Automatic Music Genre Classification Using Bass Lines. - Umut Simsekli (ICPR, 2010)

Generalised Coupled Tensor Factorisation. - Yusuf Kenan Yilmaz; Ali Taylan Cemgil; Umut Simsekli (NIPS, 2011)

Probabilistic latent tensor factorization framework for audio modeling. - Ali Taylan Cemgil; Umut Simsekli; Yusuf Cem Sübakan (WASPAA, 2011)

Real-Time Recognition of Percussive Sounds by a Model-Based Method. - Umut Simsekli; Antti Jylhä; Cumhur Erkut; Ali Taylan Cemgil (EURASIP J. Adv. Signal Process., 2011)

Large scale polyphonic music transcription using randomized matrix decompositions. - Ismail An; Umut Simsekli; Ali Taylan Cemgil; Lale Akarun (EUSIPCO, 2012)

Score guided musical source separation using Generalized Coupled Tensor Factorization. - Umut Simsekli; A. Taylan Cemgil (EUSIPCO, 2012)

Score guided audio restoration via generalised coupled tensor factorisation. - Umut Simsekli; Yusuf Kenan Yilmaz; Ali Taylan Cemgil (ICASSP, 2012)

Markov Chain Monte Carlo inference for probabilistic latent tensor factorization. - Umut Simsekli; A. Taylan Cemgil (MLSP, 2012)

SVD-based polyphonic music transcription. - Ismail Ari; Umut Simsekli; Ali Taylan Cemgil; Lale Akarun (SIU, 2012)

Coupled tensor factorization models for polyphonic music transcription. - Umut Simsekli; Yusuf Kenan Yilmaz; Ali Taylan Cemgil (SIU, 2012)

Combined perception and control for timing in robotic music performances. - Umut Simsekli; Orhan Sonmez; Baris Kurt; Ali Taylan Cemgil (EURASIP J. Audio Speech Music. Process., 2012)

Optimal weight learning for Coupled Tensor Factorization with mixed divergences. - Umut Simsekli; Beyza Ermis; A. Taylan Cemgil; Evrim Acar (EUSIPCO, 2013)

Learning the beta-Divergence in Tweedie Compound Poisson Matrix Factorization Models. - Umut Simsekli; Ali Taylan Cemgil; Yusuf Kenan Yilmaz (ICML (3), 2013)

A factorization based recommender system for online services. - Umut Simsekli; Tolga Birdal; Emre Koc; Ali Taylan Cemgil (SIU, 2013)

Hierarchical and coupled non-negative dynamical systems with application to audio modeling. - Umut Simsekli; Jonathan Le Roux; John R. Hershey (WASPAA, 2013)

Non-negative source-filter dynamical system for speech enhancement. - Umut Simsekli; Jonathan Le Roux; John R. Hershey (ICASSP, 2014)

Extraction of Temporal Patterns in Multi-rate and Multi-modal Datasets. - Antoine Liutkus; Umut Simsekli; A. Taylan Cemgil (LVA/ICA, 2015)

Section-level modeling of musical audio for linking performances to scores in Turkish makam music. - Andre Holzapfel; Umut Simsekli; Sertan Sentürk; Ali Taylan Cemgil (ICASSP, 2015)

A unified probabilistic framework for robust decoding of linear barcodes. - Umut Simsekli; Tolga Birdal (ICASSP, 2015)

Learning mixed divergences in coupled matrix and tensor factorization models. - Umut Simsekli; Ali Taylan Cemgil; Beyza Ermis (ICASSP, 2015)

HAMSI: Distributed Incremental Optimization Algorithm Using Quadratic Approximations for Partially Separable Problems. - Umut Simsekli; Hazal Koptagel; Figen Öztoprak; S. Ilker Birbil; Ali Taylan Cemgil (CoRR, 2015)

Non-negative tensor factorization models for Bayesian audio processing. - Umut Simsekli; Tuomas Virtanen; Ali Taylan Cemgil (Digit. Signal Process., 2015)

Alpha-Stable Matrix Factorization. - Umut Simsekli; Antoine Liutkus; Ali Taylan Cemgil (IEEE Signal Process. Lett., 2015)

Tensor fusion: Learning in heterogeneous and distributed data (Tensör tümleştirme: Ayrı cinsten ve dağıtık verilerde öğrenme) - Umut Simsekli (2015)

