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Umut Simsekli
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2020 – today
- 2024
- [c71]Benjamin Dupuis, Umut Simsekli:
Generalization Bounds for Heavy-Tailed SDEs through the Fractional Fokker-Planck Equation. ICML 2024 - [c70]Yijun Wan, Melih Barsbey, Abdellatif Zaidi, Umut Simsekli:
Implicit Compressibility of Overparametrized Neural Networks Trained with Heavy-Tailed SGD. ICML 2024 - [i56]Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj:
Tighter Generalisation Bounds via Interpolation. CoRR abs/2402.05101 (2024) - [i55]Benjamin Dupuis, Umut Simsekli:
Generalization Bounds for Heavy-Tailed SDEs through the Fractional Fokker-Planck Equation. CoRR abs/2402.07723 (2024) - [i54]Maxime Haddouche, Paul Viallard, Umut Simsekli, Benjamin Guedj:
A PAC-Bayesian Link Between Generalisation and Flat Minima. CoRR abs/2402.08508 (2024) - [i53]Fabian Schaipp, Guillaume Garrigos, Umut Simsekli, Robert M. Gower:
SGD with Clipping is Secretly Estimating the Median Gradient. CoRR abs/2402.12828 (2024) - [i52]Umut Simsekli, Mert Gürbüzbalaban, Sinan Yildirim, Lingjiong Zhu:
Differential Privacy of Noisy (S)GD under Heavy-Tailed Perturbations. CoRR abs/2403.02051 (2024) - [i51]Benjamin Dupuis, Paul Viallard, George Deligiannidis
, Umut Simsekli:
Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets. CoRR abs/2404.17442 (2024) - [i50]Rayna Andreeva, Benjamin Dupuis, Rik Sarkar, Tolga Birdal, Umut Simsekli:
Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms. CoRR abs/2407.08723 (2024) - [i49]Dario Shariatian, Umut Simsekli, Alain Durmus:
Denoising Lévy Probabilistic Models. CoRR abs/2407.18609 (2024) - [i48]Andrea Bertazzi, Alain Oliviero Durmus, Dario Shariatian, Umut Simsekli, Eric Moulines:
Piecewise deterministic generative models. CoRR abs/2407.19448 (2024) - 2023
- [j11]Mert Gürbüzbalaban, Yuanhan Hu, Umut Simsekli, Lingjiong Zhu:
Cyclic and Randomized Stepsizes Invoke Heavier Tails in SGD than Constant Stepsize. Trans. Mach. Learn. Res. 2023 (2023) - [c69]Anant Raj, Melih Barsbey, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli:
Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares. ALT 2023: 1292-1342 - [c68]Sarah Sachs, Tim van Erven, Liam Hodgkinson, Rajiv Khanna, Umut Simsekli:
Generalization Guarantees via Algorithm-dependent Rademacher Complexity. COLT 2023: 4863-4880 - [c67]Benjamin Dupuis, George Deligiannidis, Umut Simsekli:
Generalization Bounds using Data-Dependent Fractal Dimensions. ICML 2023: 8922-8968 - [c66]Anant Raj, Lingjiong Zhu, Mert Gürbüzbalaban, Umut Simsekli:
Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions. ICML 2023: 28578-28597 - [c65]Kruno Lehman, Alain Durmus, Umut Simsekli:
Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient Descent. NeurIPS 2023 - [c64]Anant Raj, Umut Simsekli, Alessandro Rudi:
Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models. NeurIPS 2023 - [c63]Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj:
Learning via Wasserstein-Based High Probability Generalisation Bounds. NeurIPS 2023 - [c62]Lingjiong Zhu, Mert Gürbüzbalaban, Anant Raj, Umut Simsekli:
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent. NeurIPS 2023 - [i47]Anant Raj
Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions. CoRR abs/2301.11885 (2023) - [i46]Benjamin Dupuis, George Deligiannidis, Umut Simsekli:
Generalization Bounds with Data-dependent Fractal Dimensions. CoRR abs/2302.02766 (2023) - [i45]Mert Gürbüzbalaban, Yuanhan Hu, Umut Simsekli, Lingjiong Zhu:
Cyclic and Randomized Stepsizes Invoke Heavier Tails in SGD. CoRR abs/2302.05516 (2023) - [i44]Anant Raj, Umut Simsekli, Alessandro Rudi:
Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models. CoRR abs/2303.17109 (2023) - [i43]Lingjiong Zhu, Mert Gürbüzbalaban, Anant Raj
Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent. CoRR abs/2305.12056 (2023) - [i42]Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj:
Learning via Wasserstein-Based High Probability Generalisation Bounds. CoRR abs/2306.04375 (2023) - [i41]Yijun Wan, Abdellatif Zaidi, Umut Simsekli:
Implicit Compressibility of Overparametrized Neural Networks Trained with Heavy-Tailed SGD. CoRR abs/2306.08125 (2023) - [i40]Sarah Sachs, Tim van Erven, Liam Hodgkinson, Rajiv Khanna, Umut Simsekli:
Generalization Guarantees via Algorithm-dependent Rademacher Complexity. CoRR abs/2307.02501 (2023) - [i39]Bertille Follain, Umut Simsekli, Francis Bach:
Nonparametric Linear Feature Learning in Regression Through Regularisation. CoRR abs/2307.12754 (2023) - [i38]Krunoslav Lehman Pavasovic, Alain Durmus, Umut Simsekli:
Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient Descent. CoRR abs/2310.18455 (2023) - 2022
- [j10]Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar, Umut Simsekli, Lingjiong Zhu:
Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks. J. Mach. Learn. Res. 23: 220:1-220:96 (2022) - [c61]Milad Sefidgaran, Amin Gohari, Gaël Richard, Umut Simsekli:
Rate-Distortion Theoretic Generalization Bounds for Stochastic Learning Algorithms. COLT 2022: 4416-4463 - [c60]Soheil Kolouri, Kimia Nadjahi, Shahin Shahrampour, Umut Simsekli:
Generalized Sliced Probability Metrics. ICASSP 2022: 4513-4517 - [c59]Liam Hodgkinson, Umut Simsekli, Rajiv Khanna, Michael W. Mahoney:
Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers. ICML 2022: 8774-8795 - [c58]Soon Hoe Lim, Yijun Wan, Umut Simsekli:
Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent. NeurIPS 2022 - [c57]Sejun Park, Umut Simsekli, Murat A. Erdogdu:
Generalization Bounds for Stochastic Gradient Descent via Localized $\varepsilon$-Covers. NeurIPS 2022 - [i37]Milad Sefidgaran, Amin Gohari, Gaël Richard, Umut Simsekli:
Rate-Distortion Theoretic Generalization Bounds for Stochastic Learning Algorithms. CoRR abs/2203.02474 (2022) - [i36]Mert Gürbüzbalaban, Yuanhan Hu, Umut Simsekli, Kun Yuan, Lingjiong Zhu:
Heavy-Tail Phenomenon in Decentralized SGD. CoRR abs/2205.06689 (2022) - [i35]Soon Hoe Lim, Yijun Wan, Umut Simsekli:
Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent. CoRR abs/2205.11361 (2022) - [i34]Anant Raj
Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares. CoRR abs/2206.01274 (2022) - [i33]Sejun Park, Umut Simsekli, Murat A. Erdogdu:
Generalization Bounds for Stochastic Gradient Descent via Localized ε-Covers. CoRR abs/2209.08951 (2022) - 2021
- [j9]Sinan Yildirim
