Multivariate iterative hard thresholding for sparse decomposition with flexible sparsity patterns. - Lucas Rencker; Wenwu Wang 001; Mark D. Plumbley (EUSIPCO, 2017)

Assessment of musical noise using localization of isolated peaks in time-frequency domain. - Ronan Hamon; Valentin Emiya; Lucas Rencker; Wenwu Wang 001; Mark D. Plumbley (ICASSP, 2017)

A greedy algorithm with learned statistics for sparse signal reconstruction. - Lucas Rencker; Wenwu Wang 001; Mark D. Plumbley (ICASSP, 2017)

Consistent Dictionary Learning for Signal Declipping. - Lucas Rencker; Francis R. Bach; Wenwu Wang 001; Mark D. Plumbley (LVA/ICA, 2018)

Orthogonality-Regularized Masked NMF for Learning on Weakly Labeled Audio Data. - Iwona Sobieraj; Lucas Rencker; Mark D. Plumbley (ICASSP, 2018)

An RIP-Based Performance Guarantee of Covariance-Assisted Matching Pursuit. - Jiayang Wang; Gen Li 005; Lucas Rencker; Wenwu Wang 001; Yuantao Gu (IEEE Signal Process. Lett., 2018)

Sparse Recovery and Dictionary Learning From Nonlinear Compressive Measurements. - Lucas Rencker; Francis R. Bach; Wenwu Wang 001; Mark D. Plumbley (IEEE Trans. Signal Process., 2019)

Context-Aware Prosody Correction for Text-Based Speech Editing. - Max Morrison; Lucas Rencker; Zeyu Jin; Nicholas J. Bryan; Juan Pablo Cáceres; Bryan Pardo (ICASSP, 2021)

Sparse Analysis Model Based Dictionary Learning for Signal Declipping. - Bin Li 062; Lucas Rencker; Jing Dong 001; Yuhui Luo; Mark D. Plumbley; Wenwu Wang 001 (IEEE J. Sel. Top. Signal Process., 2021)

A Survey and an Extensive Evaluation of Popular Audio Declipping Methods. - Pavel Záviska; Pavel Rajmic; Alexey Ozerov; Lucas Rencker (IEEE J. Sel. Top. Signal Process., 2021)