Technical Program
MLSP-L5: Metric and Embedding Learning |
Session Type: Lecture |
Time: Wednesday, March 8, 16:00 - 18:00 |
Location: Grand Salon 3 |
Session Chair: Waheed U. Bajwa, Rutgers University, USA |
MLSP-L5.1: NOISY OBJECTIVE FUNCTIONS BASED ON THE F-DIVERGENCE |
Markus Nussbaum-Thom; International Business Machine |
Ralf Schlüter; RWTH Aachen University |
Vaibhava Goel; International Business Machine |
Hermann Ney; RWTH Aachen University |
MLSP-L5.2: EMBEDDED CLUSTERING VIA ROBUST ORTHOGONAL LEAST SQUARE DISCRIMINANT ANALYSIS |
Rui Zhang; Northwestern Polytechnical University |
Feiping Nie; Northwestern Polytechnical University |
Xuelong Li; Northwestern Polytechnical University |
MLSP-L5.3: A GEOMETRIC LEARNING APPROACH ON THE SPACE OF COMPLEX COVARIANCE MATRICES |
Hatem Hajri; IMS Bordeaux |
Salem Said; IMS Bordeaux |
Lionel Bombrun; IMS Bordeaux |
Yannick Berthoumieu; IMS Bordeaux |
MLSP-L5.4: DENSITY RIDGE MANIFOLD TRAVERSAL |
Jonas Nordhaug Myhre; Uit - The arctic university of Norway |
Michael Kampffmeyer; Uit - The arctic university of Norway |
Robert Jenssen; Uit - The arctic university of Norway |
MLSP-L5.5: POWER-LAW STOCHASTIC NEIGHBOR EMBEDDING |
Huan-Hsin Tseng; University of Michigan Health System |
Issam El Naqa; University of Michigan Health System |
Jen-Tzung Chien; National Chiao Tung University |
MLSP-L5.6: LARGEST CENTER-SPECIFIC MARGIN FOR DIMENSION REDUCTION |
Jian'an Zhang; Northwestern Polytechnical University |
Yuan Yuan; Northwestern Polytechnical University |
Feiping Nie; Northwestern Polytechnical University |
Qi Wang; Northwestern Polytechnical University |