Stochastic thermodynamic integration: Efficient Bayesian model selection via stochastic gradient MCMC. - Umut Simsekli; Roland Badeau; Gaël Richard; Ali Taylan Cemgil (ICASSP, 2016)

Stochastic Quasi-Newton Langevin Monte Carlo. - Umut Simsekli; Roland Badeau; A. Taylan Cemgil; Gaël Richard (ICML, 2016)

Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo. - Alain Durmus; Umut Simsekli; Eric Moulines; Roland Badeau; Gaël Richard (NIPS, 2016)

Alpha-stable multichannel audio source separation. - Simon Leglaive; Umut Simsekli; Antoine Liutkus; Roland Badeau; Gaël Richard (ICASSP, 2017)

Parallelized Stochastic Gradient Markov Chain Monte Carlo algorithms for non-negative matrix factorization. - Umut Simsekli; Alain Durmus; Roland Badeau; Gaël Richard; Eric Moulines; A. Taylan Cemgil (ICASSP, 2017)

Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for Markov Chain Monte Carlo. - Umut Simsekli (ICML, 2017)

Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse Coding. - Mainak Jas; Tom Dupré la Tour; Umut Simsekli; Alexandre Gramfort (NIPS, 2017)

Synthetic dataset generation for non-intrusive load monitoring in commercial buildings. - Simon Henriet; Umut Simsekli; Gaël Richard; Benoit Fuentes (BuildSys, 2017)

Multichannel Audio Modeling with Elliptically Stable Tensor Decomposition. - Mathieu Fontaine 002; Fabian-Robert Stöter; Antoine Liutkus; Umut Simsekli; Romain Serizel; Roland Badeau (LVA/ICA, 2018)

Alpha-Stable Low-Rank Plus Residual Decomposition for Speech Enhancement. - Umut Simsekli; Halil Erdogan; Simon Leglaive; Antoine Liutkus; Roland Badeau; Gaël Richard (ICASSP, 2018)

Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization. - Umut Simsekli; Çagatay Yildiz; Thanh Huy Nguyen 001; A. Taylan Cemgil; Gaël Richard (ICML, 2018)

Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC. - Tolga Birdal; Umut Simsekli; Mustafa Onur Eken; Slobodan Ilic (NeurIPS, 2018)

A Generative Model for Non-Intrusive Load Monitoring in Commercial Buildings. - Simon Henriet; Umut Simsekli; Benoit Fuentes; Gaël Richard (CoRR, 2018)

Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions. - Umut Simsekli; Antoine Liutkus; Szymon Majewski; Alain Durmus (CoRR, 2018)

Efficient Bayesian Model Selection in PARAFAC via Stochastic Thermodynamic Integration. - Thanh Huy Nguyen 001; Umut Simsekli; Gaël Richard; Ali Taylan Cemgil (IEEE Signal Process. Lett., 2018)

Probabilistic Permutation Synchronization Using the Riemannian Structure of the Birkhoff Polytope. - Tolga Birdal; Umut Simsekli (CVPR, 2019)

Speech Enhancement with Variational Autoencoders and Alpha-stable Distributions. - Simon Leglaive; Umut Simsekli; Antoine Liutkus; Laurent Girin; Radu Horaud (ICASSP, 2019)

Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions. - Antoine Liutkus; Umut Simsekli; Szymon Majewski; Alain Durmus; Fabian-Robert Stöter (ICML, 2019)

Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization. - Thanh Huy Nguyen 001; Umut Simsekli; Gaël Richard (ICML, 2019)

A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks. - Umut Simsekli; Levent Sagun; Mert Gürbüzbalaban (ICML, 2019)

Supervised Symbolic Music Style Translation Using Synthetic Data. - Ondrej Cífka; Umut Simsekli; Gaël Richard (ISMIR, 2019)

Generalized Sliced Wasserstein Distances. - Soheil Kolouri; Kimia Nadjahi; Umut Simsekli; Roland Badeau; Gustavo K. Rohde (NeurIPS, 2019)

Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance. - Kimia Nadjahi; Alain Durmus; Umut Simsekli; Roland Badeau (NeurIPS, 2019)

First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise. - Thanh Huy Nguyen 001; Umut Simsekli; Mert Gürbüzbalaban; Gaël Richard (NeurIPS, 2019)

