Umut Simsekli - RankMe

153 papers A* 42B 3Misc 13Journal 76Unranked 18

Year	Rank	Type	Title / Venue / Authors
2025	B	`conf`	A PAC-Bayesian Link Between Generalisation and Flat Minima. ALT Maxime Haddouche, Paul Viallard, Umut Simsekli, Benjamin Guedj
2025	J	`jnl`	Algorithm- and Data-Dependent Generalization Bounds for Score-Based Generative Models. CoRR Benjamin Dupuis, Dario Shariatian, Maxime Haddouche, Alain Durmus, Umut Simsekli
2025	J	`jnl`	Algorithmic Stability of Stochastic Gradient Descent with Momentum under Heavy-Tailed Noise. CoRR Thanh Dang, Melih Barsbey, A K. M. Rokonuzzaman Sonet, Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu
2025	A*	`conf`	Heavy-Tailed Diffusion with Denoising Levy Probabilistic Models. ICLR Dario Shariatian, Umut Simsekli, Alain Oliviero Durmus
2025	J	`jnl`	Mutual Information Free Topological Generalization Bounds via Stability. CoRR Mario Tuci, Lennart Bastian, Benjamin Dupuis, Nassir Navab, Tolga Birdal, Umut Simsekli
2025	J	`jnl`	On the Interaction of Compressibility and Adversarial Robustness. CoRR Melih Barsbey, Antônio H. Ribeiro, Umut Simsekli, Tolga Birdal
2025	J	`jnl`	Rényi Differential Privacy for Heavy-Tailed SDEs via Fractional Poincaré Inequalities. CoRR Benjamin Dupuis, Mert Gürbüzbalaban, Umut Simsekli, Jian Wang, Sinan Yildirim, Lingjiong Zhu
2025	A*	`conf`	The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training. ICML Fabian Schaipp, Alexander Hägele, Adrien B. Taylor, Umut Simsekli, Francis Bach
2025	J	`jnl`	The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training. CoRR Fabian Schaipp, Alexander Hägele, Adrien B. Taylor, Umut Simsekli, Francis R. Bach
2025	J	`jnl`	Tracking the Median of Gradients with a Stochastic Proximal Point Method. Trans. Mach. Learn. Res. Fabian Schaipp, Guillaume Garrigos, Umut Simsekli, Robert M. Gower
2025	J	`jnl`	Understanding the Generalization Error of Markov algorithms through Poissonization. CoRR Benjamin Dupuis, Maxime Haddouche, George Deligiannidis, Umut Simsekli
2024	J	`jnl`	A PAC-Bayesian Link Between Generalisation and Flat Minima. CoRR Maxime Haddouche, Paul Viallard, Umut Simsekli, Benjamin Guedj
2024	J	`jnl`	Denoising Lévy Probabilistic Models. CoRR Dario Shariatian, Umut Simsekli, Alain Durmus
2024	J	`jnl`	Differential Privacy of Noisy (S)GD under Heavy-Tailed Perturbations. CoRR Umut Simsekli, Mert Gürbüzbalaban, Sinan Yildirim, Lingjiong Zhu
2024	A*	`conf`	Generalization Bounds for Heavy-Tailed SDEs through the Fractional Fokker-Planck Equation. ICML Benjamin Dupuis, Umut Simsekli
2024	J	`jnl`	Generalization Bounds for Heavy-Tailed SDEs through the Fractional Fokker-Planck Equation. CoRR Benjamin Dupuis, Umut Simsekli
2024	A*	`conf`	Implicit Compressibility of Overparametrized Neural Networks Trained with Heavy-Tailed SGD. ICML Yijun Wan, Melih Barsbey, Abdellatif Zaidi, Umut Simsekli
2024	A*	`conf`	Piecewise deterministic generative models. NeurIPS Andrea Bertazzi, Dario Shariatian, Umut Simsekli, Eric Moulines, Alain Durmus
2024	J	`jnl`	Piecewise deterministic generative models. CoRR Andrea Bertazzi, Alain Oliviero Durmus, Dario Shariatian, Umut Simsekli, Eric Moulines
2024	J	`jnl`	SGD with Clipping is Secretly Estimating the Median Gradient. CoRR Fabian Schaipp, Guillaume Garrigos, Umut Simsekli, Robert M. Gower
2024	J	`jnl`	Tighter Generalisation Bounds via Interpolation. CoRR Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj
