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

<div>Clustering accuracy of our algorithm with different <svg height="6.20645pt" id="M292" style="vertical-align:-0.2063999pt" version="1.1" viewbox="-0.0498162 -6.00005 5.67144 6.20645" width="5.67144pt" 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="M397 380C406 395 404 411 396 425S369 451 350 451C302 451 239 372 192 294H189L199 338C214 407 207 451 180 451C152 451 83 405 30 345L48 318C87 354 117 372 125 372S135 362 127 324L55 -5L61 -12C87 -5 117 3 139 5C154 87 168 162 179 207C198 250 240 310 260 332C281 355 297 366 307 366C321 366 333 360 347 346C351 342 360 342 369 348C379 355 389 366 397 380Z" id="g50-115"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="427" vert-adv-y="427"></glyph.data></g></svg> values upon Extended Yale Face Database B.</div>

Mathematical Problems in Engineering

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Figure 8

Figure 8: A Rank-Constrained Matrix Representation for Hypergraph-Based Subspace Clustering 