Tail Bounds for <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-4.1996pt" id="M1" height="15.599pt" version="1.1" viewBox="-0.0657574 -11.3994 13.895 15.599" width="13.895pt"><g transform="matrix(.017,0,0,-0.017,0,0)"><path id="g113-127" d="M442 569C442 628 407 660 362 660C328 660 292 648 255 616C200 568 165 508 123 334L106 264C80 242 52 222 23 202L30 176C54 191 76 205 100 222L87 166C73 103 79 43 95 19C108 0 139 -12 169 -12C242 -12 318 38 369 106L354 129C322 93 260 49 215 49C173 49 147 81 170 187L189 274C293 344 442 452 442 569ZM380 565C380 478 267 377 196 322L216 406C254 556 282 623 332 623C364 623 380 596 380 565Z"/></g><g transform="matrix(.012,0,0,-0.012,7.207,4.134)"><path id="g50-50" d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z"/></g></svg> Norm of Gaussian Random Matrices with Applications

<div>Geometric explanation of lasso and ridge regression.</div>

Journal of Mathematics

fig1

Figure 1

Figure 1: Tail Bounds for <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-4.1996pt" id="M1" height="15.599pt" version="1.1" viewBox="-0.0657574 -11.3994 13.895 15.599" width="13.895pt"><g transform="matrix(.017,0,0,-0.017,0,0)"><path id="g113-127" d="M442 569C442 628 407 660 362 660C328 660 292 648 255 616C200 568 165 508 123 334L106 264C80 242 52 222 23 202L30 176C54 191 76 205 100 222L87 166C73 103 79 43 95 19C108 0 139 -12 169 -12C242 -12 318 38 369 106L354 129C322 93 260 49 215 49C173 49 147 81 170 187L189 274C293 344 442 452 442 569ZM380 565C380 478 267 377 196 322L216 406C254 556 282 623 332 623C364 623 380 596 380 565Z"/></g><g transform="matrix(.012,0,0,-0.012,7.207,4.134)"><path id="g50-50" d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z"/></g></svg> Norm of Gaussian Random Matrices with Applications 

Journal of Mathematics

Tail Bounds for Norm of Gaussian Random Matrices with Applications

Figure 1