A framework for parallel second order incremental optimization algorithms for solving partially separable problems. - Kamer Kaya; Figen Öztoprak; S. Ilker Birbil; A. Taylan Cemgil; Umut Simsekli; Nurdan Kuru; Hazal Koptagel; M. Kaan Öztürk (Comput. Optim. Appl., 2019)

Bayesian Allocation Model: Inference by Sequential Monte Carlo for Nonnegative Tensor Factorizations and Topic Models using Polya Urns. - Ali Taylan Cemgil; Mehmet Burak Kurutmaz; Sinan Yildirim; Melih Barsbey; Umut Simsekli (CoRR, 2019)

On the Heavy-Tailed Theory of Stochastic Gradient Descent for Deep Neural Networks. - Umut Simsekli; Mert Gürbüzbalaban; Thanh Huy Nguyen 001; Gaël Richard; Levent Sagun (CoRR, 2019)

Independent-Variation Matrix Factorization With Application to Energy Disaggregation. - Simon Henriet; Umut Simsekli; Sergio Dos Santos; Benoit Fuentes; Gaël Richard (IEEE Signal Process. Lett., 2019)

Synchronizing Probability Measures on Rotations via Optimal Transport. - Tolga Birdal; Michael Arbel; Umut Simsekli; Leonidas J. Guibas (CVPR, 2020)

Approximate Bayesian Computation with the Sliced-Wasserstein Distance. - Kimia Nadjahi; Valentin De Bortoli; Alain Durmus; Roland Badeau; Umut Simsekli (ICASSP, 2020)

Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise. - Umut Simsekli; Lingjiong Zhu; Yee Whye Teh; Mert Gürbüzbalaban (ICML, 2020)

Quantitative Propagation of Chaos for SGD in Wide Neural Networks. - Valentin De Bortoli; Alain Durmus; Xavier Fontaine; Umut Simsekli (NeurIPS, 2020)

Explicit Regularisation in Gaussian Noise Injections. - Alexander Camuto; Matthew Willetts; Umut Simsekli; Stephen J. Roberts; Chris C. Holmes (NeurIPS, 2020)

Statistical and Topological Properties of Sliced Probability Divergences. - Kimia Nadjahi; Alain Durmus; Lénaïc Chizat; Soheil Kolouri; Shahin Shahrampour; Umut Simsekli (NeurIPS, 2020)

Hausdorff Dimension, Heavy Tails, and Generalization in Neural Networks. - Umut Simsekli; Ozan Sener; George Deligiannidis; Murat A. Erdogdu (NeurIPS, 2020)

Matrix Factorization for High Frequency Non Intrusive Load Monitoring: Definitions and Algorithms. - Simon Henriet; Benoit Fuentes; Umut Simsekli; Gaël Richard (NILM@SenSys, 2020)

Generalized Sliced Distances for Probability Distributions. - Soheil Kolouri; Kimia Nadjahi; Umut Simsekli; Shahin Shahrampour (CoRR, 2020)

Hausdorff Dimension, Stochastic Differential Equations, and Generalization in Neural Networks. - Umut Simsekli; Ozan Sener; George Deligiannidis; Murat A. Erdogdu (CoRR, 2020)

Groove2Groove: One-Shot Music Style Transfer With Supervision From Synthetic Data. - Ondrej Cífka; Umut Simsekli; Gaël Richard (IEEE ACM Trans. Audio Speech Lang. Process., 2020)

Groove2Groove MIDI Dataset: synthetic accompaniments in 3k styles. - Ondrej Cífka; Umut Simsekli; Gaël Richard (Zenodo, 2020)

Self-Supervised VQ-VAE for One-Shot Music Style Transfer. - Ondrej Cífka; Alexey Ozerov; Umut Simsekli; Gaël Richard (ICASSP, 2021)

Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections. - Alexander Camuto; Xiaoyu Wang; Lingjiong Zhu; Chris C. Holmes; Mert Gürbüzbalaban; Umut Simsekli (ICML, 2021)

The Heavy-Tail Phenomenon in SGD. - Mert Gürbüzbalaban; Umut Simsekli; Lingjiong Zhu (ICML, 2021)

Relative Positional Encoding for Transformers with Linear Complexity. - Antoine Liutkus; Ondrej Cífka; Shih-Lun Wu; Umut Simsekli; Yi-Hsuan Yang; Gaël Richard (ICML, 2021)

Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks. - Melih Barsbey; Milad Sefidgaran; Murat A. Erdogdu; Gaël Richard; Umut Simsekli (NeurIPS, 2021)

Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks. - Tolga Birdal; Aaron Lou; Leonidas J. Guibas; Umut Simsekli (NeurIPS, 2021)

Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms. - Alexander Camuto; George Deligiannidis; Murat A. Erdogdu; Mert Gürbüzbalaban; Umut Simsekli; Lingjiong Zhu (NeurIPS, 2021)

Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections. - Kimia Nadjahi; Alain Durmus; Pierre E. Jacob; Roland Badeau; Umut Simsekli (NeurIPS, 2021)

Convergence Rates of Stochastic Gradient Descent under Infinite Noise Variance. - Hongjian Wang; Mert Gürbüzbalaban; Lingjiong Zhu; Umut Simsekli; Murat A. Erdogdu (NeurIPS, 2021)

Generalization Properties of Stochastic Optimizers via Trajectory Analysis. - Liam Hodgkinson; Umut Simsekli; Rajiv Khanna; Michael W. Mahoney (CoRR, 2021)

Bayesian Allocation Model: Marginal Likelihood-Based Model Selection for Count Tensors. - Sinan Yildirim; M. Burak Kurutmaz; Melih Barsbey; Umut Simsekli; A. Taylan Cemgil (IEEE J. Sel. Top. Signal Process., 2021)

Rate-Distortion Theoretic Generalization Bounds for Stochastic Learning Algorithms. - Milad Sefidgaran; Amin Gohari; Gaël Richard; Umut Simsekli (COLT, 2022)

Generalized Sliced Probability Metrics. - Soheil Kolouri; Kimia Nadjahi; Shahin Shahrampour; Umut Simsekli (ICASSP, 2022)

Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers. - Liam Hodgkinson; Umut Simsekli; Rajiv Khanna; Michael W. Mahoney (ICML, 2022)

Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent. - Soon Hoe Lim; Yijun Wan; Umut Simsekli (NeurIPS, 2022)

Generalization Bounds for Stochastic Gradient Descent via Localized $ varepsilon$-Covers. - Sejun Park; Umut Simsekli; Murat A. Erdogdu (NeurIPS, 2022)

Heavy-Tail Phenomenon in Decentralized SGD. - Mert Gürbüzbalaban; Yuanhan Hu; Umut Simsekli; Kun Yuan 001; Lingjiong Zhu (CoRR, 2022)

Generalization Bounds for Stochastic Gradient Descent via Localized ε-Covers. - Sejun Park; Umut Simsekli; Murat A. Erdogdu (CoRR, 2022)

Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks. - Alireza Fallah 001; Mert Gürbüzbalaban; Asuman E. Ozdaglar; Umut Simsekli; Lingjiong Zhu (J. Mach. Learn. Res., 2022)

Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares. - Anant Raj; Melih Barsbey; Mert Gürbüzbalaban; Lingjiong Zhu; Umut Simsekli (ALT, 2023)

Generalization Guarantees via Algorithm-dependent Rademacher Complexity. - Sarah Sachs; Tim van Erven; Liam Hodgkinson; Rajiv Khanna; Umut Simsekli (COLT, 2023)

Generalization Bounds using Data-Dependent Fractal Dimensions. - Benjamin Dupuis; George Deligiannidis; Umut Simsekli (ICML, 2023)

Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions. - Anant Raj; Lingjiong Zhu; Mert Gürbüzbalaban; Umut Simsekli (ICML, 2023)

Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient Descent. - Kruno Lehman; Alain Durmus; Umut Simsekli (NeurIPS, 2023)

Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models. - Anant Raj; Umut Simsekli; Alessandro Rudi (NeurIPS, 2023)

Learning via Wasserstein-Based High Probability Generalisation Bounds. - Paul Viallard; Maxime Haddouche; Umut Simsekli; Benjamin Guedj (NeurIPS, 2023)

Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent. - Lingjiong Zhu; Mert Gürbüzbalaban; Anant Raj; Umut Simsekli (NeurIPS, 2023)

Generalization Bounds with Data-dependent Fractal Dimensions. - Benjamin Dupuis; George Deligiannidis; Umut Simsekli (CoRR, 2023)

