Wed PM1.L4.2
Conditional Diffusion with Label Smoothing for Data Synthesis from Examples with Noisy Labels
Gentry Atkinson, Xiaomin Li, Vangelis Metsis, Texas State University, United States
Session:
Wed PM1.L4: Signal Processing and Machine Learning for Big Data Lecture
Track:
SiG-DML - Signal and Data Analytics for Machine Learning
Location:
Nautica
Presentation Time:
Wed, 6 Sep, 14:20 - 14:40 Finland Time (UTC +3)
Session Chair:
Alexander Jung, Aalto University
Presentation
Discussion
Resources
No resources available.
Session Wed PM1.L4
Wed PM1.L4.1: A WATER-FILLING ALGORITHM MAXIMIZING THE VOLUME OF SUBMATRICES ABOVE THE RANK
Claude Petit, Aline Roumy, Thomas Maugey, INRIA, France
Wed PM1.L4.2: Conditional Diffusion with Label Smoothing for Data Synthesis from Examples with Noisy Labels
Gentry Atkinson, Xiaomin Li, Vangelis Metsis, Texas State University, United States
Wed PM1.L4.3: UNCERTAINTY-INFORMED ON-DEVICE PERSONALISATION USING EARLY EXIT NETWORKS ON SENSOR SIGNALS
Terry Fawden, University of Cambridge, United Kingdom; Lorena Qendro, University of Cambridge; Nokia Bell Labs, Cambridge, United Kingdom; Cecilia Mascolo, University of Cambridge, United Kingdom
Wed PM1.L4.4: Proportion inference using deep neural networks. Applications to X-ray diffraction and hyperspectral imaging
Titouan Simonnet, Mame Diarra Fall, Bruno Galerne, Université d'Orléans, France; Francis Claret, Sylvain Grangeon, BRGM, France
Wed PM1.L4.5: MULTI-BVOC SUPER-RESOLUTION EXPLOITING COMPOUNDS INTER-CONNECTION
Antonio Giganti, Sara Mandelli, Paolo Bestagini, Marco Marcon, Stefano Tubaro, Politecnico di Milano, Italy