Umut Şimşekli

1. Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions
   2018/06/21 by Antoine Liutkus, Liutkus, Antoine, Umut Ş Imşekli +8 · 19 citations
   Computer Science · Mathematics · #Generative Adversarial Networks and Image Synthesis #Stochastic Gradient Optimization Techniques #Markov Chains and Monte Carlo Methods
2. Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks
   2021/11/25 by Tolga Birdal, Aaron Lou, Birdal, Tolga +5 · 13 citations
   Computer Science · Mathematics · #Advanced Graph Neural Networks #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Mathematics #General Topology (math.GN) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Morphological variations and asymmetry #Topological and Geometric Data Analysis
3. On the Heavy-Tailed Theory of Stochastic Gradient Descent for Deep Neural Networks
   2019/11/29 by Umut Şimşekli, Şimşekli, Umut, Mert Gürbüzbalaban +7 · 11 citations
   Computer Science · Engineering · #Stochastic Gradient Optimization Techniques #Sparse and Compressive Sensing Techniques #Adversarial Robustness in Machine Learning
4. Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks
   2021/06/07 by Melih Barsbey, Milad Sefidgaran, Barsbey, Melih +7 · 10 citations
   Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Stochastic Gradient Optimization Techniques
5. Fast Approximation of the Sliced-Wasserstein Distance Using\n Concentration of Random Projections
   2021/06/29 by Kimia Nadjahi, Nadjahi, Kimia, Alain Durmus +7 · 5 citations
   Mathematics · #Geometric Analysis and Curvature Flows
6. Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC
   2018/05/31 by Tolga Birdal, Birdal, Tolga, Umut Şimşekli +5 · 5 citations
   Computer Science · Engineering · #3D Shape Modeling and Analysis #Advanced Vision and Imaging #Artificial Intelligence (cs.AI) #Computational Geometry (cs.CG) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (stat.ML) #Robotics (cs.RO) #Robotics and Sensor-Based Localization
7. Convergence Rates of Stochastic Gradient Descent under Infinite Noise Variance
   2021/02/20 by Hongjian Wang, Mert Gürbüzbalaban, Wang, Hongjian +7 · 4 citations
   Computer Science · Engineering · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Random Matrices and Applications #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
8. Quantitative Propagation of Chaos for SGD in Wide Neural Networks
   2020/07/13 by Valentin De Bortoli, De Bortoli, Valentin, Alain Durmus +5 · 3 citations
   Computer Science · Mathematics · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Model Reduction and Neural Networks #Probability (math.PR) #Stochastic Gradient Optimization Techniques
9. Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for\n Non-Convex Optimization
   2019/01/22 by Thanh Huy Nguyen, Nguyen, Thanh Huy, Umut Şimşekli +3 · 4 citations
   Mathematics · Engineering · Computer Science · #Mathematical Approximation and Integration #Control Systems and Identification #Image and Signal Denoising Methods
10. Implicit Compressibility of Overparametrized Neural Networks Trained with Heavy-Tailed SGD
    2023/06/13 by Yijun Wan, Wan, Yijun, Barsbey, Melih +4 · 4 citations
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Neural Networks and Applications #Probability (math.PR) #Stochastic Gradient Optimization Techniques
11. Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions
    2023/01/27 by Anant Raj, Raj, Anant, Lingjiong Zhu +5 · 4 citations
    Computer Science · Mathematics · #FOS: Computer and information sciences #Geometric Analysis and Curvature Flows #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Stochastic Gradient Optimization Techniques
12. Learning via Wasserstein-Based High Probability Generalisation Bounds
    2023/06/07 by Paul Viallard, Viallard, Paul, Maxime Haddouche +5 · 2 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
13. Generalized Sliced Distances for Probability Distributions
    2020/02/28 by Soheil Kolouri, Kolouri, Soheil, Kimia Nadjahi +5 · 1 citation
    Computer Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis #Human Pose and Action Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML)
14. Heavy-Tailed Diffusion with Denoising Lévy Probabilistic Models
    2024/07/26 by Dario Shariatian, Shariatian, Dario, Umut Şimşekli +3 · 2 citations
    Computer Science · Decision Sciences · #Advanced Database Systems and Queries #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Simulation Techniques and Applications #Time Series Analysis and Forecasting
15. Privacy of SGD under Gaussian or Heavy-Tailed Noise: Guarantees without Gradient Clipping
    2024/03/04 by Umut Şimşekli, Şimşekli, Umut, Mert Gürbüzbalaban +5 · 2 citations
    Computer Science · #Cryptography and Data Security #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #FOS: Mathematics #Internet Traffic Analysis and Secure E-voting #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Privacy-Preserving Technologies in Data #Statistics Theory (math.ST)
16. Probabilistic Permutation Synchronization using the Riemannian Structure\n of the Birkhoff Polytope
    2019/04/11 by Tolga Birdal, Umut Şimşekli, Birdal, Tolga +1 · 1 citation
    Computer Science · #Advanced Image and Video Retrieval Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Mathematics #Graph Theory and Algorithms #Graphics (cs.GR) #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #Robotics (cs.RO) #Topological and Geometric Data Analysis
17. Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent
    2022/05/23 by Soon Hoe Lim, Lim, Soon Hoe, Yijun Wan +3 · 1 citation
    Computer Science · Mathematics · Physics and Astronomy · #Advanced Thermodynamics and Statistical Mechanics #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Probability (math.PR) #Stochastic Gradient Optimization Techniques
18. Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms
    2024/07/11 by Rayna Andreeva, Andreeva, Rayna, Benjamin Dupuis +7 · 2 citations
    Computer Science · #Advanced Image and Video Retrieval Techniques #Algebraic Topology (math.AT) #FOS: Computer and information sciences #FOS: Mathematics #Image Retrieval and Classification Techniques #Machine Learning (cs.LG) #Topological and Geometric Data Analysis
19. Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient Descent
    2023/10/27 by Krunoslav Lehman Pavasovic, Pavasovic, Krunoslav Lehman, Alain Durmus +3 · 1 citation
    Computer Science · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Stochastic Gradient Optimization Techniques
20. Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent
    2023/05/20 by Lingjiong Zhu, Zhu, Lingjiong, Mert Gürbüzbalaban +5 · 1 citation
    Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
21. Generalization Guarantees via Algorithm-dependent Rademacher Complexity
    2023/07/04 by Sarah Sachs, Tim van Erven, Sachs, Sarah +7 · 1 citation
    Computer Science · Engineering · #FOS: Computer and information sciences #Ferroelectric and Negative Capacitance Devices #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Stochastic Gradient Optimization Techniques
22. Generalization Bounds for Markov Algorithms through Entropy Flow Computations
    2025/02/11 by Benjamin Dupuis, Maxime Haddouche, Dupuis, Benjamin +6 · 1 voice · 1 citation
    Computer Science · Mathematics · #Neural Networks and Applications #cs.LG #stat.ML