Bayesian Allocation Model: Marginal Likelihood-Based Model Selection for Count Tensors. IEEE J. Sel. Top. Signal Process. 15(3): 560-573 (2021) - [c56]Ondrej Cífka
Self-Supervised VQ-VAE for One-Shot Music Style Transfer. ICASSP 2021: 96-100 - [c55]Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris C. Holmes, Mert Gürbüzbalaban, Umut Simsekli:
Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections. ICML 2021: 1249-1260 - [c54]Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu:
The Heavy-Tail Phenomenon in SGD. ICML 2021: 3964-3975 - [c53]Antoine Liutkus, Ondrej Cífka, Shih-Lun Wu, Umut Simsekli, Yi-Hsuan Yang, Gaël Richard:
Relative Positional Encoding for Transformers with Linear Complexity. ICML 2021: 7067-7079 - [c52]Tolga Birdal, Aaron Lou, Leonidas J. Guibas, Umut Simsekli:
Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks. NeurIPS 2021: 6776-6789 - [c51]Kimia Nadjahi, Alain Durmus, Pierre E. Jacob, Roland Badeau, Umut Simsekli:
Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections. NeurIPS 2021: 12411-12424 - [c50]Alexander Camuto, George Deligiannidis, Murat A. Erdogdu, Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu:
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms. NeurIPS 2021: 18774-18788 - [c49]Hongjian Wang, Mert Gürbüzbalaban, Lingjiong Zhu, Umut Simsekli, Murat A. Erdogdu:
Convergence Rates of Stochastic Gradient Descent under Infinite Noise Variance. NeurIPS 2021: 18866-18877 - [c48]Melih Barsbey, Milad Sefidgaran, Murat A. Erdogdu, Gaël Richard, Umut Simsekli:
Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks. NeurIPS 2021: 29364-29378 - [i32]Ondrej Cífka
Self-Supervised VQ-VAE For One-Shot Music Style Transfer. CoRR abs/2102.05749 (2021) - [i31]Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris C. Holmes, Mert Gürbüzbalaban, Umut Simsekli:
Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections. CoRR abs/2102.07006 (2021) - [i30]Antoine Liutkus, Ondrej Cífka
Relative Positional Encoding for Transformers with Linear Complexity. CoRR abs/2105.08399 (2021) - [i29]Melih Barsbey, Milad Sefidgaran, Murat A. Erdogdu, Gaël Richard, Umut Simsekli:
Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks. CoRR abs/2106.03795 (2021) - [i28]Alexander Camuto, George Deligiannidis, Murat A. Erdogdu, Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu:
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms. CoRR abs/2106.04881 (2021) - [i27]Kimia Nadjahi, Alain Durmus, Pierre E. Jacob, Roland Badeau, Umut Simsekli:
Fast Approximation of the Sliced-Wasserstein Distance Using Concentration of Random Projections. CoRR abs/2106.15427 (2021) - [i26]Liam Hodgkinson, Umut Simsekli, Rajiv Khanna, Michael W. Mahoney:
Generalization Properties of Stochastic Optimizers via Trajectory Analysis. CoRR abs/2108.00781 (2021) - [i25]Tolga Birdal, Aaron Lou, Leonidas J. Guibas, Umut Simsekli:
Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks. CoRR abs/2111.13171 (2021) - 2020
- [j8]Ondrej Cífka
Groove2Groove: One-Shot Music Style Transfer With Supervision From Synthetic Data. IEEE ACM Trans. Audio Speech Lang. Process. 28: 2638-2650 (2020) - [c47]Tolga Birdal
Synchronizing Probability Measures on Rotations via Optimal Transport. CVPR 2020: 1566-1576 - [c46]Kimia Nadjahi, Valentin De Bortoli, Alain Durmus, Roland Badeau, Umut Simsekli:
