Malik Tiomoko

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All published works

Action	Title	Year	Authors
+ PDF Chat	User-friendly Foundation Model Adapters for Multivariate Time Series Classification	2024	Vasilii Feofanov Romain Ilbert Malik Tiomoko Themis Palpanas Ievgen Redko
+	Random matrix theory improved Fréchet mean of symmetric positive definite matrices	2024	Florent Bouchard Ammar Mian Malik Tiomoko Guillaume Ginolhac Frédéric Pascal
+ PDF Chat	Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting	2024	Romain Ilbert Malik Tiomoko Cosme Louart Ambroise Odonnat Vasilii Feofanov Themis Palpanas Ievgen Redko
+	Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption	2023	Vasilii Feofanov Malik Tiomoko Aladin Virmaux
+	Multi-task learning on the edge: cost-efficiency and theoretical optimality	2021	Sami Fakhry Romain Couillet Malik Tiomoko
+	PCA-based Multi Task Learning: a Random Matrix Approach	2021	Malik Tiomoko Romain Couillet Frédéric Pascal
+ PDF Chat	Random matrix improved covariance estimation for a large class of metrics*	2020	Malik Tiomoko Florent Bouchard Guillaume Ginolhac Romain Couillet
+	Large Dimensional Analysis and Improvement of Multi Task Learning	2020	Malik Tiomoko Romain Couillet Hafiz Tiomoko
+ PDF Chat	Estimation of Covariance Matrix Distances in the High Dimension Low Sample Size Regime	2019	Malik Tiomoko Romain Couillet
+ PDF Chat	Random Matrix-Improved Estimation of the Wasserstein Distance between two Centered Gaussian Distributions	2019	Malik Tiomoko Romain Couillet
+	Random matrix-improved estimation of covariance matrix distances	2019	Romain Couillet Malik Tiomoko Steeve Zozor Éric Moisan
+ PDF Chat	Improved Estimation of the Distance between Covariance Matrices	2019	Malik Tiomoko Romain Couillet Éric Moisan Steeve Zozor
+	Random Matrix-Improved Estimation of the Wasserstein Distance between two Centered Gaussian Distributions	2019	Malik Tiomoko Romain Couillet
+	Random Matrix-Improved Estimation of the Wasserstein Distance between two Centered Gaussian Distributions	2019	Malik Tiomoko Romain Couillet
+	Random matrix-improved estimation of covariance matrix distances	2018	Romain Couillet Malik Tiomoko Steeve Zozor Éric Moisan
+	Random matrix-improved estimation of covariance matrix distances	2018	Romain Couillet Malik Tiomoko Steeve Zozor Éric Moisan

