Fetching the paper…
Reading the bibliography…
We consider the problem of estimating a linear time-invariant (LTI) dynamical system from a single trajectory via streaming algorithms, which is encountered in several applications including reinforcement learning (RL) and time-series analysis.
Nets of Grassmann manifold and orthogonal group
Stanislaw J Szarek · 1982
Earlier work this paper cites.
Asymptotic properties of general autoregressive models and strong consistency of least-squares estimates of their parameters
TL Lai and CZ Wei · 1983
Earlier work this paper cites.
Self-improving reactive agents based on reinforcement learning, planning and teaching
Long-Ji Lin · 1992
Earlier work this paper cites.
On the averaged stochastic approximation for linear regression
László Györfi and Harro Walk · 1996
Earlier work this paper cites.
Finite sample properties of system identification methods
Marco C Campi and Erik Weyer · 2002
Earlier work this paper cites.
Lectures on the coupling method
Torgny Lindvall · 2002
Earlier work this paper cites.
A learning theory approach to system identification and stochastic adaptive control
Mathukumalli Vidyasagar and Rajeeva L Karandikar · 2006
Earlier work this paper cites.
Modeling gene expression regulatory networks with the sparse vector autoregressive model
André Fujita, João R Sato, Humberto M Garay-Malpartida, Rui Yamaguchi, Satoru Miyano, Mari C Sogayar, and Carlos E Ferreira · 2007
Earlier work this paper cites.
Ergodic Mirror Descent
John C. Duchi, Alekh Agarwal, Mikael Johansson, and Michael I. Jordan · 2012
Earlier work this paper cites.
Lossless convexification of nonconvex control bound and pointing constraints of the soft landing optimal control problem
Behçet Açıkmeşe, John M Carson, and Lars Blackmore · 2013
Earlier work this paper cites.
Concentration inequalities: A nonasymptotic theory of independence
Stéphane Boucheron, Gábor Lugosi, and Pascal Massart · 2013
Earlier work this paper cites.
Sparse PCA: Optimal rates and adaptive estimation
T Tony Cai, Zongming Ma, Yihong Wu, et al · 2013
Earlier work this paper cites.
Stochastic systems: Estimation, identification, and adaptive control
Panqanamala Ramana Kumar and Pravin Varaiya · 2015
Earlier work this paper cites.
Regularized estimation in sparse high-dimensional time series models
Sumanta Basu, George Michailidis, et al · 2015
Earlier work this paper cites.
Averaged least-mean-squares: Bias-variance trade-offs and optimal sampling distributions
Alexandre Défossez and Francis Bach · 2015
Earlier work this paper cites.
A neural autoregressive approach to collaborative filtering
Yin Zheng, Bangsheng Tang, Wenkui Ding, and Hanning Zhou · 2016
Earlier work this paper cites.
Reverse replay of hippocampal place cells is uniquely modulated by changing reward
R Ellen Ambrose, Brad E Pfeiffer, and David J Foster · 2016
Earlier work this paper cites.
Time series prediction and online learning
Vitaly Kuznetsov and Mehryar Mohri · 2016
Earlier work this paper cites.
Non-asympototic version of Gelfand’s formula
Fedor Petrov · 2016
Earlier work this paper cites.
Parallelizing stochastic gradient descent for least squares regression: mini-batching, averaging, and model misspecification
Prateek Jain, Praneeth Netrapalli, Sham M Kakade, Rahul Kidambi, and Aaron Sidford · 2017
Cited alongside, same era.
Learning linear dynamical systems via spectral filtering
Elad Hazan, Karan Singh, and Cyril Zhang · 2017
Cited alongside, same era.
Learning without mixing: Towards a sharp analysis of linear system identification
Max Simchowitz, Horia Mania, Stephen Tu, Michael I Jordan, and Benjamin Recht · 2018
Cited alongside, same era.
Low Rank and Structured Modeling of High-Dimensional Vector Autoregressions
Sumanta Basu, Xianqi Li, and George Michailidis · 2018
Cited alongside, same era.
