Mojmír Mutný

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All published works

Action	Title	Year	Authors
+ PDF Chat	Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design	2024	Melis İlayda Bal Pier Giuseppe Sessa Mojmír Mutný Andreas Krause
+ PDF Chat	Transition Constrained Bayesian Optimization via Markov Decision Processes	2024	Jose Pablo Folch Calvin Tsay Robert M Lee Behrang Shafei Weronika Ormaniec Andreas Krause Mark van der Wilk Ruth Misener Mojmír Mutný
+	Submodular Reinforcement Learning	2023	Manish Prajapat Mojmír Mutný Melanie N. Zeilinger Andreas Krause
+	Likelihood Ratio Confidence Sets for Sequential Decision Making	2023	Nicolas Emmenegger Mojmír Mutný Andreas Krause
+ PDF Chat	Tuning particle accelerators with safety constraints using Bayesian optimization	2022	Johannes Kirschner Mojmír Mutný Andreas Krause J. Coello de Portugal Nicole Hiller J. Snuverink
+	Experimental Design for Linear Functionals in Reproducing Kernel Hilbert Spaces	2022	Mojmír Mutný Andreas Krause
+	Active Exploration via Experiment Design in Markov Chains	2022	Mojmír Mutný Tadeusz J. Janik Andreas Krause
+	Sensing Cox Processes via Posterior Sampling and Positive Bases.	2021	Mojmír Mutný Andreas Krause
+	Data Summarization via Bilevel Optimization	2021	Zalán Borsos Mojmír Mutný Marco Tagliasacchi Andreas Krause
+	Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processes	2021	Elvis Nava Mojmír Mutný Andreas Krause
+	Sensing Cox Processes via Posterior Sampling and Positive Bases	2021	Mojmír Mutný Andreas Krause
+	Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback	2021	Marc Jourdan Mojmír Mutný Johannes Kirschner Andreas Krause
+	Learning Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory.	2020	Lenart Treven Sebastian Curi Mojmír Mutný Andreas Krause
+	Coresets via Bilevel Optimization for Continual Learning and Streaming	2020	Zalán Borsos Mojmír Mutný Andreas Krause
+	Coresets via Bilevel Optimization for Continual Learning and Streaming	2020	Zalán Borsos Mojmír Mutný Andreas Krause
+	Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling.	2020	Mojmír Mutný Michał Dereziński Andreas Krause
+	Learning Stabilizing Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory	2020	Lenart Treven Sebastian Curi Mojmír Mutný Andreas Krause
+	Convergence Analysis of the Randomized Newton Method with Determinantal Sampling.	2019	Mojmír Mutný Michał Dereziński Andreas Krause
+	Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling	2019	Mojmír Mutný Michał Dereziński Andreas Krause
+	Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces	2019	Johannes Kirschner Mojmír Mutný Nicole Hiller R. Ischebeck Andreas Krause
+	Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling	2019	Mojmír Mutný Michał Dereziński Andreas Krause
+	Parallel Stochastic Newton Method	2017	Mojmír Mutný Peter Richtárik
+	Parallel Stochastic Newton Method	2017	Mojmír Mutný Peter Richtárik
+	Stochastic Second-Order Optimization via von Neumann Series	2016	Mojmír Mutný
+	Learning the Correction for Multi-Path Deviations in Time-of-Flight Cameras	2015	Mojmír Mutný Rahul Nair Jens-Malte Gottfried
+	Learning the Correction for Multi-Path Deviations in Time-of-Flight Cameras	2015	Mojmír Mutný R. Nair Jens-Malte Gottfried

