Maxim Raginsky

Orcid: 0000-0002-5586-9219

Affiliations:
  • University of Illinois at Urbana-Champaign, Coordinated Science Laboratory, Urbana, IL, USA
  • Duke University, Department of Electrical and Computer Engineering, Durham, NC, USA
  • Northwestern University, Department of Electrical and Computer Engineering, Evanston, IL, USA (PhD 202)


According to our database1, Maxim Raginsky authored at least 123 papers between 2003 and 2024.

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Bibliography

2024
Revisiting Stochastic Realization Theory using Functional Itô Calculus.
CoRR, 2024

Rademacher Complexity of Neural ODEs via Chen-Fliess Series.
CoRR, 2024

Transformer-Based Models Are Not Yet Perfect At Learning to Emulate Structural Recursion.
CoRR, 2024

2023
Partially Observed Discrete-Time Risk-Sensitive Mean Field Games.
Dyn. Games Appl., September, 2023

Variational Principles for Mirror Descent and Mirror Langevin Dynamics.
IEEE Control. Syst. Lett., 2023

Generalization Bounds: Perspectives from Information Theory and PAC-Bayes.
CoRR, 2023

Can Transformers Learn to Solve Problems Recursively?
CoRR, 2023

A Chain Rule for the Expected Suprema of Bernoulli Processes.
CoRR, 2023

A unified framework for information-theoretic generalization bounds.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Nonlinear Controllability and Function Representation by Neural Stochastic Differential Equations.
Proceedings of the Learning for Dynamics and Control Conference, 2023

Majorizing Measures, Codes, and Information.
Proceedings of the IEEE International Symposium on Information Theory, 2023

A Constructive Approach to Function Realization by Neural Stochastic Differential Equations.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022
Minimum Excess Risk in Bayesian Learning.
IEEE Trans. Inf. Theory, 2022

Robustness to incorrect models and data-driven learning in average-cost optimal stochastic control.
Autom., 2022

Input-to-State Stable Neural Ordinary Differential Equations with Applications to Transient Modeling of Circuits.
Proceedings of the Learning for Dynamics and Control Conference, 2022

Fitting an immersed submanifold to data via Sussmann's orbit theorem.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021
Information-theoretic generalization bounds for black-box learning algorithms.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Neural Networks for Transient Modeling of Circuits : Invited Paper.
Proceedings of the 3rd ACM/IEEE Workshop on Machine Learning for CAD, 2021

Learning Recurrent Neural Net Models of Nonlinear Systems.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Sampling, variational Bayesian inference, and conditioned stochastic differential equations.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

EE-Grad: Exploration and Exploitation for Cost-Efficient Mini-Batch SGD.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020
Channel Polarization Through the Lens of Blackwell Measures.
IEEE Trans. Inf. Theory, 2020

Approximate Markov-Nash Equilibria for Discrete-Time Risk-Sensitive Mean-Field Games.
Math. Oper. Res., 2020

A mean-field theory of lazy training in two-layer neural nets: entropic regularization and controlled McKean-Vlasov dynamics.
CoRR, 2020

Model-Augmented Conditional Mutual Information Estimation for Feature Selection.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Universal Simulation of Stable Dynamical Systems by Recurrent Neural Nets.
Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

2019
Learning Finite-Dimensional Coding Schemes with Nonlinear Reconstruction Maps.
SIAM J. Math. Data Sci., 2019

Approximate Nash Equilibria in Partially Observed Stochastic Games with Mean-Field Interactions.
Math. Oper. Res., 2019

Model-Augmented Nearest-Neighbor Estimation of Conditional Mutual Information for Feature Selection.
CoRR, 2019

Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit.
CoRR, 2019

Universal Approximation of Input-Output Maps by Temporal Convolutional Nets.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Theoretical guarantees for sampling and inference in generative models with latent diffusions.
Proceedings of the Conference on Learning Theory, 2019

Linear Noisy Networks with Stochastic Components.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Robustness to Incorrect Models in Average-Cost Optimal Stochastic Control.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018
Sequential Empirical Coordination Under an Output Entropy Constraint.
IEEE Trans. Inf. Theory, 2018

Coordinate Dual Averaging for Decentralized Online Optimization With Nonseparable Global Objectives.
IEEE Trans. Control. Netw. Syst., 2018

Markov-Nash Equilibria in Mean-Field Games with Discounted Cost.
SIAM J. Control. Optim., 2018

Discrete-time Risk-sensitive Mean-field Games.
CoRR, 2018

Minimax Statistical Learning with Wasserstein distances.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Universal Compression, List Decoding, and Logarithmic Loss.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

