Fetching the paper…
Reading the bibliography…
The convergence of many numerical optimization techniques is highly dependent on the initial guess given to the solver.
IEEE Circuits and Devices magazine 5(1): 19–26
Rutenbar RA (1989) Simulated annealing algorithms: An overview · 1989
Earlier work this paper cites.
Statistics and computing 4(2): 65–85
Whitley D (1994) A genetic algorithm tutorial · 1994
Earlier work this paper cites.
Evolutionary computation 11(1): 1–18
Hansen N, Müller SD and Koumoutsakos P (2003) Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (cma-es) · 2003
Earlier work this paper cites.
Cambridge, MA, USA: MIT Press
Rasmussen C and Williams C (2006) Gaussian Processes for Machine Learning · 2006
Earlier work this paper cites.
In: Proc. IEEE Intl Conf. on Robotics and Automation (ICRA) . pp. 3344–3349
Stolle M and Atkeson CG (2006) Policies based on trajectory libraries · 2006
Earlier work this paper cites.
In: Proc. IEEE/RSJ Intl Conf. on Intelligent Robots and Systems (IROS) . pp. 2981–2986
Stolle M, Tappeiner H, Chestnutt J and Atkeson CG (2007) Transfer of policies based on trajectory libraries · 2007
Earlier work this paper cites.
In: Proc. Intl Conf. on Machine Learning (ICML) . pp. 449–456
Jetchev N and Toussaint M (2009) Trajectory prediction: learning to map situations to robot trajectories · 2009
Earlier work this paper cites.
SIAM review 51(3): 455–500
Kolda TG and Bader BW (2009) Tensor decompositions and applications · 2009
Earlier work this paper cites.
In: Proc. IEEE Intl Conf. on Robotics and Automation (ICRA) . pp. 3733–3738
Escande A, Mansard N and Wieber PB (2010) Fast resolution of hierarchized inverse kinematics with inequality constraints · 2010
Earlier work this paper cites.
In: Matrix Methods: Theory, Algorithms And Applications: Dedicated to the Memory of Gene Golub . World Scientific, pp. 247–256
Goreinov SA, Oseledets I, Savostyanov DV, Tyrtyshnikov EE and Zamarashkin N (2010) How to find a good submatrix · 2010
Earlier work this paper cites.
Linear Algebra and its Applications 432(1): 70–88
Oseledets I and Tyrtyshnikov E (2010) TT-cross approximation for multidimensional arrays · 2010
Earlier work this paper cites.
In: Proc. IEEE Intl Conf. on Robotics and Automation (ICRA) . pp. 4569–4574
Kalakrishnan M, Chitta S, Theodorou E, Pastor P and Schaal S (2011) STOMP: Stochastic trajectory optimization for motion planning · 2011
Earlier work this paper cites.
SIAM Journal on Scientific Computing 33: 2295–2317
Oseledets I (2011) Tensor-train decomposition · 2011
Earlier work this paper cites.
The 2011 International Workshop on Multidimensional (nD) Systems : 1–8
Savostyanov DV and Oseledets I (2011) Fast adaptive interpolation of multi-dimensional arrays in tensor train format · 2011
Earlier work this paper cites.
IEEE Transactions on Robotics 27(5): 984–991
Sugihara T (2011) Solvability-unconcerned inverse kinematics by the Levenberg–Marquardt method · 2011
Earlier work this paper cites.
GAMM-Mitteilungen 36(1): 53–78
Grasedyck L, Kressner D and Tobler C (2013) A literature survey of low‐rank tensor approximation techniques · 2013
Earlier work this paper cites.
Advances in Neural Information Processing Systems (NIPS) 26
Paraschos A, Daniel C, Peters JR and Neumann G (2013) Probabilistic movement primitives · 2013
Cited alongside, same era.
Intl Journal of Robotics Research 32(9-10): 1164–1193
Zucker M, Ratliff N, Dragan AD, Pivtoraiko M, Klingensmith M, Dellin CM, Bagnell JA and Srinivasa SS (2013) CHOMP: Covariant hamiltonian optimization for motion planning · 2013
Cited alongside, same era.
In: Proc. IEEE Intl Conf. on Humanoid Robots (Humanoids) . pp. 279–286
Deits R and Tedrake R (2014) Footstep planning on uneven terrain with mixed-integer convex optimization · 2014
Cited alongside, same era.
IEEE Conference on Decision and Control (CDC) : 5880–5887
Horowitz MB, Damle A and Burdick JW (2014) Linear Hamilton Jacobi Bellman equations in high dimensions · 2014
Cited alongside, same era.
Intl Journal of Robotics Research 33(9): 1251–1270
Schulman J, Duan Y, Ho J, Lee A, Awwal I, Bradlow H, Pan J, Patil S, Goldberg K and Abbeel P (2014) Motion planning with sequential convex optimization and convex collision checking · 2014
Cited alongside, same era.
