MLSP-41.3
On the Effectiveness of Active Learning by Uncertainty Sampling in Classification of High-Dimensional Gaussian Mixture Data
Xiaoyi Mai, French National Centre for Scientific Research (CNRS), France; Salman Avestimehr, Antonio Ortega, Mahdi Soltanolkotabi, University of Southern California, United States of America
Session:
Supervised Learning
Track:
Machine Learning for Signal Processing
Location:
Gather Area G
Presentation Time:
Thu, 12 May, 20:00 - 20:45 China Time (UTC +8)
Thu, 12 May, 12:00 - 12:45 UTC
Thu, 12 May, 12:00 - 12:45 UTC
Session Chair:
Kong Aik Lee , Institute for Infocomm Research, A*STAR
Session MLSP-41
MLSP-41.1: MISMATCHED SUPERVISED LEARNING
Xun Xian, Mingyi Hong, Jie Ding, University of Minnesota, United States of America
MLSP-41.2: SUPERVISED TRAINING OF SIAMESE SPIKING NEURAL NETWORKS WITH EARTH MOVER’S DISTANCE
Mateusz Pabian, Dominik Rzepka, Mirosław Pawlak, AGH University of Science and Technology, Poland
MLSP-41.3: On the Effectiveness of Active Learning by Uncertainty Sampling in Classification of High-Dimensional Gaussian Mixture Data
Xiaoyi Mai, French National Centre for Scientific Research (CNRS), France; Salman Avestimehr, Antonio Ortega, Mahdi Soltanolkotabi, University of Southern California, United States of America
MLSP-41.4: Neural Collapse in Deep Homogeneous Classifiers and the role of Weight Decay
Akshay Rangamani, Andrzej Banburski-Fahey, Massachusetts Institute of Technology, United States of America
MLSP-41.5: SYNTHESIS OF ADVERSARIAL SAMPLES IN TWO-STAGE CLASSIFIERS
Ismail Alkhouri, George Atia, University of Central Florida, United States of America; Alvaro Velasquez, Air Force Research Laboratory, United States of America
MLSP-41.6: Synergistic Network Learning and Label Correction for Noise-robust Image Classification
Chen Gong, University of Washington, United States of America; Kong Bin, Xin Wang, Youbing Yin, Qi Song, Keya medical, United States of America; Eric Seibel, Univerisity of Washington, United States of America