V. Tadić

发表

Parameter estimation in general state-space models using particle methods

A. Doucet, V. Tadić, 2003 .

On the Convergence of Temporal-Difference Learning with Linear Function Approximation

Vladislav Tadic, V. Tadić, 2001, Machine Learning.

Convergence of stochastic approximation under general noise and stability conditions

V. Tadić, 1997, Proceedings of the 36th IEEE Conference on Decision and Control.

Probabilistic and Randomized Methods for Design under Uncertainty

Sean P. Meyn, Roberto Tempo, Vladislav B. Tadić, 2006 .

Almost sure convergence of two time-scale stochastic approximation algorithms

V. Tadić, 2004, Proceedings of the 2004 American Control Conference.

Convergence and convergence rate of stochastic gradient search in the case of multiple and non-isolated extrema

V. Tadić, 2015 .

Two time-scale stochastic approximation for constrained stochastic optimization and constrained Markov decision problems

A. Doucet, V. Tadić, S. Singh, 2003, Proceedings of the 2003 American Control Conference, 2003..

Performance Evaluation and Policy Selection in Multiclass Networks

Sean P. Meyn, Shane G. Henderson, Vladislav B. Tadic, 2003, Discret. Event Dyn. Syst..

A policy gradient method for semi-Markov decision processes with application to call admission control

Arnaud Doucet, Sumeetpal S. Singh, Vladislav B. Tadic, 2007, Eur. J. Oper. Res..

Asymptotic properties of two time-scale stochastic approximation algorithms with constant step sizes

S. Meyn, V. Tadić, V. Tadic, 2003, Proceedings of the 2003 American Control Conference, 2003..

On-Line Parameter Estimation in General State-Space Models

A. Doucet, V. Tadić, C. Andrieu, 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

Stochastic approximation with random truncations, state-dependent noise and discontinuous dynamics

V. Tadić, 1998 .

Asymptotic bias of stochastic gradient search

A. Doucet, V. Tadić, 2017 .

Exponential forgetting and geometric ergodicity for optimal filtering in general state-space models

A. Doucet, V. Tadić, 2005 .

Online sampling for parameter estimation in general state space models

A. Doucet, V. Tadić, C. Andrieu, 2003 .

Randomized algorithms for semi-infinite programming problems

Sean P. Meyn, Roberto Tempo, Vladislav B. Tadic, 2003, 2003 European Control Conference (ECC).

Optimisation of particle filters using simultaneous perturbation stochastic approximation

Arnaud Doucet, Vladislav B. Tadic, Bao Ling Chan, 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

On-line optimization of sequential Monte Carlo methods using stochastic approximation

A. Doucet, V. Tadić, V. Tadic, 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

Asymptotic Properties of Recursive Maximum Likelihood Estimation in Non-Linear State-Space Models

A. Doucet, V. Tadić, 2018, 1806.09571.

Mean-square asymptotic analysis of cross-coupled Kalman filter state-estimation algorithm for bilinear systems

V. Tadić, V. Krishnamurthy, 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

WEAK CONVERGENCE ANALYSIS OF CROSS-COUPLED KALMAN FILTER STATE-ESTIMATION ALGORITHM FOR BILINEAR SYSTEMS

V. Tadić, V. Krishnamurthy, 2002 .

On the mean-square rate of convergence of temporal-difference learning algorithms

V. Tadić, 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

ON THE ALMOST SURE RATE OF CONVERGENCE OF TEMPORAL-DIFFERENCE LEARNING ALGORITHMS

V. Tadić, 2002 .

PR ] 1 A ug 2 01 8 Stability of Optimal Filter Higher-Order Derivatives

A. Doucet, V. Tadić, 2018 .

Exponential forgetting and geometric ergodicity in state-space models

A. Doucet, V. Tadić, V.B. Tadic, 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

Exponential forgetting and geo-metric ergodicity in general state-space models

Arnaud Doucet, Vladislav B. Tadić, A. Doucet, 2002 .