2024	A*	`conf`	Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms. NeurIPS Rayna Andreeva, Benjamin Dupuis, Rik Sarkar, Tolga Birdal, Umut Simsekli
2024	J	`jnl`	Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms. CoRR Rayna Andreeva, Benjamin Dupuis, Rik Sarkar, Tolga Birdal, Umut Simsekli
2024	J	`jnl`	Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets. CoRR Benjamin Dupuis, Paul Viallard, George Deligiannidis, Umut Simsekli
2024	J	`jnl`	Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets. J. Mach. Learn. Res. Benjamin Dupuis, Paul Viallard, George Deligiannidis, Umut Simsekli
2023	A*	`conf`	Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions. ICML Anant Raj, Lingjiong Zhu, Mert Gürbüzbalaban, Umut Simsekli
2023	J	`jnl`	Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions. CoRR Anant Raj, Lingjiong Zhu, Mert Gürbüzbalaban, Umut Simsekli
2023	B	`conf`	Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares. ALT Anant Raj, Melih Barsbey, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli
2023	A*	`conf`	Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient Descent. NeurIPS Kruno Lehman, Alain Durmus, Umut Simsekli
2023	J	`jnl`	Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient Descent. CoRR Krunoslav Lehman Pavasovic, Alain Durmus, Umut Simsekli
2023	J	`jnl`	Cyclic and Randomized Stepsizes Invoke Heavier Tails in SGD than Constant Stepsize. Trans. Mach. Learn. Res. Mert Gürbüzbalaban, Yuanhan Hu, Umut Simsekli, Lingjiong Zhu
2023	J	`jnl`	Cyclic and Randomized Stepsizes Invoke Heavier Tails in SGD. CoRR Mert Gürbüzbalaban, Yuanhan Hu, Umut Simsekli, Lingjiong Zhu
2023	A*	`conf`	Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models. NeurIPS Anant Raj, Umut Simsekli, Alessandro Rudi
2023	J	`jnl`	Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models. CoRR Anant Raj, Umut Simsekli, Alessandro Rudi
2023	A*	`conf`	Generalization Bounds using Data-Dependent Fractal Dimensions. ICML Benjamin Dupuis, George Deligiannidis, Umut Simsekli
2023	J	`jnl`	Generalization Bounds with Data-dependent Fractal Dimensions. CoRR Benjamin Dupuis, George Deligiannidis, Umut Simsekli
2023	A*	`conf`	Generalization Guarantees via Algorithm-dependent Rademacher Complexity. COLT Sarah Sachs, Tim van Erven, Liam Hodgkinson, Rajiv Khanna, Umut Simsekli
2023	J	`jnl`	Generalization Guarantees via Algorithm-dependent Rademacher Complexity. CoRR Sarah Sachs, Tim van Erven, Liam Hodgkinson, Rajiv Khanna, Umut Simsekli
2023	J	`jnl`	Implicit Compressibility of Overparametrized Neural Networks Trained with Heavy-Tailed SGD. CoRR Yijun Wan, Abdellatif Zaidi, Umut Simsekli
2023	A*	`conf`	Learning via Wasserstein-Based High Probability Generalisation Bounds. NeurIPS Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj
2023	J	`jnl`	Learning via Wasserstein-Based High Probability Generalisation Bounds. CoRR Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj
2023	J	`jnl`	Nonparametric Linear Feature Learning in Regression Through Regularisation. CoRR Bertille Follain, Umut Simsekli, Francis Bach
2023	A*	`conf`	Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent. NeurIPS Lingjiong Zhu, Mert Gürbüzbalaban, Anant Raj, Umut Simsekli
2023	J	`jnl`	Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent. CoRR Lingjiong Zhu, Mert Gürbüzbalaban, Anant Raj, Umut Simsekli
