Lionel Tondji

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All published works

Action	Title	Year	Authors
+ PDF Chat	Acceleration and restart for the randomized Bregman-Kaczmarz method	2024	Lionel Tondji Ion Necoara Dirk A. Lorenz
+ PDF Chat	Adaptive Bregman–Kaczmarz: an approach to solve linear inverse problems with independent noise exactly	2024	Lionel Tondji Idriss Tondji Dirk A. Lorenz
+ PDF Chat	Linearly convergent adjoint free solution of least squares problems by random descent	2023	Dirk A. Lorenz Felix Schneppe Lionel Tondji
+	An accelerated randomized Bregman-Kaczmarz method for strongly convex linearly constraint optimization*	2023	Lionel Tondji Dirk A. Lorenz Ion Necoara
+	Linearly convergent adjoint free solution of least squares problems by random descent	2023	Dirk A. Lorenz Felix Schneppe Lionel Tondji
+	Adaptive Bregman-Kaczmarz: An Approach to Solve Linear Inverse Problems with Independent Noise Exactly	2023	Lionel Tondji Idriss Tondji Dirk A. Lorenz
+	Acceleration and restart for the randomized Bregman-Kaczmarz method	2023	Lionel Tondji Ion Necoara Dirk A. Lorenz
+ PDF Chat	Faster randomized block sparse Kaczmarz by averaging	2022	Lionel Tondji Dirk A. Lorenz
+ PDF Chat	Extended randomized Kaczmarz method for sparse least squares and impulsive noise problems	2022	Frank Schöpfer Dirk A. Lorenz Lionel Tondji Maximilian Winkler
+	Extended Randomized Kaczmarz Method for Sparse Least Squares and Impulsive Noise Problems	2022	Frank Schöpfer Dirk A. Lorenz Lionel Tondji Maximilian Winkler
+	Faster Randomized Block Sparse Kaczmarz by Averaging	2022	Lionel Tondji Dirk A. Lorenz
+	Variance Reduction in Deep Learning: More Momentum is All You Need	2021	Lionel Tondji Sergii Kashubin Moustapha Cissé
+ PDF Chat	Variance Reduction in Deep Learning: More Momentum is All You Need	2021	Lionel Tondji Sergii Kashubin Moustapha Cissé
+	Variance Reduction in Deep Learning: More Momentum is All You Need	2021	Lionel Tondji Sergii Kashubin Moustapha Cissé

Common Coauthors

Coauthor	Papers Together
Dirk A. Lorenz	11
Ion Necoara	3
Sergii Kashubin	3
Moustapha Cissé	3
Maximilian Winkler	2
Frank Schöpfer	2
Felix Schneppe	2
Idriss Tondji	2

