IEEE International Workshop on
Machine Learning for Signal Processing (MLSP) 2025
August 31-September 3, Istanbul/Turkey
Signal Processing in the age of
Large Language Models
IEEE

TECHNICAL PROGRAM

Tentative Program Overview
Note that the program below is tentative, and is subject to change. It can however give you a general idea for the time being. We will try to release the detailed program before August. 
 
 
 
 All papers will do a poster presentation (regular track, special session track, data competition track, ICASSP 2025 papers, SPS papers). 
 
We have selected a small number of papers for oral presentations. Here are the selected papers: 
 
Oral Session 1 papers: Signal Decomposition and Estimation
- (regular track) Continuous-Time Signal Decomposition: An Implicit Neural Generalization of PCA and ICA
- (regular track) Learning Rate Should Scale Inversely with High-Order Data Moments in High-Dimensional Online Independent Component Analysis
- (regular track) LANM: Learned Atomic Norm Minimization for Superfast Gridless Spectral Compressed Sensing
- (regular track) prNet: Efficient and Robust Phase Retrieval via Stochastic Refinement Coordinate Ascent Neural Kalman-MLE for State Estimation
- (regular track) Coordinate Ascent Neural Kalman-MLE for State Estimation
 
Oral Session 2 papers: Audio, Speech, and Music Processing
- (Data competition: NOCASA) Comparison of End-to-end Speech Assessment Models for the NOCASA 2025 Challenge
- (regular track) Audio Prototypical Network for Controllable Music Recommendation
- (regular track) Re-Bottleneck: Latent Re-Structuring for Neural Audio Autoencoders
- (regular track) DDL: A Dataset for Drone Detection and Localization from Multi-Channel Audio and a Deep Uncertainty-Aware Framework
- (regular track) Input Conditioned Layer Dropping in Speech Foundation Models
  
Oral Session 3 papers: Learning Algorithms and Optimization
- (Special Session: LEAP) Improving Communication-Efficiency for Decentralized Federated Clustering
- (regular track) Fast and Robust Training of Deep Learning Models with Multiplicative Adagrad
- (regular track) Information Entropy-Based Scheduling for Communication-Efficient Decentralized Learning
- (regular track) Model Recycling Framework for Multi-Source Data-Free Supervised Transfer Learning
- (regular track) Meta-Tree: Bayesian Approach to Avoid Overfitting in Decision Trees and Analysis on the Application to Boosting
 
Oral Session 4 papers: Computer Vision
- (Special Session: LVLM) Trust the Model: Compact VLMS As In-Context Judges For Image-test Data Quality
- (Special Session: Art) Solving Jigsaw Puzzles in the Wild: Human-Guided Reconstruction of Cultural Heritage Fragments
- (regular track) APA: Domain Generalization Using Frequency Based Augmentation
- (regular track) Ptychographic Image Reconstruction from Limited Data via Score-Based Diffusion Models with Physics-Guidance
- (regular track) RadioTrace: Bridging Diffusion Priors and RSS Measurements for Accurate Radio Map Estimation
 
Oral Session 5 papers: ML for Health and Neuroscience
- (Special Session: Brain Decoding) Toward a gaze-independent brain-computer interface using the code-modulated visual evoked potentials
- (regular track) Closing the Gap in Multimodal Medical Representation Alignment
- (regular track) Cycle-Consistent Diffusion Model with Vessel-Aware Attention for Endoscopic Image Translation
- (regular track) RSR-NF: Neural Field Regularization by Static Restoration Priors for Computed Dynamic Imaging 
- (regular track) Perturbation-based Multiview Graph Learning with Consensus Graph