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        <title>𝐶𝑎𝑟𝑎𝑚𝑖𝑧𝑎𝑟𝑢'𝑠 𝐵𝑙𝑜𝑔 feed:2024:04:25</title>
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            <title>𝐶𝑎𝑟𝑎𝑚𝑖𝑧𝑎𝑟𝑢'𝑠 𝐵𝑙𝑜𝑔</title>
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            <title>Is the Future of Linear Algebra.. Random?</title>
            <link>https://blog.caramizaru.xyz/doku.php/feed:2024:04:25:is_the_future_of_linear_algebra.._random</link>
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&lt;h1 class=&quot;sectionedit3&quot; id=&quot;is_the_future_of_linear_algebra_random&quot;&gt;Is the Future of Linear Algebra.. Random?&lt;/h1&gt;
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&lt;p&gt;
Source [1] is the paper that caused me to create this video. [3], [7] and [8] provided a broad and technical view of randomization as a strategy for NLA. [9] and [12] informed me about the history of NLA. [2], [4], [5], [6], [10], [11], [13] and [14] provide concrete algorithms demonstrating the utility of randomization.
&lt;/p&gt;
&lt;hr /&gt;

&lt;p&gt;
[1] Murray et al. Randomized Numerical Linear Algebra. arXiv:2302.11474v2 2023
&lt;/p&gt;

&lt;p&gt;
[2] Melnichenko et al. CholeskyQR with Randomization and Pivoting for Tall Matrices (CQRRPT). arXiv:2311.08316v1 2023 
&lt;/p&gt;

&lt;p&gt;
[3] P. Drineas and M. Mahoney. RandNLA: Randomized Numerical Linear Algebra. Communications of the ACM. 2016
&lt;/p&gt;

&lt;p&gt;
[4] N. Halko, P. Martinsson, and J. Tropp. Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions. arXiv:0909.4061v2 2010
&lt;/p&gt;

&lt;p&gt;
[5] Tropp et al. Fixed Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data. NeurIPS Proceedings. 2017
&lt;/p&gt;

&lt;p&gt;
[6] X. Meng, M. Saunders, and M. Mahoney. LSRN: A Parallel Iterative Solver for Strongly Over- Or Underdetermined Systems. SIAM 2014
&lt;/p&gt;

&lt;p&gt;
[7] D. Woodruff. Sketching as a Tool for Numerical Linear Algebra. IBM Research Almaden. 2015
&lt;/p&gt;

&lt;p&gt;
[8] M. Mahoney. Randomized Algorithms for Matrices and Data.  arXiv:1104.5557v3. 2011
&lt;/p&gt;

&lt;p&gt;
[9] G. Golub and H van der Vorst. Eigenvalue Computation in the 20th Century. Journal of Computational and Applied Mathematics. 2000
&lt;/p&gt;

&lt;p&gt;
[10] J. Duersch and M. Gu. Randomized QR with Column Pivoting.  arXiv:1509.06820v2 2017
&lt;/p&gt;

&lt;p&gt;
[11] Erichson et al. Randomized Matrix Decompositions Using R. Journal of Statistical Software. 2019
&lt;/p&gt;

&lt;p&gt;
[12] J. Gentle et al. Software for Numerical Linear Algebra. Springer. 2017
&lt;/p&gt;

&lt;p&gt;
[13] H. Avron, P. Maymounkov, and S. Toledo. Blendenpik: Supercharging LAPACK&amp;#039;s Least-Squares Solver. Siam. 2010
&lt;/p&gt;

&lt;p&gt;
[14] M. Mahoney and P. Drineas. CUR Matrix Decompositions for Improved Data Analysis. Proceedings of the National Academy of Sciences. 2009
&lt;/p&gt;
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            <author>anonymous@undisclosed.example.com (Anonymous)</author>
        <category>math</category>
        <category>linear-algebra</category>
        <category>random</category>
        <category>numerics</category>
            <pubDate>Thu, 25 Apr 2024 14:21:40 +0000</pubDate>
        </item>
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            <title>Jemin Hwangbo (KAIST): Large-scale policy training for robots</title>
            <link>https://blog.caramizaru.xyz/doku.php/feed:2024:04:25:jemin_hwangbo_kaist_large-scale_policy_training_for_robots</link>
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&lt;h1 class=&quot;sectionedit3&quot; id=&quot;jemin_hwangbo_kaistlarge-scale_policy_training_for_robots&quot;&gt;Jemin Hwangbo (KAIST): Large-scale policy training for robots&lt;/h1&gt;
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            <author>anonymous@undisclosed.example.com (Anonymous)</author>
        <category>robotics</category>
        <category>jemin-hwangbo</category>
        <category>kaist</category>
        <category>rl</category>
            <pubDate>Fri, 26 Apr 2024 09:41:33 +0000</pubDate>
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