Finite time identification in unstable linear systems
Mohamad Kazem Shirani Faradonbeh, Ambuj Tewari, and George Michailidis · 2018
Cited alongside, same era.
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms
Dheeraj Nagaraj, Xian Wu, Guy Bresler, Prateek Jain, and Praneeth Netrapalli · 2020
Later among the works it cites.
Finite-time Identification of Stable Linear Systems Optimality of the Least-Squares Estimator
Yassir Jedra and Alexandre Proutiere · 2020
Later among the works it cites.
Non-asymptotic and accurate learning of nonlinear dynamical systems
Yahya Sattar and Samet Oymak · 2020
Later among the works it cites.
Learning nonlinear dynamical systems from a single trajectory
Dylan Foster, Tuhin Sarkar, and Alexander Rakhlin · 2020
Later among the works it cites.
Logarithmic regret bound in partially observable linear dynamical systems
Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, and Anima Anandkumar · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Vitaly Kuznetsov and Mehryar Mohri · 2018
Cited alongside, same era.
Gradient descent learns linear dynamical systems
Moritz Hardt, Tengyu Ma, and Benjamin Recht · 2018
Cited alongside, same era.
Online linear quadratic control
Alon Cohen, Avinatan Hasidim, Tomer Koren, Nevena Lazic, Yishay Mansour, and Kunal Talwar · 2018
Cited alongside, same era.
High-dimensional probability: An introduction with applications in data science , volume 47
Roman Vershynin · 2018
Cited alongside, same era.
Near optimal finite time identification of arbitrary linear dynamical systems
Tuhin Sarkar and Alexander Rakhlin · 2019
Cited alongside, same era.
Introduction to econometrics with r
Christoph Hanck, Martin Arnold, Alexander Gerber, and Martin Schmelzer · 2019
Cited alongside, same era.
Egor Rotinov · 2019
Cited alongside, same era.
Improved rates for identification of partially observed linear dynamical systems
Holden Lee · 2020
Later among the works it cites.
Non-asymptotic closed-loop system identification using autoregressive processes and hankel model reduction
Bruce Lee and Andrew Lamperski · 2020
Later among the works it cites.
The nonstochastic control problem
Elad Hazan, Sham Kakade, and Karan Singh · 2020
Later among the works it cites.
Black-box control for linear dynamical systems
Xinyi Chen and Elad Hazan · 2020
Later among the works it cites.
No-regret prediction in marginally stable systems
Udaya Ghai, Holden Lee, Karan Singh, Cyril Zhang, and Yi Zhang · 2020
Later among the works it cites.
SLIP: Learning to predict in unknown dynamical systems with long-term memory
Paria Rashidinejad, Jiantao Jiao, and Stuart Russell · 2020
Later among the works it cites.
Sample complexity of kalman filtering for unknown systems
Anastasios Tsiamis, Nikolai Matni, and George Pappas · 2020
Later among the works it cites.
Online learning of the kalman filter with logarithmic regret
Anastasios Tsiamis and George Pappas · 2020
Later among the works it cites.
Near-optimal Offline and Streaming Algorithms for Learning Non-Linear Dynamical Systems
Prateek Jain, Suhas S Kowshik, Dheeraj Nagaraj, and Praneeth Netrapalli · 2021
Closest in time.
Naman Agarwal, Syomantak Chaudhuri, Prateek Jain, Dheeraj Nagaraj, and Praneeth Netrapalli · 2021
Closest in time.
A robotic model of hippocampal reverse replay for reinforcement learning
Matthew T Whelan, Tony J Prescott, and Eleni Vasilaki · 2021
Closest in time.
Finite Time LTI System Identification
Tuhin Sarkar, Alexander Rakhlin, and Munther A Dahleh · 2021
Closest in time.
Linear systems can be hard to learn
Anastasios Tsiamis and George J Pappas · 2021
Closest in time.