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	A Randomized Kaczmarz Algorithm with Exponential Convergence	2008	Thomas Strohmer Roman Vershynin	6
+ PDF Chat	Randomized Extended Kaczmarz for Solving Least Squares	2013	Anastasios Zouzias Nikolaos M. Freris	5
+ PDF Chat	Linear convergence of the randomized sparse Kaczmarz method	2018	Frank Schöpfer Dirk A. Lorenz	5
+	Randomized Extended Average Block Kaczmarz for Solving Least Squares	2020	Kui Du Wutao Si Xiaohui Sun	5
+	Paved with good intentions: Analysis of a randomized block Kaczmarz method	2013	Deanna Needell Joel A. Tropp	5
+ PDF Chat	The Linearized Bregman Method via Split Feasibility Problems: Analysis and Generalizations	2014	Dirk A. Lorenz Frank Schöpfer Stephan Wenger	5
+ PDF Chat	Efficiency of Coordinate Descent Methods on Huge-Scale Optimization Problems	2012	Yu. Nesterov	4
+	Analysis and Generalizations of the Linearized Bregman Method	2010	Wotao Yin	4
+ PDF Chat	Preasymptotic convergence of randomized Kaczmarz method	2017	Yuling Jiao Bangti Jin Xiliang Lu	4
+ PDF Chat	Faster Randomized Block Kaczmarz Algorithms	2019	Ion Necoara	4
+ PDF Chat	Extended randomized Kaczmarz method for sparse least squares and impulsive noise problems	2022	Frank Schöpfer Dirk A. Lorenz Lionel Tondji Maximilian Winkler	4
+ PDF Chat	A sparse Kaczmarz solver and a linearized Bregman method for online compressed sensing	2014	Dirk A. Lorenz Stephan Wenger Frank Schöpfer Marcus Magnor	3
+ PDF Chat	Faster randomized block sparse Kaczmarz by averaging	2022	Lionel Tondji Dirk A. Lorenz	3
+ PDF Chat	Randomized Kaczmarz with averaging	2020	Jacob D. Moorman Thomas K. Tu Denali Molitor Deanna Needell	3
+	Parallel Random Coordinate Descent Method for Composite Minimization: Convergence Analysis and Error Bounds	2016	Ion Necoara Dragos Clipici	3
+	Convergence of the linearized Bregman iteration for ℓ₁-norm minimization	2009	Jian‐Feng Cai Stanley Osher Zuowei Shen	2
+	Compressed sensing	2006	David L. Donoho	2
+	Robust Stochastic Approximation Approach to Stochastic Programming	2009	Arkadi Nemirovski Anatoli Juditsky Guanghui Lan Alexander Shapiro	2
+ PDF Chat	The randomized Kaczmarz method with mismatched adjoint	2018	Dirk A. Lorenz Sean Rose Frank Schöpfer	2
+	Iterative Methods for Linear Systems	2014		2
+ PDF Chat	IMPROVED ANALYSIS OF THE SUBSAMPLED RANDOMIZED HADAMARD TRANSFORM	2011	Joel A. Tropp	2
+	Accelerated, Parallel, and Proximal Coordinate Descent	2015	Olivier Fercoq Peter Richtárik	2
+	On stochastic Kaczmarz type methods for solving large scale systems of ill-posed equations	2021	Joel C. Rabelo Yuri F. Saporito Antonio Leitão	2
+ PDF Chat	ImageNet Large Scale Visual Recognition Challenge	2015	Olga Russakovsky Jia Deng Hao Su Jonathan Krause Sanjeev Satheesh Sean Ma Zhiheng Huang Andrej Karpathy Aditya Khosla Michael S. Bernstein	1
+ PDF Chat	Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization	2010	Benjamin Recht Maryam Fazel Pablo A. Parrilo	1
+	None	1998	Claude Brezinski Michela Redivo‐Zaglia	1
+ PDF Chat	Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information	2006	Emmanuel J. Candès Justin Romberg Terence Tao	1
+	Random Gradient-Free Minimization of Convex Functions	2015	Yurii Nesterov Vladimir Spokoiny	1
+	Sparse nonnegative solution of underdetermined linear equations by linear programming	2005	David L. Donoho Jared Tanner	1
+ PDF Chat	Randomized Methods for Linear Constraints: Convergence Rates and Conditioning	2010	D. Leventhal Adrian S. Lewis	1
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	1
+	Methods of conjugate gradients for solving linear systems	1952	Magnus R. Hestenes Eduard Stiefel	1
+	Wide Residual Networks	2016	Sergey Zagoruyko Nikos Komodakis	1
+	Linear Convergence of Descent Methods for the Unconstrained Minimization of Restricted Strongly Convex Functions	2016	Frank Schöpfer	1
+	Restarting accelerated gradient methods with a rough strong convexity estimate	2016	Olivier Fercoq Zheng Qu	1
+	Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite-Sum Structure	2016	Alberto Bietti Julien Mairal	1
+ PDF Chat	Convergence rates for Kaczmarz-type algorithms	2017	Constantin Popa	1
+	YellowFin and the Art of Momentum Tuning	2017	Jian Zhang Ioannis Mitliagkas	1
+ PDF Chat	Stochastic Mirror Descent Dynamics and Their Convergence in Monotone Variational Inequalities	2018	Panayotis Mertikopoulos Mathias Staudigl	1
+	mixup: Beyond Empirical Risk Minimization	2017	Hongyi Zhang Moustapha Cissé Yann Dauphin David López-Paz	1
+	On Greedy Randomized Kaczmarz Method for Solving Large Sparse Linear Systems	2018	Zhong‐Zhi Bai Wen-Ting Wu	1
+	Group Normalization	2018	Yuxin Wu Kaiming He	1
+	Decoupled Weight Decay Regularization	2017	Ilya Loshchilov Frank Hutter	1
+	Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift	2015	Sergey Ioffe Christian Szegedy	1
+	SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives	2014	Aaron Defazio Francis Bach Simon Lacoste-Julien	1
+ PDF Chat	In-Datacenter Performance Analysis of a Tensor Processing Unit	2017	Norman P. Jouppi Cliff Young Nishant Patil David A. Patterson Gaurav Agrawal Raminder Bajwa S. C. Bates Suresh Bhatia Nan Boden Al Borchers	1
+	SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient	2017	Lam M. Nguyen Jie Liu Katya Scheinberg Martin Takáč	1
+ PDF Chat	Optimization of Convex Functions with Random Pursuit	2013	Sebastian U. Stich Christian L. Müller Bernd Gärtner	1
+ PDF Chat	Minimizing finite sums with the stochastic average gradient	2016	Mark Schmidt Nicolas Le Roux Francis Bach	1
+	Optimization Methods for Large-Scale Machine Learning	2018	Léon Bottou Frank E. Curtis Jorge Nocedal	1