Common Coauthors

Coauthor	Papers Together
Romain Couillet	12
Steeve Zozor	4
Éric Moisan	4
Vasilii Feofanov	3
Romain Ilbert	2
Ievgen Redko	2
Themis Palpanas	2
Guillaume Ginolhac	2
Florent Bouchard	2
Fréderic Pascal	2
Ambroise Odonnat	1
Aladin Virmaux	1
Ammar Mian	1
Cosme Louart	1
Hafiz Tiomoko	1
Sami Fakhry	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	On the Empirical Distribution of Eigenvalues of a Class of Large Dimensional Random Matrices	1995	Jack W. Silverstein Zhidong Bai	6
+	On the Asymptotic Behavior of the Sample Estimates of Eigenvalues and Eigenvectors of Covariance Matrices	2008	Xavier Mestre	5
+	Random matrix-improved estimation of covariance matrix distances	2018	Romain Couillet Malik Tiomoko Steeve Zozor Éric Moisan	4
+ PDF Chat	A well-conditioned estimator for large-dimensional covariance matrices	2003	Olivier Ledoit Michael Wolf	3
+ PDF Chat	Numerical implementation of the QuEST function	2017	Olivier Ledoit Michael Wolf	3
+	DISTRIBUTION OF EIGENVALUES FOR SOME SETS OF RANDOM MATRICES	1967	V A Marčenko L. А. Pastur	3
+ PDF Chat	Analysis of the limiting spectral measure of large random matrices of the separable covariance type	2014	Romain Couillet Walid Hachem	2
+	Spectrum estimation: A unified framework for covariance matrix estimation and PCA in large dimensions	2015	Olivier Ledoit Michael Wolf	2
+ PDF Chat	Graph analysis of functional brain networks: practical issues in translational neuroscience	2014	Fabrizio De Vico Fallani Jonas Richiardi Mario Chávez Sophie Achard	2
+ PDF Chat	Eigen-Inference for Energy Estimation of Multiple Sources	2011	Romain Couillet Jack W. Silverstein Zhidong Bai Mérouane Debbah	2
+	On a measure of divergence between two statistical populations defined by their probability distributions	1943	Ayan Bhattacharyya	2
+ PDF Chat	Optimal estimation of a large-dimensional covariance matrix under Stein’s loss	2018	Olivier Ledoit Michael Wolf	2
+	Divergence measures for statistical data processing—An annotated bibliography	2012	Michèle Basseville	2
+	Kernel spectral clustering of large dimensional data	2016	Romain Couillet Florent Benaych-Georges	2
+	The Dilogarithm Function	2007	Don Zagier	2
+	Random matrix-improved estimation of covariance matrix distances	2019	Romain Couillet Malik Tiomoko Steeve Zozor Éric Moisan	2
+	Improved Estimation of Eigenvalues and Eigenvectors of Covariance Matrices Using Their Sample Estimates	2008	Xavier Mestre	2
+	Fundamentals of Complex Analysis with Applications to Engineering and Science	2003	Edward B. Saff Arthur David Snider	2
+	Optimization Algorithms on Matrix Manifolds	2007	P.-A. Absil Robert Mahony Rodolphe Sepulchre	2
+	Analysis of the Limiting Spectral Distribution of Large Dimensional Random Matrices	1995	Jack W. Silverstein Sang Il Choi	2
+	On the Limiting Empirical Distribution Function of the Eigenvalues of a Multivariate <i>F</i> Matrix	1988	Zhidong Bai Yanqing Yin P. R. Krishnaiah	2
+ PDF Chat	Random matrix improved covariance estimation for a large class of metrics*	2020	Malik Tiomoko Florent Bouchard Guillaume Ginolhac Romain Couillet	2
+	Fisher information distance: A geometrical reading	2014	Sueli I. R. Costa Sandra A. Santos João E. Strapasson	2
+ PDF Chat	On the Translocation of Masses	2006	L. V. Kantorovich	2
+ PDF Chat	Computational Optimal Transport	2019	Gabriel Peyré Marco Cuturi	2
+	The Limiting Eigenvalue Distribution of a Multivariate <i>F</i> Matrix	1985	Jack W. Silverstein	2
+	Minimum variance portfolio optimization in the spiked covariance model	2015	Liusha Yang Romain Couillet Matthew R. McKay	1
+	Unsupervised Domain Adaptation with Residual Transfer Networks	2016	Mingsheng Long Zhu Han Jianmin Wang Michael I. Jordan	1
+	BANDING SAMPLE AUTOCOVARIANCE MATRICES OF STATIONARY PROCESSES	2009	Wei Biao Wu Mohsen Pourahmadi	1
+ PDF Chat	Challenges and Opportunities in Edge Computing	2016	Blesson Varghese Nan Wang Sakil Barbhuiya Peter Kilpatrick Dimitrios S. Nikolopoulos	1
+	CLT for eigenvalue statistics of large-dimensional general Fisher matrices with applications	2017	Shurong Zheng Zhidong Bai Jianfeng Yao	1
+	An Overview of Multi-Task Learning in Deep Neural Networks	2017	Sebastian Ruder	1
+ PDF Chat	Deep Hashing Network for Unsupervised Domain Adaptation	2017	Hemanth Venkateswara José Eusébio Shayok Chakraborty Sethuraman Panchanathan	1
+ PDF Chat	A Survey on Deep Transfer Learning	2018	Chuanqi Tan Fuchun Sun Tao Kong Wenchang Zhang Chao Yang Chunfang Liu	1
+	Unsupervised and Supervised Principal Component Analysis: Tutorial.	2019	Benyamin Ghojogh Mark Crowley	1
+	Efficient Learning of Domain-invariant Image Representations	2013	Judy Hoffman Erik Rodner Jeff Donahue Trevor Darrell Kate Saenko	1
+ PDF Chat	A CLT for information-theoretic statistics of Gram random matrices with a given variance profile	2008	Walid Hachem Philippe Loubaton Jamal Najım	1
+ PDF Chat	On the distribution of the largest eigenvalue in principal components analysis	2001	Iain M. Johnstone	1
+ PDF Chat	Maximum Classifier Discrepancy for Unsupervised Domain Adaptation	2018	Kuniaki Saito Kohei Watanabe Yoshitaka Ushiku Tatsuya Harada	1
+	Sparse coding for multitask and transfer learning	2012	Andreas Maurer Massi Pontil Bernardino Romera‐Paredes	1
+	Positive definite matrices and the S-divergence	2015	Suvrit Sra	1
+ PDF Chat	Semi-supervised Multitask Learning for Sequence Labeling	2017	Marek Rei	1
+	Energy and Policy Considerations for Deep Learning in NLP	2019	Emma Strubell Ananya Ganesh Andrew McCallum	1
+	A convex formulation for learning task relationships in multi-task learning	2010	Yu Zhang Dit‐Yan Yeung	1
+	Normalization: A Preprocessing Stage	2015	S. Gopal Krishna Patro Kishore Kumar Sahu	1
+	Quantifying the Carbon Emissions of Machine Learning	2019	Alexandre Lacoste Alexandra Sasha Luccioni Victor Schmidt Thomas Dandres	1
+ PDF Chat	Random Matrix-Improved Estimation of the Wasserstein Distance between two Centered Gaussian Distributions	2019	Malik Tiomoko Romain Couillet	1
+	Perturbed Laguerre Unitary Ensembles, Painlevé V and Information Theory	2013	Estelle Basor Yang Chen Matthew R. McKay	1
+ PDF Chat	Asymptotic Bayes Risk for Gaussian Mixture in a Semi-Supervised Setting	2019	Marc Lelarge Léo Miolane	1
+	To transfer or not to transfer	2005	Michael T. Rosenstein	1