Stochastic modeling of air electrostatic discharge parameters.
Proceedings of the IEEE International Reliability Physics Symposium, 2018

Local Optimality and Generalization Guarantees for the Langevin Algorithm via Empirical Metastability.
Proceedings of the Conference On Learning Theory, 2018

Sequential prediction with coded side information under logarithmic loss.
Proceedings of the Algorithmic Learning Theory, 2018

2017
Information-Theoretic Lower Bounds for Distributed Function Computation.
IEEE Trans. Inf. Theory, 2017

Information-Theoretic Lower Bounds on Bayes Risk in Decentralized Estimation.
IEEE Trans. Inf. Theory, 2017

Stochastic Dual Averaging for Decentralized Online Optimization on Time-Varying Communication Graphs.
IEEE Trans. Autom. Control., 2017

Minimax Statistical Learning and Domain Adaptation with Wasserstein Distances.
CoRR, 2017

Cost-Performance Tradeoffs in Fusing Unreliable Computational Units.
CoRR, 2017

EE-Grad: Exploration and Exploitation for Cost-Efficient Mini-Batch SGD.
CoRR, 2017

Information-theoretic analysis of generalization capability of learning algorithms.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Universal lossy compression under logarithmic loss.
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis.
Proceedings of the 30th Conference on Learning Theory, 2017

Rationally inattentive Markov decision processes over a finite horizon.
Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

2016
Strong Data Processing Inequalities and Φ-Sobolev Inequalities for Discrete Channels.
IEEE Trans. Inf. Theory, 2016

Rationally Inattentive Control of Markov Processes.
SIAM J. Control. Optim., 2016

Online Optimization Under Adversarial Perturbations.
IEEE J. Sel. Top. Signal Process., 2016

Online Discrete Optimization in Social Networks in the Presence of Knightian Uncertainty.
Oper. Res., 2016

Concentration of measure without independence: a unified approach via the martingale method.
CoRR, 2016

Active object detection on graphs via locally informative trees.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Information-theoretic analysis of stability and bias of learning algorithms.
Proceedings of the 2016 IEEE Information Theory Workshop, 2016

Channel polarization and Blackwell measures.
Proceedings of the IEEE International Symposium on Information Theory, 2016

Regret minimization algorithms for single-controller zero-sum stochastic games.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Cost-performance tradeoffs in unreliable computation architectures.
Proceedings of the 50th Asilomar Conference on Signals, Systems and Computers, 2016

2015
Poisson's Equation in Nonlinear Filtering.
SIAM J. Control. Optim., 2015

Concentration of Measure Inequalities and Their Communication and Information-Theoretic Applications.
CoRR, 2015

Converses for distributed estimation via strong data processing inequalities.
Proceedings of the IEEE International Symposium on Information Theory, 2015

On MMSE estimation from quantized observations in the nonasymptotic regime.
Proceedings of the IEEE International Symposium on Information Theory, 2015

Decentralized online optimization with global objectives and local communication.
Proceedings of the American Control Conference, 2015

2014
Online Markov Decision Processes With Kullback-Leibler Control Cost.
IEEE Trans. Autom. Control., 2014

A new information-theoretic lower bound for distributed function computation.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Online discrete optimization in social networks.
Proceedings of the American Control Conference, 2014

From minimax value to low-regret algorithms for online Markov decision processes.
Proceedings of the American Control Conference, 2014

2013
Empirical Processes, Typical Sequences, and Coordinated Actions in Standard Borel Spaces.
IEEE Trans. Inf. Theory, 2013

Concentration of Measure Inequalities in Information Theory, Communications, and Coding.
Found. Trends Commun. Inf. Theory, 2013

Relax but stay in control: from value to algorithms for online Markov decision processes.
CoRR, 2013

Learning joint quantizers for reconstruction and prediction.
Proceedings of the 2013 IEEE Information Theory Workshop, 2013

Refined bounds on the empirical distribution of good channel codes via concentration inequalities.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

Logarithmic Sobolev inequalities and strong data processing theorems for discrete channels.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

Rational inattention in scalar LQG control.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Rational inattention in controlled Markov processes.
Proceedings of the American Control Conference, 2013

2012
Sequential Anomaly Detection in the Presence of Noise and Limited Feedback.
IEEE Trans. Inf. Theory, 2012

Target detection performance bounds in compressive imaging.
EURASIP J. Adv. Signal Process., 2012

Continuous-time stochastic Mirror Descent on a network: Variance reduction, consensus, convergence.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