Common Coauthors

Coauthor	Papers Together
Andreas Krause	21
Michał Dereziński	4
Zalán Borsos	3
Johannes Kirschner	3
Nicole Hiller	2
Jens-Malte Gottfried	2
Peter Richtárik	2
Sebastian Curi	2
Lenart Treven	2
Marco Tagliasacchi	1
Weronika Ormaniec	1
Pier Giuseppe Sessa	1
J. Coello de Portugal	1
Melanie N. Zeilinger	1
Tadeusz J. Janik	1
Manish Prajapat	1
Marc Jourdan	1
Elvis Nava	1
Behrang Shafei	1
Rahul Nair	1
Ruth Misener	1
Robert M Lee	1
Calvin Tsay	1
Jose Pablo Folch	1
J. Snuverink	1
R. Nair	1
Nicolas Emmenegger	1
R. Ischebeck	1
Mark van der Wilk	1
Melis İlayda Bal	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	On the limited memory BFGS method for large scale optimization	1989	Cheng‐Di Dong Jorge Nocedal	3
+	Sub-Sampled Newton Methods II: Local Convergence Rates	2016	Farbod Roosta-Khorasani Michael W. Mahoney	3
+	Sub-Sampled Newton Methods I: Globally Convergent Algorithms	2016	Farbod Roosta-Khorasani Michael W. Mahoney	3
+	High-Dimensional Probability: An Introduction with Applications in Data Science	2018	Roman Vershynin	2
+	Automated Scalable Bayesian Inference via Hilbert Coresets	2019	Trevor Campbell Tamara Broderick	2
+	Continual learning with tiny episodic memories	2019	Arslan Chaudhry Marcus Rohrbach Mohamed Elhoseiny Thalaiyasingam Ajanthan Puneet K. Dokania Philip H. S. Torr Marc’Aurelio Ranzato	2
+	Functional Regularisation for Continual Learning with Gaussian Processes	2020	Michalis K. Titsias Jonathan Schwarz Alexander Matthews Razvan Pascanu Yee Whye Teh	2
+	Primal-dual rates and certificates	2016	Celestine Dünner Simone Forte Martin Takáč Martin Jaggi	2
+	An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks	2014	Ian Goodfellow Mehdi Mirza Xiao Da Aaron Courville Yoshua Bengio	2
+ PDF Chat	Task-Free Continual Learning	2019	Rahaf Aljundi Klaas Kelchtermans Tinne Tuytelaars	2
+	Regression Shrinkage and Selection Via the Lasso	1996	Robert Tibshirani	2
+ PDF Chat	iCaRL: Incremental Classifier and Representation Learning	2017	Sylvestre-Alvise Rebuffi Alexander Kolesnikov Georg Sperl Christoph H. Lampert	2
+	Newton Sketch: A Linear-time Optimization Algorithm with Linear-Quadratic Convergence	2015	Mert Pilancı Martin J. Wainwright	2
+ PDF Chat	Coordinate descent with arbitrary sampling II: expected separable overapproximation	2016	Zheng Qu Peter Richtárik	2
+	Overcoming catastrophic forgetting in neural networks	2017	James Kirkpatrick Razvan Pascanu Neil C. Rabinowitz Joel Veness Guillaume Desjardins Andrei A. Rusu Kieran Milan John Quan Tiago Ramalho Agnieszka Grabska‐Barwińska	2
+ PDF Chat	On optimal probabilities in stochastic coordinate descent methods	2015	Peter Richtárik Martin Takáč	2
+	Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences	2018	Motonobu Kanagawa Philipp Hennig Dino Sejdinović Bharath K. Sriperumbudur	2
+	Coresets for Scalable Bayesian Logistic Regression	2016	Jonathan H. Huggins Trevor Campbell Tamara Broderick	2
+	A unified framework for approximating and clustering data	2011	Dan Feldman Michael Langberg	2
+	A System-Level Approach to Controller Synthesis	2019	Yuh-Shyang Wang Nikolai Matni John C. Doyle	2
