Randomized algorithms for estimating the trace of an implicit symmetric positive semi-definite matrix von Avron, Haim, Toledo, Sivan

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Randomized Signal Processing with Continuous Frames von Levie, Ron, Avron, Haim

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Randomized continuous frames in time-frequency analysis von Levie, Ron, Avron, Haim

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Tensor-tensor algebra for optimal representation and compression of multiway data von Kilmer, Misha E., Horesh, Lior, Avron, Haim, Newman, Elizabeth

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Dimensionality reduction of longitudinal ’omics data using modern tensor factorizations von Mor, Uria, Cohen, Yotam, Valdés-Mas, Rafael, Kviatcovsky, Denise, Elinav, Eran, Avron, Haim

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Solving trust region subproblems using Riemannian optimization von Mor, Uria, Shustin, Boris, Avron, Haim

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Experimental Design for Overparameterized Learning With Application to Single Shot Deep Active Learning von Shoham, Neta, Avron, Haim

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Stable tensor neural networks for efficient deep learning von Newman, Elizabeth, Horesh, Lior, Avron, Haim, Kilmer, Misha E

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Riemannian optimization with a preconditioning scheme on the generalized Stiefel manifold von Shustin, Boris, Avron, Haim

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Faster Subset Selection for Matrices and Applications von Avron, Haim, Boutsidis, Christos

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Semi-Infinite Linear Regression and Its Applications von Shustin, Paz Fink, Avron, Haim

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Faster Kernel Ridge Regression Using Sketching and Preconditioning von Avron, Haim, Clarkson, Kenneth L., Woodruff, David P.

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Revisiting Asynchronous Linear Solvers: Provable Convergence Rate through Randomization von Avron, Haim, Druinsky, Alex, Gupta, Anshul

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Sketching for Principal Component Regression von Mor-Yosef, Liron, Avron, Haim

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Blendenpik: Supercharging LAPACK's Least-Squares Solver von Avron, Haim, Maymounkov, Petar, Toledo, Sivan

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High-Performance Kernel Machines With Implicit Distributed Optimization and Randomization von Avron, Haim, Sindhwani, Vikas

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Low‐rank updates of matrix square roots von Shmueli, Shany, Drineas, Petros, Avron, Haim

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Quasi Monte Carlo time-frequency analysis von Levie, Ron, Avron, Haim, Kutyniok, Gitta

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Approximating Spectral Sums of Large-Scale Matrices using Stochastic Chebyshev Approximations von Han, Insu, Malioutov, Dmitry, Avron, Haim, Shin, Jinwoo

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Spectral condition‐number estimation of large sparse matrices von Avron, Haim, Druinsky, Alex, Toledo, Sivan

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