MLSP-P9.2
LEARNING FROM EASY TO HARD: MULTI-TASK LEARNING WITH DATA SCHEDULING
Zeyu Liu, Heyan Chai, Qing Liao, Harbin Institute of Technology (Shenzhen), China
Session:
MLSP-P9: Deep Learning Techniques III Poster
Track:
Machine Learning for Signal Processing
Location:
Poster Zone 3A
Poster Board PZ-3A.2
Poster Board PZ-3A.2
Presentation Time:
Wed, 17 Apr, 08:20 - 10:20 (UTC +9)
Session Chair:
Lu Gan, Brunel University
Session MLSP-P9
MLSP-P9.1: Multi-source DOA estimation with statistical coverage guarantees
Ishan D Khurjekar, Peter Gerstoft, University of California San Diego, United States of America
MLSP-P9.2: LEARNING FROM EASY TO HARD: MULTI-TASK LEARNING WITH DATA SCHEDULING
Zeyu Liu, Heyan Chai, Qing Liao, Harbin Institute of Technology (Shenzhen), China
MLSP-P9.3: Encoding Seasonal Climate Predictions with Modular Neural Network
Smit Marvaniya, Linkedin, India; Jitendra Singh, Nicolas Galichet, Fred Ochieng Otieno, Geeth De Mel, Kommy Weldemariam, IBM, India
MLSP-P9.4: EXPLORATION OF VISUAL PROMPT IN GROUNDED PRE-TRAINED OPEN-SET DETECTION
Qibo Chen, Weizhong Jin, Shuchang Li, Mengdi Liu, Li Yu, Jian Jiang, Xiaozheng Wang, China Mobile(Zhejiang) Research & Innovation Institute, China
MLSP-P9.5: ADAPTIVE QUANTIZATION WITH MIXED-PRECISION BASED ON LOW-COST PROXY
Junzhe Chen, Qiao Yang, Senmao Tian, Shunli Zhang, Beijing Jiaotong university, China
MLSP-P9.6: EXPLORING THE UTILITY OF CLIP PRIORS FOR VISUAL RELATIONSHIP PREDICTION
Rakshith Subramanyam, Arizona State University, United States of America; Jayram T. S., Rushil Anirudh, Jayaraman J. Thiagarajan, Lawrence Livermore National Laboratory, United States of America
MLSP-P9.7: KNOWLEDGE-BASED CONVOLUTIONAL NEURAL NETWORK FOR THE SIMULATION AND PREDICTION OF TWO-PHASE DARCY FLOWS
Zakaria Elabid, Sorbonne university Abu Dhabi, United Arab Emirates; Daniel Busby, TotalEnergies, France; Abdenour Hadid, Sorbonne university Abu Dhabi, United Arab Emirates
MLSP-P9.8: ASFORMER: LEARNING FROM ADJACENT SCALE
Hanpeng Jiang, Zhennan Chen, Wei Ding, Fan Lin, Xiamen University, China
MLSP-P9.9: ACCURATE GIGAPIXEL CROWD COUNTING BY ITERATIVE ZOOMING AND REFINEMENT
Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis, Aarhus University, Denmark
MLSP-P9.10: TEMPORAL INCONSISTENCY-BASED ACTIVE LEARNING
Tianjiao Wan, National University of Defense technology, China; Yutao Dou, Hunan University, China; Kele Xu, Zijian Gao, Bo Ding, Dawei Feng, Huaimin Wang, National University of Defense technology, China
MLSP-P9.11: FREQ2TIME: WEAKLY SUPERVISED LEARNING OF CAMERA-BASED RPPG FROM HEART RATE
Jeremy Speth, University of Notre Dame, United States of America; Korosh Vatanparvar, Li Zhu, Jilong Kuang, Alex Gao, Samsung Research America, United States of America
MLSP-P9.12: GRAPHON POOLING FOR REDUCING DIMENSIONALITY OF SIGNALS AND CONVOLUTIONAL OPERATORS ON GRAPHS
Alejandro Parada-Mayorga, alejandro Ribeiro, zhiyang wang, University of Pennsylvania, United States of America
MLSP-P9.13: CONVOLUTIONAL FILTERS AND NEURAL NETWORKS WITH NONCOMMUTATIVE ALGEBRAS
Alejandro Parada-Mayorga, Alejandro Ribeiro, University of Pennsylvania, United States of America; Landon Butler, University of California Berkeley, United States of America
Contacts