Approximate Bayesian Computation with the Sliced-Wasserstein Distance. ICASSP 2020: 5470-5474 - [c45]Umut Simsekli, Lingjiong Zhu, Yee Whye Teh, Mert Gürbüzbalaban:
Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise. ICML 2020: 8970-8980 - [c44]Valentin De Bortoli, Alain Durmus, Xavier Fontaine, Umut Simsekli:
Quantitative Propagation of Chaos for SGD in Wide Neural Networks. NeurIPS 2020 - [c43]Alexander Camuto, Matthew Willetts, Umut Simsekli, Stephen J. Roberts, Chris C. Holmes:
Explicit Regularisation in Gaussian Noise Injections. NeurIPS 2020 - [c42]Kimia Nadjahi, Alain Durmus, Lénaïc Chizat, Soheil Kolouri, Shahin Shahrampour, Umut Simsekli:
Statistical and Topological Properties of Sliced Probability Divergences. NeurIPS 2020 - [c41]Umut Simsekli, Ozan Sener, George Deligiannidis, Murat A. Erdogdu:
Hausdorff Dimension, Heavy Tails, and Generalization in Neural Networks. NeurIPS 2020 - [c40]Simon Henriet, Benoit Fuentes, Umut Simsekli, Gaël Richard:
Matrix Factorization for High Frequency Non Intrusive Load Monitoring: Definitions and Algorithms. NILM@SenSys 2020: 20-24 - [d1]Ondrej Cífka
Groove2Groove MIDI Dataset: synthetic accompaniments in 3k styles. Zenodo, 2020 - [i24]Umut Simsekli, Lingjiong Zhu, Yee Whye Teh, Mert Gürbüzbalaban:
Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise. CoRR abs/2002.05685 (2020) - [i23]Soheil Kolouri, Kimia Nadjahi, Umut Simsekli, Shahin Shahrampour:
Generalized Sliced Distances for Probability Distributions. CoRR abs/2002.12537 (2020) - [i22]Kimia Nadjahi, Alain Durmus, Lénaïc Chizat, Soheil Kolouri, Shahin Shahrampour, Umut Simsekli:
Statistical and Topological Properties of Sliced Probability Divergences. CoRR abs/2003.05783 (2020) - [i21]Tolga Birdal, Michael Arbel, Umut Simsekli, Leonidas J. Guibas:
Synchronizing Probability Measures on Rotations via Optimal Transport. CoRR abs/2004.00663 (2020) - [i20]Mert Gürbüzbalaban, Umut Simsekli, Lingjiong Zhu:
The Heavy-Tail Phenomenon in SGD. CoRR abs/2006.04740 (2020) - [i19]Umut Simsekli, Ozan Sener, George Deligiannidis, Murat A. Erdogdu:
Hausdorff Dimension, Stochastic Differential Equations, and Generalization in Neural Networks. CoRR abs/2006.09313 (2020) - [i18]Valentin De Bortoli, Alain Durmus, Xavier Fontaine, Umut Simsekli:
Quantitative Propagation of Chaos for SGD in Wide Neural Networks. CoRR abs/2007.06352 (2020) - [i17]Alexander Camuto, Matthew Willetts, Umut Simsekli, Stephen J. Roberts, Chris C. Holmes:
Explicit Regularisation in Gaussian Noise Injections. CoRR abs/2007.07368 (2020)
2010 – 2019
- 2019
- [j7]Kamer Kaya, Figen Öztoprak, S. Ilker Birbil
A framework for parallel second order incremental optimization algorithms for solving partially separable problems. Comput. Optim. Appl. 72(3): 675-705 (2019) - [j6]Simon Henriet
Independent-Variation Matrix Factorization With Application to Energy Disaggregation. IEEE Signal Process. Lett. 26(11): 1643-1647 (2019) - [c39]Tolga Birdal
Probabilistic Permutation Synchronization Using the Riemannian Structure of the Birkhoff Polytope. CVPR 2019: 11105-11116 - [c38]Simon Leglaive