2022	J	`jnl`	Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares. CoRR Anant Raj, Melih Barsbey, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli
2022	A*	`conf`	Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent. NeurIPS Soon Hoe Lim, Yijun Wan, Umut Simsekli
2022	J	`jnl`	Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent. CoRR Soon Hoe Lim, Yijun Wan, Umut Simsekli
2022	A*	`conf`	Generalization Bounds for Stochastic Gradient Descent via Localized $\varepsilon$-Covers. NeurIPS Sejun Park, Umut Simsekli, Murat A. Erdogdu
2022	J	`jnl`	Generalization Bounds for Stochastic Gradient Descent via Localized ε-Covers. CoRR Sejun Park, Umut Simsekli, Murat A. Erdogdu
2022	A*	`conf`	Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers. ICML Liam Hodgkinson, Umut Simsekli, Rajiv Khanna, Michael W. Mahoney
2022	Misc	`conf`	Generalized Sliced Probability Metrics. ICASSP Soheil Kolouri, Kimia Nadjahi, Shahin Shahrampour, Umut Simsekli
2022	J	`jnl`	Heavy-Tail Phenomenon in Decentralized SGD. CoRR Mert Gürbüzbalaban, Yuanhan Hu, Umut Simsekli, Kun Yuan, Lingjiong Zhu
2022	A*	`conf`	Rate-Distortion Theoretic Generalization Bounds for Stochastic Learning Algorithms. COLT Milad Sefidgaran, Amin Gohari, Gaël Richard, Umut Simsekli
2022	J	`jnl`	Rate-Distortion Theoretic Generalization Bounds for Stochastic Learning Algorithms. CoRR Milad Sefidgaran, Amin Gohari, Gaël Richard, Umut Simsekli
2022	J	`jnl`	Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks. J. Mach. Learn. Res. Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar, Umut Simsekli, Lingjiong Zhu
2021	A*	`conf`	Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections. ICML Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris C. Holmes, Mert Gürbüzbalaban, Umut Simsekli
2021	J	`jnl`	Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections. CoRR Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris C. Holmes, Mert Gürbüzbalaban, Umut Simsekli
2021	J	`jnl`	Bayesian Allocation Model: Marginal Likelihood-Based Model Selection for Count Tensors. IEEE J. Sel. Top. Signal Process. Sinan Yildirim, M. Burak Kurutmaz, Melih Barsbey, Umut Simsekli, A. Taylan Cemgil
2021	A*	`conf`	Convergence Rates of Stochastic Gradient Descent under Infinite Noise Variance. NeurIPS Hongjian Wang, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli, Murat A. Erdogdu
2021	A*	`conf`	Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections. NeurIPS Kimia Nadjahi, Alain Durmus, Pierre E. Jacob, Roland Badeau, Umut Simsekli
2021	J	`jnl`	Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections. CoRR Kimia Nadjahi, Alain Durmus, Pierre E. Jacob, Roland Badeau, Umut Simsekli
2021	A*	`conf`	Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms. NeurIPS Alexander Camuto, George Deligiannidis, Murat A. Erdogdu, Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu
2021	J	`jnl`	Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms. CoRR Alexander Camuto, George Deligiannidis, Murat A. Erdogdu, Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu
2021	J	`jnl`	Generalization Properties of Stochastic Optimizers via Trajectory Analysis. CoRR Liam Hodgkinson, Umut Simsekli, Rajiv Khanna, Michael W. Mahoney
2021	A*	`conf`	Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks. NeurIPS Melih Barsbey, Milad Sefidgaran, Murat A. Erdogdu, Gaël Richard, Umut Simsekli