2011
Performance Bounds for Expander-Based Compressed Sensing in Poisson Noise.
IEEE Trans. Signal Process., 2011

Information-Based Complexity, Feedback and Dynamics in Convex Programming.
IEEE Trans. Inf. Theory, 2011

Lower Bounds for Passive and Active Learning.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Shannon meets Blackwell and Le Cam: Channels, codes, and statistical experiments.
Proceedings of the 2011 IEEE International Symposium on Information Theory Proceedings, 2011

Decentralized Online Convex Programming with local information.
Proceedings of the American Control Conference, 2011

Directed information and pearl's causal calculus.
Proceedings of the 49th Annual Allerton Conference on Communication, 2011

2010
Compressed sensing performance bounds under Poisson noise.
IEEE Trans. Signal Process., 2010

Multiscale Photon-Limited Spectral Image Reconstruction.
SIAM J. Imaging Sci., 2010

Information-based complexity, feedback and dynamics in sequential convex programming
CoRR, 2010

Empirical processes and typical sequences.
Proceedings of the IEEE International Symposium on Information Theory, 2010

Mutual information saddle points in channels of exponential family type.
Proceedings of the IEEE International Symposium on Information Theory, 2010

Hyperspectral target detection from incoherent projections: Nonequiprobable targets and inhomogeneous SNR.
Proceedings of the International Conference on Image Processing, 2010

Hyperspectral target detection from incoherent projections.
Proceedings of the IEEE International Conference on Acoustics, 2010

Fishing in Poisson streams: Focusing on the whales, ignoring the minnows.
Proceedings of the 44th Annual Conference on Information Sciences and Systems, 2010

Online Convex Programming and regularization in adaptive control.
Proceedings of the 49th IEEE Conference on Decision and Control, 2010

Divergence-based characterization of fundamental limitations of adaptive dynamical systems.
Proceedings of the 48th Annual Allerton Conference on Communication, 2010

2009
A low-complexity universal scheme for rate-constrained distributed regression using a wireless sensor network.
IEEE Trans. Signal Process., 2009

Joint universal lossy coding and identification of stationary mixing sources with general alphabets.
IEEE Trans. Inf. Theory, 2009

Supervised Learning of Quantizer Codebooks by Information Loss Minimization.
IEEE Trans. Pattern Anal. Mach. Intell., 2009

Sequential anomaly detection in the presence of noise and limited feedback
CoRR, 2009

Performance Bounds for Expander-based Compressed Sensing in the presence of Poisson Noise
CoRR, 2009

Minimax risk for Poisson compressed sensing
CoRR, 2009

Locality-sensitive binary codes from shift-invariant kernels.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Performance bounds on compressed sensing with Poisson noise.
Proceedings of the IEEE International Symposium on Information Theory, 2009

Sequential probability assignment via online convex programming using exponential families.
Proceedings of the IEEE International Symposium on Information Theory, 2009

Achievability results for statistical learning under communication constraints.
Proceedings of the IEEE International Symposium on Information Theory, 2009

An empirical Bayes approach to contextual region classification.
Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009

Information complexity of black-box convex optimization: A new look via feedback information theory.
Proceedings of the 47th Annual Allerton Conference on Communication, 2009

2008
Joint Fixed-Rate Universal Lossy Coding and Identification of Continuous-Alphabet Memoryless Sources.
IEEE Trans. Inf. Theory, 2008

Cooperation in self-organizing map networks enhances information transmission in the presence of input background activity.
Biol. Cybern., 2008

Near-minimax recursive density estimation on the binary hypercube.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Universal Wyner-Ziv coding of discrete memoryless sources with known side information statistics.
Proceedings of the 2008 IEEE International Symposium on Information Theory, 2008

On the information capacity of Gaussian channels under small peak power constraints.
Proceedings of the 46th Annual Allerton Conference on Communication, 2008

2007
Learning Nearest-Neighbor Quantizers from Labeled Data by Information Loss Minimization.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Learning from compressed observations
CoRR, 2007

Joint Universal Lossy Coding and Identification of Stationary Mixing Sources.
Proceedings of the IEEE International Symposium on Information Theory, 2007

2006
Joint Universal Lossy Coding and Identification of I.I.D. Vector Sources.
Proceedings of the Proceedings 2006 IEEE International Symposium on Information Theory, 2006

2005
Estimation of Intrinsic Dimensionality Using High-Rate Vector Quantization.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

A complexity-regularized quantization approach to nonlinear dimensionality reduction.
Proceedings of the 2005 IEEE International Symposium on Information Theory, 2005

2003
Scaling and Renormalization in Fault-Tolerant Quantum Computers.
Quantum Inf. Process., 2003


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