Speech Enhancement with Variational Autoencoders and Alpha-stable Distributions. ICASSP 2019: 541-545 - [c37]Antoine Liutkus, Umut Simsekli, Szymon Majewski, Alain Durmus, Fabian-Robert Stöter:
Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions. ICML 2019: 4104-4113 - [c36]Thanh Huy Nguyen, Umut Simsekli, Gaël Richard:
Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization. ICML 2019: 4810-4819 - [c35]Umut Simsekli, Levent Sagun, Mert Gürbüzbalaban:
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks. ICML 2019: 5827-5837 - [c34]Ondrej Cífka, Umut Simsekli, Gaël Richard:
Supervised Symbolic Music Style Translation Using Synthetic Data. ISMIR 2019: 588-595 - [c33]Kimia Nadjahi, Alain Durmus, Umut Simsekli, Roland Badeau:
Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance. NeurIPS 2019: 250-260 - [c32]Soheil Kolouri, Kimia Nadjahi, Umut Simsekli, Roland Badeau, Gustavo K. Rohde:
Generalized Sliced Wasserstein Distances. NeurIPS 2019: 261-272 - [c31]Thanh Huy Nguyen, Umut Simsekli, Mert Gürbüzbalaban, Gaël Richard:
First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise. NeurIPS 2019: 273-283 - [i16]Umut Simsekli, Levent Sagun, Mert Gürbüzbalaban:
A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks. CoRR abs/1901.06053 (2019) - [i15]Thanh Huy Nguyen, Umut Simsekli, Gaël Richard:
Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization. CoRR abs/1901.07487 (2019) - [i14]Soheil Kolouri, Kimia Nadjahi, Umut Simsekli, Roland Badeau, Gustavo K. Rohde:
Generalized Sliced Wasserstein Distances. CoRR abs/1902.00434 (2019) - [i13]Simon Leglaive, Umut Simsekli, Antoine Liutkus, Laurent Girin, Radu Horaud:
Speech enhancement with variational autoencoders and alpha-stable distributions. CoRR abs/1902.03926 (2019) - [i12]Ali Taylan Cemgil, Mehmet Burak Kurutmaz, Sinan Yildirim
Bayesian Allocation Model: Inference by Sequential Monte Carlo for Nonnegative Tensor Factorizations and Topic Models using Polya Urns. CoRR abs/1903.04478 (2019) - [i11]Tolga Birdal, Umut Simsekli:
Probabilistic Permutation Synchronization using the Riemannian Structure of the Birkhoff Polytope. CoRR abs/1904.05814 (2019) - [i10]Kimia Nadjahi, Alain Durmus, Umut Simsekli, Roland Badeau:
Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance. CoRR abs/1906.04516 (2019) - [i9]Thanh Huy Nguyen, Umut Simsekli, Mert Gürbüzbalaban, Gaël Richard:
First Exit Time Analysis of Stochastic Gradient Descent Under Heavy-Tailed Gradient Noise. CoRR abs/1906.09069 (2019) - [i8]Ondrej Cífka, Umut Simsekli, Gaël Richard:
Supervised Symbolic Music Style Translation Using Synthetic Data. CoRR abs/1907.02265 (2019) - [i7]Alireza Fallah, Mert Gürbüzbalaban, Asuman E. Ozdaglar, Umut Simsekli, Lingjiong Zhu:
Robust Distributed Accelerated Stochastic Gradient Methods for Multi-Agent Networks. CoRR abs/1910.08701 (2019) - [i6]Umut Simsekli, Mert Gürbüzbalaban, Thanh Huy Nguyen, Gaël Richard, Levent Sagun:
On the Heavy-Tailed Theory of Stochastic Gradient Descent for Deep Neural Networks. CoRR abs/1912.00018 (2019) - 2018
- [j5]Thanh Huy Nguyen
Efficient Bayesian Model Selection in PARAFAC via Stochastic Thermodynamic Integration. IEEE Signal Process. Lett. 25(5): 725-729 (2018) - [c30]Mathieu Fontaine
Multichannel Audio Modeling with Elliptically Stable Tensor Decomposition. LVA/ICA 2018: 13-23 - [c29]Umut Simsekli, Halil Erdogan, Simon Leglaive
