MLSP-37.4
ACCESS CONTROL FOR PRIVACY-PRESERVING GAUSSIAN PROCESS REGRESSION
Takayuki Nakachi, University of the Ryukyus, Japan; Yitu Wang, Nippon Telegraph and Telephone Corporation, Japan
Session:
Kernel Methods
Track:
Machine Learning for Signal Processing
Location:
Gather Area G
Presentation Time:
Wed, 11 May, 22:00 - 22:45 China Time (UTC +8)
Wed, 11 May, 14:00 - 14:45 UTC
Wed, 11 May, 14:00 - 14:45 UTC
Session Chair:
Jingdong Chen, Northwestern Polytechnical University
Session MLSP-37
MLSP-37.1: MULTIPLE KERNEL K-MEANS CLUSTERING WITH SIMULTANEOUS SPECTRAL ROTATION
Jitao Lu, Yihang Lu, Rong Wang, Feiping Nie, Xuelong Li, Northwestern Polytechnical University, China
MLSP-37.2: Multitask Gaussian Process with Hierarchical Latent Interactions
Kai Chen, Feng Yin, Shuguang Cui, The Chinese University of Hong Kong, Shenzhen, China; Twan van Laarhoven, Elena Marchiori, Radboud University, Nijmegen, Netherlands
MLSP-37.3: DISCRETE MULTI-KERNEL K-MEANS WITH DIVERSE AND OPTIMAL KERNEL LEARNING
Yihang Lu, Jitao Lu, Rong Wang, Feiping Nie, Northwestern Polytechnical University, China
MLSP-37.4: ACCESS CONTROL FOR PRIVACY-PRESERVING GAUSSIAN PROCESS REGRESSION
Takayuki Nakachi, University of the Ryukyus, Japan; Yitu Wang, Nippon Telegraph and Telephone Corporation, Japan
MLSP-37.5: SCALABLE RIDGE LEVERAGE SCORE SAMPLING FOR THE NYSTRÖM METHOD
Farah Cherfaoui, Hachem Kadri, LIS, France; Liva Ralaivola, Criteo IA lab, Paris, France, France
MLSP-37.6: On Submodular Set Cover Problems For Near-Optimal Online Kernel Basis Selection
Hrusikesha Pradhan, IIT Kanpur, India; Alec Koppel, Amazon, United States of America; Ketan Rajawat, Indian Institute of Technology Kanpur, India