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cs.CC2025
The communication complexity of distributed estimation
Parikshit Gopalan, Raghu Meka, Prasad Raghavendra +2
We study an extension of the standard two-party communication model in which Alice and Bob hold probability distributions and over domains and , respectively. Their…
cs.LG2025
Sparse Linear Regression is Easy on Random Supports
Gautam Chandrasekaran, Raghu Meka, Konstantinos Stavropoulos
Sparse linear regression is one of the most basic questions in machine learning and statistics. Here, we are given as input a design matrix and meas…
cs.DS2025
Sparsifying Sums of Positive Semidefinite Matrices
Arpon Basu, Pravesh K. Kothari, Yang P. Liu +1
In this paper, we revisit spectral sparsification for sums of arbitrary positive semidefinite (PSD) matrices. Concretely, for any collection of PSD matrices $\mathcal{A} = \{A_1, A…