+ PDF Chat	On the Sample Complexity of the Linear Quadratic Regulator	2019	Sarah Dean Horia Mania Nikolai Matni Benjamin Recht Stephen Tu	2
+	BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning	2019	Andreas Kirsch Joost van Amersfoort Yarin Gal	2
+ PDF Chat	Residuals and Influence in Regression	1984	Robert F. Ling R. Dennis Cook Sanford Weisberg	2
+ PDF Chat	Memory Efficient Experience Replay for Streaming Learning	2019	Tyler L. Hayes Nathan D. Cahill Christopher Kanan	2
+ PDF Chat	Information Consistency of Nonparametric Gaussian Process Methods	2008	Matthias Seeger Sham M. Kakade Dean P. Foster	2
+	A new identity for resolvents of matrices	2013	Michael Gil'	2
+	Variational continual learning	2017	Cuong V. Nguyen Yingzhen Li Thang D. Bui Richard E. Turner	2
+ PDF Chat	Random sampling with a reservoir	1985	Jeffrey Scott Vitter	2
+	SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization	2015	Zheng Qu Peter Richtárik Martin Takáč Olivier Fercoq	2
+ PDF Chat	A tail inequality for quadratic forms of subgaussian random vectors	2012	Daniel Hsu Sham M. Kakade Tong Zhang	2
+	Singular vector autoregressions with deterministic terms: Strong consistency and lag order determination	2008	Bent Nielsen	2
+	Understanding Black-box Predictions via Influence Functions	2017	Pang Wei Koh Percy Liang	2
+	Continual Learning with Deep Generative Replay	2017	Hanul Shin Jung Kwon Lee Jaehong Kim Jiwon Kim	2
+	INCONSISTENT VAR REGRESSION WITH COMMON EXPLOSIVE ROOTS	2013	Peter C.B. Phillips Tassos Magdalinos	2
+	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks	2017	Chelsea Finn Pieter Abbeel Sergey Levine	2
+	Accelerated, Parallel, and Proximal Coordinate Descent	2015	Olivier Fercoq Peter Richtárik	1
+	Spatial and Spatio-Temporal Log-Gaussian Cox Processes: Extending the Geostatistical Paradigm	2013	Peter J. Diggle Paula Moraga Barry Rowlingson Benjamín M. Taylor	1
+ PDF Chat	Multivariate Nonnegative Quadratic Mappings	2004	Zhi‐Quan Luo J.F. Sturm Shuzhong Zhang	1
+	Tridiagonal Toeplitz matrices: properties and novel applications	2012	Silvia Noschese L. Pasquini Lothar Reichel	1
+	Random Fields and Geometry	2007	Robert J. Adler Jonathan Taylor	1
+	The CoMirror algorithm for solving nonsmooth constrained convex problems	2010	Amir Beck Aharon Ben‐Tal Nili Guttmann‐Beck Luba Tetruashvili	1
+ PDF Chat	The Why and How of Nonnegative Matrix Factorization	2014	Nicolas Gillis	1
+	The coincidence approach to stochastic point processes	1975	Odile Macchi	1
+ PDF Chat	CUR matrix decompositions for improved data analysis	2009	Michael W. Mahoney Petros Drineas	1
+	Descent approaches for quadratic bilevel programming	1994	L. N. Vicente Gilles Savard Joaquím J. Júdice	1
+	Randomized Dual Coordinate Ascent with Arbitrary Sampling	2014	Zheng Qu Peter Richtárik Tong Zhang	1
+	Fixed Rank Kriging for Very Large Spatial Data Sets	2008	Noel Cressie Gardar Johannesson	1
+	Online Least Squares Estimation with Self-Normalized Processes: An Application to Bandit Problems	2011	Yasin Abbasi-Yadkori Dávid Pál Csaba Szepesvári	1
+	Sequential Quadratic Programming	1995	Paul T. Boggs Jon W. Tolle	1
+ PDF Chat	Global convergence rate analysis of unconstrained optimization methods based on probabilistic models	2017	Coralia Cartis Katya Scheinberg	1