Alpha-Stable Low-Rank Plus Residual Decomposition for Speech Enhancement. ICASSP 2018: 651-655 - [c28]Umut Simsekli, Çagatay Yildiz, Thanh Huy Nguyen, A. Taylan Cemgil, Gaël Richard:
Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization. ICML 2018: 4681-4690 - [c27]Tolga Birdal, Umut Simsekli, Mustafa Onur Eken, Slobodan Ilic:
Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC. NeurIPS 2018: 306-317 - [i5]Simon Henriet, Umut Simsekli, Benoit Fuentes, Gaël Richard:
A Generative Model for Non-Intrusive Load Monitoring in Commercial Buildings. CoRR abs/1803.00515 (2018) - [i4]Tolga Birdal, Umut Simsekli, M. Onur Eken, Slobodan Ilic:
Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC. CoRR abs/1805.12279 (2018) - [i3]Umut Simsekli, Çagatay Yildiz, Thanh Huy Nguyen, Gaël Richard, A. Taylan Cemgil:
Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization. CoRR abs/1806.02617 (2018) - [i2]Umut Simsekli, Antoine Liutkus, Szymon Majewski, Alain Durmus:
Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions. CoRR abs/1806.08141 (2018) - 2017
- [c26]Simon Leglaive
Alpha-stable multichannel audio source separation. ICASSP 2017: 576-580 - [c25]Umut Simsekli, Alain Durmus, Roland Badeau, Gaël Richard, Eric Moulines, A. Taylan Cemgil:
Parallelized Stochastic Gradient Markov Chain Monte Carlo algorithms for non-negative matrix factorization. ICASSP 2017: 2242-2246 - [c24]Umut Simsekli:
Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for Markov Chain Monte Carlo. ICML 2017: 3200-3209 - [c23]Mainak Jas, Tom Dupré la Tour, Umut Simsekli, Alexandre Gramfort:
Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse Coding. NIPS 2017: 1099-1108 - [c22]Simon Henriet, Umut Simsekli, Gaël Richard, Benoit Fuentes:
Synthetic dataset generation for non-intrusive load monitoring in commercial buildings. BuildSys@SenSys 2017: 39:1-39:2 - 2016
- [c21]Umut Simsekli, Roland Badeau, Gaël Richard, Ali Taylan Cemgil:
Stochastic thermodynamic integration: Efficient Bayesian model selection via stochastic gradient MCMC. ICASSP 2016: 2574-2578 - [c20]Umut Simsekli, Roland Badeau, A. Taylan Cemgil, Gaël Richard:
Stochastic Quasi-Newton Langevin Monte Carlo. ICML 2016: 642-651 - [c19]Alain Durmus, Umut Simsekli, Eric Moulines, Roland Badeau, Gaël Richard:
Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo. NIPS 2016: 2047-2055 - 2015
- [b1]Umut Simsekli:
Tensor fusion: Learning in heterogeneous and distributed data (Tensör tümleştirme: Ayrı cinsten ve dağıtık verilerde öğrenme). Boğaziçi University, Turkey, 2015 - [j4]Umut Simsekli, Tuomas Virtanen
Non-negative tensor factorization models for Bayesian audio processing. Digit. Signal Process. 47: 178-191 (2015) - [j3]Umut Simsekli, Antoine Liutkus, Ali Taylan Cemgil:
Alpha-Stable Matrix Factorization. IEEE Signal Process. Lett. 22(12): 2289-2293 (2015) - [c18]Antoine Liutkus, Umut Simsekli, A. Taylan Cemgil
Extraction of Temporal Patterns in Multi-rate and Multi-modal Datasets. LVA/ICA 2015: 135-142 - [c17]Andre Holzapfel, Umut Simsekli, Sertan Sentürk
Section-level modeling of musical audio for linking performances to scores in Turkish makam music. ICASSP 2015: 141-145 - [c16]Umut Simsekli, Tolga Birdal