2021	J	`jnl`	Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks. CoRR Melih Barsbey, Milad Sefidgaran, Murat A. Erdogdu, Gaël Richard, Umut Simsekli
2021	A*	`conf`	Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks. NeurIPS Tolga Birdal, Aaron Lou, Leonidas J. Guibas, Umut Simsekli
2021	J	`jnl`	Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks. CoRR Tolga Birdal, Aaron Lou, Leonidas J. Guibas, Umut Simsekli
2021	A*	`conf`	Relative Positional Encoding for Transformers with Linear Complexity. ICML Antoine Liutkus, Ondrej Cífka, Shih-Lun Wu, Umut Simsekli, Yi-Hsuan Yang, Gaël Richard
2021	J	`jnl`	Relative Positional Encoding for Transformers with Linear Complexity. CoRR Antoine Liutkus, Ondrej Cífka, Shih-Lun Wu, Umut Simsekli, Yi-Hsuan Yang, Gaël Richard
2021	J	`jnl`	Self-Supervised VQ-VAE For One-Shot Music Style Transfer. CoRR Ondrej Cífka, Alexey Ozerov, Umut Simsekli, Gaël Richard
2021	Misc	`conf`	Self-Supervised VQ-VAE for One-Shot Music Style Transfer. ICASSP Ondrej Cífka, Alexey Ozerov, Umut Simsekli, Gaël Richard
2021	A*	`conf`	The Heavy-Tail Phenomenon in SGD. ICML Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu
2020	Misc	`conf`	Approximate Bayesian Computation with the Sliced-Wasserstein Distance. ICASSP Kimia Nadjahi, Valentin De Bortoli, Alain Durmus, Roland Badeau, Umut Simsekli
2020	A*	`conf`	Explicit Regularisation in Gaussian Noise Injections. NeurIPS Alexander Camuto, Matthew Willetts, Umut Simsekli, Stephen J. Roberts, Chris C. Holmes
2020	J	`jnl`	Explicit Regularisation in Gaussian Noise Injections. CoRR Alexander Camuto, Matthew Willetts, Umut Simsekli, Stephen J. Roberts, Chris C. Holmes
2020	A*	`conf`	Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise. ICML Umut Simsekli, Lingjiong Zhu, Yee Whye Teh, Mert Gürbüzbalaban
2020	J	`jnl`	Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise. CoRR Umut Simsekli, Lingjiong Zhu, Yee Whye Teh, Mert Gürbüzbalaban
2020	J	`jnl`	Generalized Sliced Distances for Probability Distributions. CoRR Soheil Kolouri, Kimia Nadjahi, Umut Simsekli, Shahin Shahrampour
2020	J	`jnl`	Groove2Groove: One-Shot Music Style Transfer With Supervision From Synthetic Data. IEEE ACM Trans. Audio Speech Lang. Process. Ondrej Cífka, Umut Simsekli, Gaël Richard
2020	A*	`conf`	Hausdorff Dimension, Heavy Tails, and Generalization in Neural Networks. NeurIPS Umut Simsekli, Ozan Sener, George Deligiannidis, Murat A. Erdogdu
2020	J	`jnl`	Hausdorff Dimension, Stochastic Differential Equations, and Generalization in Neural Networks. CoRR Umut Simsekli, Ozan Sener, George Deligiannidis, Murat A. Erdogdu
2020	—	`conf`	Matrix Factorization for High Frequency Non Intrusive Load Monitoring: Definitions and Algorithms. NILM@SenSys Simon Henriet, Benoit Fuentes, Umut Simsekli, Gaël Richard
2020	A*	`conf`	Quantitative Propagation of Chaos for SGD in Wide Neural Networks. NeurIPS Valentin De Bortoli, Alain Durmus, Xavier Fontaine, Umut Simsekli
2020	J	`jnl`	Quantitative Propagation of Chaos for SGD in Wide Neural Networks. CoRR Valentin De Bortoli, Alain Durmus, Xavier Fontaine, Umut Simsekli
2020	A*	`conf`	Statistical and Topological Properties of Sliced Probability Divergences. NeurIPS Kimia Nadjahi, Alain Durmus, Lénaïc Chizat, Soheil Kolouri, Shahin Shahrampour, Umut Simsekli
2020	J	`jnl`	Statistical and Topological Properties of Sliced Probability Divergences. CoRR Kimia Nadjahi, Alain Durmus, Lénaïc Chizat, Soheil Kolouri, Shahin Shahrampour, Umut Simsekli
