A Rank-Constrained Matrix Representation for Hypergraph-Based Subspace Clustering

<div>Subspace clustering accuracy with different <svg height="9.4034pt" id="M296" style="vertical-align:-3.40335pt" version="1.1" viewbox="-0.0498162 -6.00005 11.59 9.4034" width="11.59pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M525 275C525 381 464 451 380 451C338 451 289 439 241 405C158 347 127 277 106 152C51 -168 37 -216 24 -242L28 -257C42 -256 92 -247 117 -222C126 -213 134 -193 150 -69L166 32C184 10 211 -12 245 -12C276 -12 332 8 384 46C458 100 525 176 525 275ZM436 260C436 131 366 41 267 41C246 41 208 51 175 82C181 125 187 162 195 200C220 322 257 400 328 400C398 400 436 338 436 260Z" id="g50-239"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="549" vert-adv-y="549"></glyph.data></g><g transform="matrix(.0091,0,0,-0.0091,6.292,3.001)"><path d="M504 89L488 119C453 85 428 69 416 69C408 69 405 75 412 102L462 304C492 438 460 451 436 451S388 441 356 423C311 397 229 336 170 256H168L189 340C208 418 200 451 177 451C144 451 82 413 24 352L40 322C65 345 98 369 108 369C114 369 119 363 112 335L28 -3L36 -12C54 -3 83 4 112 10C125 73 138 122 153 174C205 258 328 382 376 382C395 382 399 369 384 305L330 93C312 25 323 -12 351 -12C378 -12 439 21 504 89Z" id="g50-111"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="512" vert-adv-y="512"></glyph.data></g></svg> values upon Extended Yale Face Database B.</div>

Mathematical Problems in Engineering

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Figure 9

Figure 9: A Rank-Constrained Matrix Representation for Hypergraph-Based Subspace Clustering 