Approximation and k-Median in Nearly Linear Time.
CoRR
Zhili Feng, Praneeth Kacham, David P. Woodruff