MLSP-P4: Adversarial Attacks and Fast Algorithms |
Session Type: Poster |
Time: Tuesday, 5 May, 16:30 - 18:30 |
Location: On-Demand |
Virtual Session: View on Virtual Platform |
Session Chair: Mingyi Hong, University of Minnesota |
MLSP-P4.2: COST AWARE ADVERSARIAL LEARNING |
Shashini De Silva; Oregon State University |
Jinsub Kim; Oregon State University |
Raviv Raich; Oregon State University |
MLSP-P4.3: ON DIVERGENCE APPROXIMATIONS FOR UNSUPERVISED TRAINING OF DEEP DENOISERS BASED ON STEIN’S UNBIASED RISK ESTIMATOR |
Shakarim Soltanayev; Ulsan National Institute of Science and Technology |
Raja Giryes; Tel Aviv University |
Se Young Chun; Ulsan National Institute of Science and Technology |
Yonina Eldar; Weizmann Institute of Science |
MLSP-P4.4: VARIABLE METRIC PROXIMAL GRADIENT METHOD WITH DIAGONAL BARZILAI-BORWEIN STEPSIZE |
Youngsuk Park; Stanford university |
Sauptik Dhar; LG Sillicon Valley Lab |
Stephen Boyd; Stanford university |
Mohak Shah; LG Sillicon Valley Lab |
MLSP-P4.5: REVISIT OF ESTIMATE SEQUENCE FOR ACCELERATED GRADIENT METHOD |
Bingcong Li; University of minnesota |
Mario Coutino; Delft University of Technology |
Georgios B. Giannakis; University of minnesota |
MLSP-P4.6: A GENERALIZATION OF PRINCIPAL COMPONENT ANALYSIS |
Samuele Battaglino; University of Illinois at Chicago |
Erdem Koyuncu; University of Illinois at Chicago |
MLSP-P4.7: AN EASY-TO-IMPLEMENT FRAMEWORK OF FAST SUBSPACE CLUSTERING FOR BIG DATA SETS |
Linghang Meng; Tsinghua University |
Yuchen Jiao; Tsinghua University |
Yuantao Gu; Tsinghua University |
MLSP-P4.8: INVESTIGATING GENERALIZATION IN NEURAL NETWORKS UNDER OPTIMALLY EVOLVED TRAINING PERTURBATIONS |
Subhajit Chaudhury; University of Tokyo |
Toshihiko Yamasaki; University of Tokyo |
MLSP-P4.9: HETEROGENEOUS DOMAIN GENERALIZATION VIA DOMAIN MIXUP |
Yufei Wang; University of Electronic Science and Technology of China |
Haoliang Li; Nanyang Technological University |
Alex Chichung Kot; Nanyang Technological University |
MLSP-P4.10: PRESERVATION OF ANOMALOUS SUBGROUPS ON VARIATIONAL AUTOENCODER TRANSFORMED DATA |
Samuel C. Maina; IBM Research |
Reginald E. Bryant; IBM Research |
William Ogallo; IBM Research |
Robert-Florian Samoilescu; University Politehnica of Bucharest |
Aisha Walcott-Bryant; IBM Research |
Skyler Speakman; IBM Research |
Celia Cintas; IBM Research |
Kush R. Varshney; IBM Research |
Komminist Weldemariam; IBM Research |
MLSP-P4.11: LEARN-BY-CALIBRATING: USING CALIBRATION AS A TRAINING OBJECTIVE |
Jayaraman J. Thiagarajan; Lawrence Livermore National Labs |
Bindya Venkatesh; Arizona State University |
Deepta Rajan; IBM Research |