2020	A*	`conf`	Synchronizing Probability Measures on Rotations via Optimal Transport. CVPR Tolga Birdal, Michael Arbel, Umut Simsekli, Leonidas J. Guibas
2020	J	`jnl`	Synchronizing Probability Measures on Rotations via Optimal Transport. CoRR Tolga Birdal, Michael Arbel, Umut Simsekli, Leonidas J. Guibas
2020	J	`jnl`	The Heavy-Tail Phenomenon in SGD. CoRR Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu
2019	A*	`conf`	A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks. ICML Umut Simsekli, Levent Sagun, Mert Gürbüzbalaban
2019	J	`jnl`	A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks. CoRR Umut Simsekli, Levent Sagun, Mert Gürbüzbalaban
2019	J	`jnl`	A framework for parallel second order incremental optimization algorithms for solving partially separable problems. Comput. Optim. Appl. Kamer Kaya, Figen Öztoprak, S. Ilker Birbil, A. Taylan Cemgil, Umut Simsekli, Nurdan Kuru, Hazal Koptagel, M. Kaan Öztürk
2019	A*	`conf`	Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance. NeurIPS Kimia Nadjahi, Alain Durmus, Umut Simsekli, Roland Badeau
2019	J	`jnl`	Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance. CoRR Kimia Nadjahi, Alain Durmus, Umut Simsekli, Roland Badeau
2019	J	`jnl`	Bayesian Allocation Model: Inference by Sequential Monte Carlo for Nonnegative Tensor Factorizations and Topic Models using Polya Urns. CoRR Ali Taylan Cemgil, Mehmet Burak Kurutmaz, Sinan Yildirim, Melih Barsbey, Umut Simsekli
2019	A*	`conf`	First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise. NeurIPS Thanh Huy Nguyen, Umut Simsekli, Mert Gürbüzbalaban, Gaël Richard
2019	J	`jnl`	First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise. CoRR Thanh Huy Nguyen, Umut Simsekli, Mert Gürbüzbalaban, Gaël Richard
2019	A*	`conf`	Generalized Sliced Wasserstein Distances. NeurIPS Soheil Kolouri, Kimia Nadjahi, Umut Simsekli, Roland Badeau, Gustavo K. Rohde
2019	J	`jnl`	Generalized Sliced Wasserstein Distances. CoRR Soheil Kolouri, Kimia Nadjahi, Umut Simsekli, Roland Badeau, Gustavo K. Rohde
2019	J	`jnl`	Independent-Variation Matrix Factorization With Application to Energy Disaggregation. IEEE Signal Process. Lett. Simon Henriet, Umut Simsekli, Sergio Dos Santos, Benoit Fuentes, Gaël Richard
2019	A*	`conf`	Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization. ICML Thanh Huy Nguyen, Umut Simsekli, Gaël Richard
2019	J	`jnl`	Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization. CoRR Thanh Huy Nguyen, Umut Simsekli, Gaël Richard
2019	J	`jnl`	On the Heavy-Tailed Theory of Stochastic Gradient Descent for Deep Neural Networks. CoRR Umut Simsekli, Mert Gürbüzbalaban, Thanh Huy Nguyen, Gaël Richard, Levent Sagun
2019	A*	`conf`	Probabilistic Permutation Synchronization Using the Riemannian Structure of the Birkhoff Polytope. CVPR Tolga Birdal, Umut Simsekli
2019	J	`jnl`	Probabilistic Permutation Synchronization using the Riemannian Structure of the Birkhoff Polytope. CoRR Tolga Birdal, Umut Simsekli
2019	J	`jnl`	Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks. CoRR Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar, Umut Simsekli, Lingjiong Zhu
2019	A*	`conf`	Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions. ICML Antoine Liutkus, Umut Simsekli, Szymon Majewski, Alain Durmus, Fabian-Robert Stöter
2019	Misc	`conf`	Speech Enhancement with Variational Autoencoders and Alpha-stable Distributions. ICASSP Simon Leglaive, Umut Simsekli, Antoine Liutkus, Laurent Girin, Radu Horaud
