Program

Monday, 2nd July Summer School
09:30 – 10:00	Registration / Coffee
10:00 – 12:30	Tutorial 1
	Tensor Factorizations, Data Fusion & Applications Evrim Acar
12:30 – 13:30	Lunch
13:30 – 16:00	Tutorial 2
	Bayesian Inference and Deep Learning Richard Turner
16:10 – 17:00	Tutorial 3
	Evaluation of Musical Audio Source Separation Russell Mason, Ryan Chungeun Kim, Dominic Ward
17:30	Welcome Reception
Tuesday, 3rd July Conference Day 1
09:00 – 09:10	Welcome
09:10 – 10:10	Keynote
	Computational Analysis of Sound Events in Realistic Multisource Environments Tuomas Virtanen
10:10 – 10:50	Special Session: Structured Tensor Decompositions and Applications
	Robust Multilinear Tensor Decomposition with Rank Estimation Xu Han, Laurent Albera, Kachenoura Amar, Huazhong Shu, Lotfi Senhadji
	Multichannel Audio Modeling with Elliptically Stable Tensor Decomposition Mathieu Fontaine, Fabian-Robert Stöter, Antoine Liutkus, Umut Simsekli, Roland Badeau, Romain Serizel
10:50 – 11:20	Tea / Coffee
11:20 – 12:40	Special Session: Structured Tensor Decompositions and Applications (Cont.)
	Sum Conditioned Poisson Factorization Gokhan Capan, Semih Akbayrak, Taha Ceritli, Ali Taylan Cemgil
	Curve Registered Coupled Low Rank Factorization Jérémy Cohen, Rodrigo Cabral-Farias, Bertrand Rivet
	Source Analysis using Block Term Decomposition in Atrial Fibrillation Pedro Marinho, Vicente Zarzoso
	Some Issues in Computing the CP Decomposition of NonNegative Tensors Mohamad Jouni, Mauro Dalla Mura, Pierre Comon
12:40 – 12:55	Poster Spotlights
12:55 – 13:50	Lunch
13:50 – 15:10	Posters and Demos
	Nonnegative PARAFAC2: A Flexible Coupling Approach Jérémy Cohen, Rasmus Bro
	Applications of Polynomial Common Factor Computation in Signal Processing Ivan Markovsky, Antonio Fazzi, Nicola Guglielmi
	Joint Nonnegative Matrix Factorization for Underdetermined Blind Source Separation in Nonlinear Mixtures Ivica Kopriva
	On the Number of Signals in Multivariate Time Series Markus Matilainen, Klaus Nordhausen, Joni Virta
	A Generative Model for Natural Sounds Based on Latent Force Modelling William Wilkinson, Joshua Reiss, Dan Stowell
	Multi-Resolution Fully Convolutional Neural Networks for Monaural Audio Source Separation Emad M. Grais, Hagen Wierstorf, Dominic Ward, Mark D. Plumbley
	Application of Independent Component Analysis to Tumor Transcriptomes Reveals Specific And Reproducible Immune-related Signals Urszula Czerwinska, Laura Cantini, Ulykbek Kairov, Emmanuel Barillot, Andrei Zinovyev
	Probit Latent Variables Estimation for a Gaussian Process Classifier. Application to the Detection of High-Voltage Spindles Rémi Souriau, Vincent Vigneron, Jean Lerbet, Hsin Chen
	Multichannel Audio Source Separation Exploiting NMF-based Generic Source Spectral Model in Gaussian Modeling Framework Thanh Duong, Ngoc Duong, Cong-Phuong Nguyen, Quoc Cuong Nguyen
	Orthogonality-Regularized Masked NMF with KL-Divergence for Learning on Weakly Labeled Audio Data Iwona Sobieraj, Lucas Rencker, Mark D. Plumbley
	Convergence of Jacobi-Type Algorithms for Simultaneous Approximate Diagonalization of Matrices or Tensors Konstantin Usevich, Jianze Li and Pierre Comon
15:10 – 16:10	ICA Methods
	Accelerating Likelihood Optimization for ICA on Real Signals Pierre Ablin, Jean-Francois Cardoso, Alexandre Gramfort
	Orthogonally-Constrained Extraction of Independent Non-Gaussian Component from Non-Gaussian Background without ICA Zbynek Koldovsky, Petr Tichavsky, Nobutaka Ono