In: Bouguila N and Fan W (eds.) Mixture Models and Applications . Springer, Cham, pp. 39–57
Calinon S (2019) Mixture models for the analysis, edition, and synthesis of continuous time series · 2019
Later among the works it cites.
Entropy 21
Stokes J and Terilla J (2019) Probabilistic modeling with matrix product states · 2019
Later among the works it cites.
In: International Conference on Large-Scale Scientific Computing . Springer, pp. 197–202
Zheltkov DA and Osinsky A (2019) Global optimization algorithms using tensor trains · 2019
Later among the works it cites.
Statistics and Computing 30: 603–625
Dolgov S, Anaya-Izquierdo K, Fox C and Scheichl R (2020) Approximation and sampling of multivariate probability distributions in the tensor train decomposition · 2020
Later among the works it cites.
Computer Physics Communications 246: 106869
Dolgov S and Savostyanov D (2020) Parallel cross interpolation for high-precision calculation of high-dimensional integrals · 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…
IEEE Signal Processing Magazine 32: 145–163
Cichocki A, Mandic DP, Lathauwer LD, Zhou G, Zhao Q, Caiafa CF and Phan AH (2015) Tensor decompositions for signal processing applications: From two-way to multiway component analysis · 2015
Cited alongside, same era.
In: Proc. Robotics: Science and Systems (R:SS) . pp. 1–8
Gorodetsky A, Karaman S and Marzouk Y (2015) Efficient high-dimensional stochastic optimal motion control using tensor-train decomposition · 2015
Cited alongside, same era.
IEEE Transactions on Robotics 33: 141–152
Hauser KK (2016) Learning the problem-optimum map: Analysis and application to global optimization in robotics · 2016
Cited alongside, same era.
Linear and Multilinear Algebra 65(11): 2212–2244
Kishore Kumar N and Schneider J (2017) Literature survey on low rank approximation of matrices · 2017
Cited alongside, same era.
ArXiv 1711.10781
Rabanser S, Shchur O and Günnemann S (2017) Introduction to tensor decompositions and their applications in machine learning · 2017
Cited alongside, same era.
IEEE Transactions on Signal Processing 65: 3551–3582
Sidiropoulos ND, Lathauwer LD, Fu X, Huang K, Papalexakis EE and Faloutsos C (2017) Tensor decomposition for signal processing and machine learning · 2017
Cited alongside, same era.
Phys. Rev. X 8: 031012
Han ZY, Wang J, Fan H, Wang L and Zhang P (2018) Unsupervised generative modeling using matrix product states · 2018
Cited alongside, same era.
Lembono TS, Paolillo A, Pignat E and Calinon S (2020) Memory of motion for warm-starting trajectory optimization · 2020
Later among the works it cites.
Intl Journal of Robotics Research 39(8): 983–1001
Osa T (2020) Multimodal trajectory optimization for motion planning · 2020
Later among the works it cites.
In: Proc. IEEE Intl Conf. on Robotics and Automation (ICRA) . pp. 3395–3401
Pignat E, Lembono T and Calinon S (2020) Variational inference with mixture model approximation for applications in robotics · 2020
Later among the works it cites.
In: Proc. IEEE Intl Conf. on Robotics and Automation (ICRA) . pp. 8202–8208
Dantec E, Budhiraja R, Roig A, Lembono T, Saurel G, Stasse O, Fernbach P, Tonneau S, Vijayakumar S, Calinon S et al. (2021) Whole body model predictive control with a memory of motion: Experiments on a torque-controlled talos · 2021
Later among the works it cites.
In: International Conference on Artificial Intelligence and Statistics . PMLR, pp. 3079–3087
Miller J, Rabusseau G and Terilla J (2021) Tensor networks for probabilistic sequence modeling · 2021
Later among the works it cites.
In: Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence , Proceedings of Machine Learning Research , volume 161. PMLR, pp. 1321–1331
Novikov GS, Panov ME and Oseledets I (2021) Tensor-train density estimation · 2021
Later among the works it cites.
Intl Journal of Robotics Research 41(3): 281–311
Osa T (2022) Motion planning by learning the solution manifold in trajectory optimization · 2022
Closest in time.
International Journal of Robotics Research (IJRR) 41(2): 163–188
Pignat E, Silvério J and Calinon S (2022) Learning from demonstration using products of experts: Applications to manipulation and task prioritization · 2022
Closest in time.
IEEE Trans. on Robotics 38(2): 906–921
Shetty S, Silvério J and Calinon S (2022) Ergodic exploration using tensor train: Applications in insertion tasks · 2022
Closest in time.
Advances in Neural Information Processing Systems 35: 26052–26065
Sozykin K, Chertkov A, Schutski R, Phan AH, Cichocki A and Oseledets I (2022) TTOpt: A maximum volume quantized tensor train-based optimization and its application to reinforcement learning · 2022
Closest in time.