2019	J	`jnl`	Speech enhancement with variational autoencoders and alpha-stable distributions. CoRR Simon Leglaive, Umut Simsekli, Antoine Liutkus, Laurent Girin, Radu Horaud
2019	—	`conf`	Supervised Symbolic Music Style Translation Using Synthetic Data. ISMIR Ondrej Cífka, Umut Simsekli, Gaël Richard
2019	J	`jnl`	Supervised Symbolic Music Style Translation Using Synthetic Data. CoRR Ondrej Cífka, Umut Simsekli, Gaël Richard
2018	J	`jnl`	A Generative Model for Non-Intrusive Load Monitoring in Commercial Buildings. CoRR Simon Henriet, Umut Simsekli, Benoit Fuentes, Gaël Richard
2018	Misc	`conf`	Alpha-Stable Low-Rank Plus Residual Decomposition for Speech Enhancement. ICASSP Umut Simsekli, Halil Erdogan, Simon Leglaive, Antoine Liutkus, Roland Badeau, Gaël Richard
2018	A*	`conf`	Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization. ICML Umut Simsekli, Çagatay Yildiz, Thanh Huy Nguyen, A. Taylan Cemgil, Gaël Richard
2018	J	`jnl`	Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization. CoRR Umut Simsekli, Çagatay Yildiz, Thanh Huy Nguyen, Gaël Richard, A. Taylan Cemgil
2018	A*	`conf`	Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC. NeurIPS Tolga Birdal, Umut Simsekli, Mustafa Onur Eken, Slobodan Ilic
2018	J	`jnl`	Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC. CoRR Tolga Birdal, Umut Simsekli, M. Onur Eken, Slobodan Ilic
2018	J	`jnl`	Efficient Bayesian Model Selection in PARAFAC via Stochastic Thermodynamic Integration. IEEE Signal Process. Lett. Thanh Huy Nguyen, Umut Simsekli, Gaël Richard, Ali Taylan Cemgil
2018	—	`conf`	Multichannel Audio Modeling with Elliptically Stable Tensor Decomposition. LVA/ICA Mathieu Fontaine, Fabian-Robert Stöter, Antoine Liutkus, Umut Simsekli, Romain Serizel, Roland Badeau
2018	J	`jnl`	Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions. CoRR Umut Simsekli, Antoine Liutkus, Szymon Majewski, Alain Durmus
2017	Misc	`conf`	Alpha-stable multichannel audio source separation. ICASSP Simon Leglaive, Umut Simsekli, Antoine Liutkus, Roland Badeau, Gaël Richard
2017	A*	`conf`	Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for Markov Chain Monte Carlo. ICML Umut Simsekli
2017	—	`conf`	Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse Coding. NIPS Mainak Jas, Tom Dupré la Tour, Umut Simsekli, Alexandre Gramfort
2017	Misc	`conf`	Parallelized Stochastic Gradient Markov Chain Monte Carlo algorithms for non-negative matrix factorization. ICASSP Umut Simsekli, Alain Durmus, Roland Badeau, Gaël Richard, Eric Moulines, A. Taylan Cemgil
2017	—	`conf`	Synthetic dataset generation for non-intrusive load monitoring in commercial buildings. BuildSys Simon Henriet, Umut Simsekli, Gaël Richard, Benoit Fuentes
2016	—	`conf`	Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo. NIPS Alain Durmus, Umut Simsekli, Eric Moulines, Roland Badeau, Gaël Richard
2016	A*	`conf`	Stochastic Quasi-Newton Langevin Monte Carlo. ICML Umut Simsekli, Roland Badeau, A. Taylan Cemgil, Gaël Richard
2016	Misc	`conf`	Stochastic thermodynamic integration: Efficient Bayesian model selection via stochastic gradient MCMC. ICASSP Umut Simsekli, Roland Badeau, Gaël Richard, Ali Taylan Cemgil
2015	Misc	`conf`	A unified probabilistic framework for robust decoding of linear barcodes. ICASSP Umut Simsekli, Tolga Birdal