One-line Parameter Estimation in General State-Space Models using a Pseudo-Likelihood Approach

A. Doucet, V. Tadić, C. Andrieu, 2012 .

On the robustness of two time-scale stochastic approximation algorithms

V. Tadić, 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

Stochastic gradient algorithm with random truncations

V. Tadić, 1997 .

Diffusion approximation for two time-scale stochastic approximation algorithms with constant step sizes

V. Tadić, 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

Convergence and convergence rate of stochastic gradient search in the case of multiple and non-isolated extrema

V. Tadić, 2015 .

Convergence and convergence rate of stochastic gradient search in the case of multiple and non-isolated extrema

V. Tadić, 2009, 49th IEEE Conference on Decision and Control (CDC).

On the Robustness of LMS Algorithm

V. Tadić, 1996 .

Stability of Optimal Filter Higher-Order Derivatives

A. Doucet, V. Tadić, 2018, 2019 IEEE 58th Conference on Decision and Control (CDC).

A MonteCarloAlgorithm forOptimalQuantization

V. Tadić, Columbia Vancouver, 2007 .

Particle methods for change detection, system identification, and control

Christophe Andrieu, Arnaud Doucet, Sumeetpal S. Singh, 2004, Proceedings of the IEEE.

Asymptotic analysis of temporal-difference learning algorithms with linear function approximation

V. Tadić, 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304).

Asymptotic bias of stochastic gradient search

Arnaud Doucet, Vladislav B. Tadic, A. Doucet, 2011, IEEE Conference on Decision and Control and European Control Conference.

Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise

Hoi-To Wai, Eric Moulines, Alexey Naumov, 2020, COLT.

Convergence analysis of temporal-difference learning algorithms with linear function approximation

Vladislav Tadic, V. Tadić, 1999, COLT '99.

Recovery of compressively sensed ultrasound images with structured Sparse Bayesian Learning

Alin Achim, Richard J Porter, Vladislav B. Tadić, 2018, 1811.01257.

Reconstruction of compressively sensed ultrasound RF echoes by exploiting non-Gaussianity and temporal structure

Alin Achim, Vladislav B. Tadic, Richard Porter, 2015, 2015 IEEE International Conference on Image Processing (ICIP).

Better than ℓ0 recovery via blind identification

Alin Achim, Vladislav B. Tadic, Richard Porter, 2015, 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

A policy gradient method for SMDPs with application to call admission control

Arnaud Doucet, Vladislav B. Tadic, Sumetpal Singh, 2002, 7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002..

Asymptotic analysis of temporal-difference learning algorithms with constant step-sizes

Vladislav B. Tadic, V. Tadić, 2006, Machine Learning.

On the Asymptotic Behaviour of a Constant Stepsize Temporal-Difference Learning Algorithm

Vladislav Tadic, V. Tadić, 1999, EuroCOLT.

A mean-square asymptotic analysis of a constant stepsize temporal-difference learning algorithm

V. Tadić, 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).

On the almost sure rate of convergence of linear stochastic approximation algorithms

V. B. Tadic, V. Tadić, 2004, IEEE Transactions on Information Theory.

Analyticity, Convergence, and Convergence Rate of Recursive Maximum-Likelihood Estimation in Hidden Markov Models

V B Tadić, V. Tadić, V. Tadic, 2009, IEEE Transactions on Information Theory.

Asymptotic Properties of Recursive Particle Maximum Likelihood Estimation

Arnaud Doucet, Vladislav Z. B. Tadić, A. Doucet, 2019, 2019 IEEE International Symposium on Information Theory (ISIT).

Asymptotic Properties of Recursive Particle Maximum Likelihood Estimation

Arnaud Doucet, Vladislav Z. B. Tadić, A. Doucet, 2021, IEEE Transactions on Information Theory.

Bias of Particle Approximations to Optimal Filter Derivative

Arnaud Doucet, Vladislav Z.B. Tadic, A. Doucet, 2018, SIAM J. Control. Optim..

Analyticity of Entropy Rates of Continuous-State Hidden Markov Models

Arnaud Doucet, Vladislav Z. B. Tadic, A. Doucet, 2018, IEEE Transactions on Information Theory.

Maximum Likelihood Parameter Estimation in General State-Space Models using Particle Methods

A. Doucet, V. Tadić, V. Tadic, 2005 .