MLSP-36.5
OVER-PARAMETERIZED NETWORK SOLVES PHASE RETRIEVAL EFFECTIVELY
Ji Li, Chao Wang, National University of Singapore, Singapore
Session:
Applications of Machine Learning
Track:
Machine Learning for Signal Processing
Location:
Gather Area F
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:
Oldrich Plchot, Brno University of Technology
Session MLSP-36
MLSP-36.1: AN EFFICIENT DP-SGD MECHANISM FOR LARGE SCALE NLU MODELS
Christophe Dupuy, Radhika Arava, Rahul Gupta, Amazon Alexa AI, United States of America; Anna Rumshisky, Amazon Alexa AI; University of Massachusetts, Lowell, United States of America
MLSP-36.2: MAKD:MULTIPLE AUXILIARY KNOWLEDGE DISTILLATION
Zehan Chen, Xuan Jin, Yuan He, Hui Xue, Alibaba Group, China
MLSP-36.3: Feature Imitating Networks
Sari Saba-Sadiya, Mohammad Ghassemi, Michigan State University, United States of America; Tuka Alhanai, New York University Abu Dhabi, United Arab Emirates
MLSP-36.4: EXPONENTIAL HYPERBOLIC COSINE ROBUST ADAPTIVE FILTERS FOR AUDIO SIGNAL PROCESSING
Krishna Kumar, Rajlaxmi Pandey, Sankha Bhattacharjee, Nithin George, Indian Institute of Technology Gandhinagar, India
MLSP-36.5: OVER-PARAMETERIZED NETWORK SOLVES PHASE RETRIEVAL EFFECTIVELY
Ji Li, Chao Wang, National University of Singapore, Singapore
MLSP-36.6: Deep Spatio-Temporal Wind Power Forecasting
Jiangyuan Li, Mohammadreza Armandpour, Texas A&M University, United States of America