	A New Link Between Joint Blind Source Separation Using Second Order Statistics and the Canonical Polyadic Decomposition Dana Lahat, Christian Jutten
16:10 – 16:30	Tea / Coffee
16:30 – 17:30	Nonlinear Mixtures
	A Blind Source Separation Method based on Output Nonlinear Correlation for Bilinear Mixtures Andréa Guerrero, Yannick Deville, Shahram Hosseini
	Using Taylor Series Expansions and Second-Order Statistics for Blind Source Separation in Post-Nonlinear Mixtures Denis Gustavo Fantinato, Leonardo Tomazeli Duarte, Yannick Deville, Christian Jutten, Romis Attux, Aline Neves
	New Classes of Blind Quantum Source Separation and Process Tomography Methods based on Spin Component Measurements along Two Directions Yannick Deville, Alain Deville
Wednesday, 4th July Conference Day 2
09:00 – 10:00	Keynote
	Comparative Spectral Decompositions for Personalized Cancer Diagnostics and Prognostics Orly Alter
10:00 – 10:40	Matrix and Tensor Factorizations
	A Grassmannian Minimum Enclosing Ball Approach for Common Subspace Extraction Emilie Renard, Kyle A. Gallivan, Pierre-Antoine Absil
	Decoupling Multivariate Functions Using Second-Order Information and Tensors Philippe Dreesen, Jeroen De Geeter, Mariya Ishteva
10:40 – 11:10	Tea / Coffee
11:10 – 12:10	Audio Data and Methods
	Blind Signal Separation by Synchronized Joint Diagonalization Hiroshi Sawada
	Exploiting Structures of Temporal Causality for Robust Speaker Localization in Reverberant Environments Christopher Schymura, Peng Guo, Yanir Maymon, Boaz Rafaely, Dorothea Kolossa
	Relative Transfer Function Estimation From Speech Keywords Ryan Corey, Andrew Singer
12:10 – 12:30	Special Session: SiSEC 2018
	The 2018 Signal Separation Evaluation Campaign Antoine Liutkus, Fabian-Robert Stöter, Nobutaka Ito
12:30 – 12:45	Poster Spotlights
12:45 – 13:40	Lunch
13:40 – 15:00	Posters and Demos
	Image Completion with Nonnegative Matrix Factorization under Separability Assumption Tomasz Sadowski, Rafal Zdunek
	Long-Term SNR Estimation Using Noise Residuals and a Two-Stage Deep-Learning Framework Xuan Dong, Donald Williamson
	Probabilistic Sparse Non-negative Matrix Factorization Jesper L. Hinrich, Morten Mørup
	Spatial Filtering of EEG Signals to Identify Periodic Brain Activity Patterns Dounia Mulders, Cyril de Bodt, Nicolas Lejeune, André Mouraux, Michel Verleysen
	Perceptual Evaluation of Blind Source Separation in Object-based Audio Production Philip Coleman, Qingju Liu, Jon Francombe, Philip Jackson
	Improving Single-Network Single-Channel Separation of Musical Audio with Convolutional Layers Gerard Roma, Owen Green, Pierre Alexandre Tremblay
	DNN-Based Music Source Separation Using MMDenseNet and BLSTM Architectures Stefan Uhlich, Franck Giron, Michael Enenkl, Thomas Kemp, Naoya Takahashi, Yuki Mitsufuji
	Speech Separation Using Partially Asynchronous Microphone Arrays Without Resampling Ryan M. Corey, Andrew C. Singer
	Source Separation with Long Time Dependency Gated Recurrent Units Neural Networks Dominic Ward, Qiuqiang Kong, Mark D. Plumbley
	Latent Mixture Models for Automatic Music Transcription Cian O’Brien, Mark D. Plumbley
	Tensorlab 4.0 – A Preview Michiel Vandecappelle, Martijn Boussey, Nico Vervliety, Matthieu Vendevilley, Rob Zinky and Lieven De Lathauwer
15:00	Social Event
19:00	Conference Banquet
Thursday, 5th July Conference Day 3
09:00 – 10:00	Keynote