Cyclic and Randomized Stepsizes Invoke Heavier Tails in SGD. - Mert Gürbüzbalaban; Yuanhan Hu; Umut Simsekli; Lingjiong Zhu (CoRR, 2023)

Implicit Compressibility of Overparametrized Neural Networks Trained with Heavy-Tailed SGD. - Yijun Wan; Abdellatif Zaidi; Umut Simsekli (CoRR, 2023)

Nonparametric Linear Feature Learning in Regression Through Regularisation. - Bertille Follain; Umut Simsekli; Francis Bach 001 (CoRR, 2023)

Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient Descent. - Krunoslav Lehman Pavasovic; Alain Durmus; Umut Simsekli (CoRR, 2023)

Cyclic and Randomized Stepsizes Invoke Heavier Tails in SGD than Constant Stepsize. - Mert Gürbüzbalaban; Yuanhan Hu; Umut Simsekli; Lingjiong Zhu (Trans. Mach. Learn. Res., 2023)

Generalization Bounds for Heavy-Tailed SDEs through the Fractional Fokker-Planck Equation. - Benjamin Dupuis; Umut Simsekli (ICML, 2024)

Implicit Compressibility of Overparametrized Neural Networks Trained with Heavy-Tailed SGD. - Yijun Wan; Melih Barsbey; Abdellatif Zaidi; Umut Simsekli (ICML, 2024)

Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms. - Rayna Andreeva; Benjamin Dupuis; Rik Sarkar; Tolga Birdal; Umut Simsekli (NeurIPS, 2024)

Piecewise deterministic generative models. - Andrea Bertazzi; Dario Shariatian; Umut Simsekli; Eric Moulines; Alain Durmus (NeurIPS, 2024)

Tighter Generalisation Bounds via Interpolation. - Paul Viallard; Maxime Haddouche; Umut Simsekli; Benjamin Guedj (CoRR, 2024)

SGD with Clipping is Secretly Estimating the Median Gradient. - Fabian Schaipp; Guillaume Garrigos; Umut Simsekli; Robert M. Gower (CoRR, 2024)

Differential Privacy of Noisy (S)GD under Heavy-Tailed Perturbations. - Umut Simsekli; Mert Gürbüzbalaban; Sinan Yildirim; Lingjiong Zhu (CoRR, 2024)

Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets. - Benjamin Dupuis; Paul Viallard; George Deligiannidis; Umut Simsekli (CoRR, 2024)

Denoising Lévy Probabilistic Models. - Dario Shariatian; Umut Simsekli; Alain Durmus (CoRR, 2024)

A PAC-Bayesian Link Between Generalisation and Flat Minima. - Maxime Haddouche; Paul Viallard; Umut Simsekli; Benjamin Guedj (ALT, 2025)

Heavy-Tailed Diffusion with Denoising Levy Probabilistic Models. - Dario Shariatian; Umut Simsekli; Alain Oliviero Durmus (ICLR, 2025)

The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training. - Fabian Schaipp; Alexander Hägele; Adrien B. Taylor; Umut Simsekli; Francis R. Bach (CoRR, 2025)

Algorithmic Stability of Stochastic Gradient Descent with Momentum under Heavy-Tailed Noise. - Thanh Dang; Melih Barsbey; A K. M. Rokonuzzaman Sonet; Mert Gürbüzbalaban; Umut Simsekli; Lingjiong Zhu (CoRR, 2025)

Understanding the Generalization Error of Markov algorithms through Poissonization. - Benjamin Dupuis; Maxime Haddouche; George Deligiannidis; Umut Simsekli (CoRR, 2025)

Algorithm- and Data-Dependent Generalization Bounds for Score-Based Generative Models. - Benjamin Dupuis; Dario Shariatian; Maxime Haddouche; Alain Durmus; Umut Simsekli (CoRR, 2025)

Mutual Information Free Topological Generalization Bounds via Stability. - Mario Tuci; Lennart Bastian; Benjamin Dupuis; Nassir Navab; Tolga Birdal; Umut Simsekli (CoRR, 2025)

On the Interaction of Compressibility and Adversarial Robustness. - Melih Barsbey; Antônio H. Ribeiro; Umut Simsekli; Tolga Birdal (CoRR, 2025)