2015	J	`jnl`	Alpha-Stable Matrix Factorization. IEEE Signal Process. Lett. Umut Simsekli, Antoine Liutkus, Ali Taylan Cemgil
2015	—	`conf`	Extraction of Temporal Patterns in Multi-rate and Multi-modal Datasets. LVA/ICA Antoine Liutkus, Umut Simsekli, A. Taylan Cemgil
2015	J	`jnl`	HAMSI: Distributed Incremental Optimization Algorithm Using Quadratic Approximations for Partially Separable Problems. CoRR Umut Simsekli, Hazal Koptagel, Figen Öztoprak, S. Ilker Birbil, Ali Taylan Cemgil
2015	Misc	`conf`	Learning mixed divergences in coupled matrix and tensor factorization models. ICASSP Umut Simsekli, Ali Taylan Cemgil, Beyza Ermis
2015	J	`jnl`	Non-negative tensor factorization models for Bayesian audio processing. Digit. Signal Process. Umut Simsekli, Tuomas Virtanen, Ali Taylan Cemgil
2015	Misc	`conf`	Section-level modeling of musical audio for linking performances to scores in Turkish makam music. ICASSP Andre Holzapfel, Umut Simsekli, Sertan Sentürk, Ali Taylan Cemgil
2015	—	`—`	Tensor fusion: Learning in heterogeneous and distributed data (Tensör tümleştirme: Ayrı cinsten ve dağıtık verilerde öğrenme) Umut Simsekli
2014	Misc	`conf`	Non-negative source-filter dynamical system for speech enhancement. ICASSP Umut Simsekli, Jonathan Le Roux, John R. Hershey
2013	—	`conf`	A factorization based recommender system for online services. SIU Umut Simsekli, Tolga Birdal, Emre Koc, Ali Taylan Cemgil
2013	—	`conf`	Hierarchical and coupled non-negative dynamical systems with application to audio modeling. WASPAA Umut Simsekli, Jonathan Le Roux, John R. Hershey
2013	—	`conf`	Learning the beta-Divergence in Tweedie Compound Poisson Matrix Factorization Models. ICML (3) Umut Simsekli, Ali Taylan Cemgil, Yusuf Kenan Yilmaz
2013	—	`conf`	Optimal weight learning for Coupled Tensor Factorization with mixed divergences. EUSIPCO Umut Simsekli, Beyza Ermis, A. Taylan Cemgil, Evrim Acar
2012	J	`jnl`	Combined perception and control for timing in robotic music performances. EURASIP J. Audio Speech Music. Process. Umut Simsekli, Orhan Sonmez, Baris Kurt, Ali Taylan Cemgil
2012	—	`conf`	Coupled tensor factorization models for polyphonic music transcription. SIU Umut Simsekli, Yusuf Kenan Yilmaz, Ali Taylan Cemgil
2012	—	`conf`	Large scale polyphonic music transcription using randomized matrix decompositions. EUSIPCO Ismail An, Umut Simsekli, Ali Taylan Cemgil, Lale Akarun
2012	—	`conf`	Markov Chain Monte Carlo inference for probabilistic latent tensor factorization. MLSP Umut Simsekli, A. Taylan Cemgil
2012	—	`conf`	SVD-based polyphonic music transcription. SIU Ismail Ari, Umut Simsekli, Ali Taylan Cemgil, Lale Akarun
2012	Misc	`conf`	Score guided audio restoration via generalised coupled tensor factorisation. ICASSP Umut Simsekli, Yusuf Kenan Yilmaz, Ali Taylan Cemgil
2012	—	`conf`	Score guided musical source separation using Generalized Coupled Tensor Factorization. EUSIPCO Umut Simsekli, A. Taylan Cemgil
2011	—	`conf`	Generalised Coupled Tensor Factorisation. NIPS Yusuf Kenan Yilmaz, Ali Taylan Cemgil, Umut Simsekli
2011	—	`conf`	Probabilistic latent tensor factorization framework for audio modeling. WASPAA Ali Taylan Cemgil, Umut Simsekli, Yusuf Cem Sübakan
2011	J	`jnl`	Real-Time Recognition of Percussive Sounds by a Model-Based Method. EURASIP J. Adv. Signal Process. Umut Simsekli, Antti Jylhä, Cumhur Erkut, Ali Taylan Cemgil
2010	B	`conf`	Automatic Music Genre Classification Using Bass Lines. ICPR Umut Simsekli