	Tensor Networks and their Potential Applications in Dimensionality Reduction and Blind Signal Processing Danilo Mandic
10:00 – 10:40	Deep Learning and Data-Driven Methods
	Training Strategies for Deep Latent Models and Applications to Speech Presence Probability Estimation Shlomo Chazan, Sharon Gannot, Jacob Goldberger
	Jointly Detecting and Separating Singing Voice: A Multi-Task Approach Daniel Stoller, Sebastian Ewert, Simon Dixon
10:40 – 11:10	Tea / Coffee
11:10 – 12:30	Special Session: Advances in Phase Retrieval and Applications
	An Approximate Message Passing Approach for DOA Estimation in Phase Noisy Environments Guillaume Beaumont, Angélique Dremeau, Ronan Fablet
	An Expectation-Maximization Approach to Tuning Generalized Vector Approximate Message Passing Christopher Metzler, Philip Schniter, Richard Baraniuk
	A Study on the Benefits of Phase-Aware Speech Enhancement in Challenging Noise Scenarios Martin Krawczyk-Becker, Timo Gerkmann
	Phase Reconstruction for Time-Frequency Inpainting Ama Marina Kreme, Valentin Emiya, Caroline Chaux
12:30 – 12:45	Poster Spotlights
12:45 – 13:40	Lunch
13:40 – 15:00	Posters and Demos
	Feature Selection in Weakly Coherent Matrices Stephane Chretien, Zhen Wai Olivier Ho
	Variable Projection Applied to Block Term Decomposition of Higher-Order Tensors Guillaume Olikier, Pierre-Antoine Absil, Lieven De Lathauwer
	Independent Vector Analysis Exploiting Pre-Learned Banks of Relative Transfer Functions for Assumed Target's Positions Jaroslav Cmejla, Tomáš Kounovský, Jiri Malek, Zbyněk Koldovský
	Does k Matter? k-NN Hubness Analysis for Kernel Additive Modelling Vocal Separation Delia Fano Yela, Dan Stowell, Mark Sandler
	Improving Reverberant Speech Separation with Binaural Cues Using Temporal Context and Convolutional Neural Networks Alfredo Zermini, Qiuqiang Kong, Yong Xu, Mark Plumbley, Wenwu Wang
	Generating Talking Face Landmarks from Speech Sefik Emre Eskimez, Ross K Maddox, Chenliang Xu, Zhiyao Duan
	Using Hankel Structured Low-Rank Approximation for Sparse Signal Recovery Ivan Markovsky, Pier Luigi Dragotti
	Static and Dynamic Modeling of Absence Epileptic Seizures Using Depth Recordings Saeed Akhavan, Ronald Phlypo, Hamid Soltanian-Zadeh, Mahmoud Kamarei, Christian Jutten
	Muticriteria Decision Making Based on Independent Component Analysis: A Preliminary Investigation Considering the TOPSIS Approach Guilherme Pelegrina, Leonardo Tomazeli Duarte, João Romano
	A Latent Variable Model for Simultaneous Dimensionality Reduction and Connectivity Estimation Ricardo Pio Monti and Aapo Hyvarinen
	Loss Function Weighting Based on Source Dominance for Monaural Source Separation using Recurrent Neural Networks Seungtae Kang and Gil-Jin Jang
15:00 – 16:20	Sparsity-Related Methods
	Revisiting Synthesis Model in Sparse Audio Declipper Pavel Záviška, Pavel Rajmic, Zdeněk Průša, Vítězslav Veselý
	Consistent Dictionary Learning for Signal Declipping Lucas Rencker, Francis Bach, Wenwu Wang, Mark Plumbley
	Learning Fast Dictionaries for Sparse Representations using Low-Rank Tensor Decompositions Cassio Dantas, Jérémy Cohen, Remi Gribonval
	Truncated Variational Sampling for “Black Box” Optimization of Generative Models Jörg Lücke, Zhenwen Dai, Georgios Exarchakis
16:20 – 16:40	Closing Remarks
Friday, 6th July Audio Day
	See full programme on the Audio Day 2018 website The event includes the keynote
	EPSRC, the UK research landscape, and audio engineering research Philip Nelson