A unified probabilistic framework for robust decoding of linear barcodes. ICASSP 2015: 1946-1950 - [c15]Umut Simsekli, Ali Taylan Cemgil
Learning mixed divergences in coupled matrix and tensor factorization models. ICASSP 2015: 2120-2124 - [i1]Umut Simsekli, Hazal Koptagel, Figen Öztoprak, S. Ilker Birbil, Ali Taylan Cemgil:
HAMSI: Distributed Incremental Optimization Algorithm Using Quadratic Approximations for Partially Separable Problems. CoRR abs/1509.01698 (2015) - 2014
- [c14]Umut Simsekli, Jonathan Le Roux, John R. Hershey:
Non-negative source-filter dynamical system for speech enhancement. ICASSP 2014: 6206-6210 - 2013
- [c13]Umut Simsekli, Beyza Ermis, A. Taylan Cemgil, Evrim Acar:
Optimal weight learning for Coupled Tensor Factorization with mixed divergences. EUSIPCO 2013: 1-5 - [c12]Umut Simsekli, Ali Taylan Cemgil, Yusuf Kenan Yilmaz:
Learning the beta-Divergence in Tweedie Compound Poisson Matrix Factorization Models. ICML (3) 2013: 1409-1417 - [c11]Umut Simsekli, Tolga Birdal
A factorization based recommender system for online services. SIU 2013: 1-4 - [c10]Umut Simsekli, Jonathan Le Roux, John R. Hershey:
Hierarchical and coupled non-negative dynamical systems with application to audio modeling. WASPAA 2013: 1-4 - 2012
- [j2]Umut Simsekli, Orhan Sonmez, Baris Kurt, Ali Taylan Cemgil
Combined perception and control for timing in robotic music performances. EURASIP J. Audio Speech Music. Process. 2012: 8 (2012) - [c9]Ismail An, Umut Simsekli, Ali Taylan Cemgil, Lale Akarun:
Large scale polyphonic music transcription using randomized matrix decompositions. EUSIPCO 2012: 2020-2024 - [c8]Umut Simsekli, A. Taylan Cemgil:
Score guided musical source separation using Generalized Coupled Tensor Factorization. EUSIPCO 2012: 2639-2643 - [c7]Umut Simsekli, Yusuf Kenan Yilmaz, Ali Taylan Cemgil
Score guided audio restoration via generalised coupled tensor factorisation. ICASSP 2012: 5369-5372 - [c6]Umut Simsekli, A. Taylan Cemgil
Markov Chain Monte Carlo inference for probabilistic latent tensor factorization. MLSP 2012: 1-6 - [c5]Ismail Ari, Umut Simsekli, Ali Taylan Cemgil
SVD-based polyphonic music transcription. SIU 2012: 1-4 - [c4]Umut Simsekli, Yusuf Kenan Yilmaz, Ali Taylan Cemgil
Coupled tensor factorization models for polyphonic music transcription. SIU 2012: 1-4 - 2011
- [j1]Umut Simsekli, Antti Jylhä
Real-Time Recognition of Percussive Sounds by a Model-Based Method. EURASIP J. Adv. Signal Process. 2011 (2011) - [c3]Yusuf Kenan Yilmaz, Ali Taylan Cemgil, Umut Simsekli:
Generalised Coupled Tensor Factorisation. NIPS 2011: 2151-2159 - [c2]Ali Taylan Cemgil
Probabilistic latent tensor factorization framework for audio modeling. WASPAA 2011: 137-140 - 2010
- [c1]Umut Simsekli:
Automatic Music Genre Classification Using Bass Lines. ICPR 2010: 4137-4140
Coauthor Index
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For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
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to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
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last updated on 2024-10-07 21:25 CEST by the dblp team
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