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Sethu Vijayakumar: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Graham McNeill, Sethu Vijayakumar
    Hierarchical Procrustes Matching for Shape Retrieval. [Citation Graph (0, 0)][DBLP]
    CVPR (1), 2006, pp:885-894 [Conf]
  2. Jan Peters, Sethu Vijayakumar, Stefan Schaal
    Natural Actor-Critic. [Citation Graph (0, 0)][DBLP]
    ECML, 2005, pp:280-291 [Conf]
  3. Georgios Petkos, Marc Toussaint, Sethu Vijayakumar
    Learning Multiple Models of Non-linear Dynamics for Control Under Varying Contexts. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2006, pp:898-907 [Conf]
  4. Jörg Conradt, Gaurav Tevatia, Sethu Vijayakumar, Stefan Schaal
    On-line Learning for Humanoid Robot Systems. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:191-198 [Conf]
  5. Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal
    The Bayesian backfitting relevance vector machine. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  6. Marc Toussaint, Sethu Vijayakumar
    Learning discontinuities with products-of-sigmoids for switching between local models. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:904-911 [Conf]
  7. Sethu Vijayakumar, Stefan Schaal
    Locally Weighted Projection Regression: Incremental Real Time Learning in High Dimensional Space. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:1079-1086 [Conf]
  8. Graham McNeill, Sethu Vijayakumar
    Part-Based Probabilistic Point Matching. [Citation Graph (0, 0)][DBLP]
    ICPR (2), 2006, pp:382-386 [Conf]
  9. Stefan Schaal, Christopher G. Atkeson, Sethu Vijayakumar
    Real-Time Robot Learning with Locally Weighted Statistical Learning. [Citation Graph (0, 0)][DBLP]
    ICRA, 2000, pp:288-293 [Conf]
  10. Sethu Vijayakumar, Stefan Schaal
    Fast and Efficient Incremental Learning for High-Dimensional Movement Systems. [Citation Graph (0, 0)][DBLP]
    ICRA, 2000, pp:1894-1899 [Conf]
  11. Sethu Vijayakumar, S. Wu
    Sequential Support Vector Classifiers and Regression. [Citation Graph (0, 0)][DBLP]
    IIA/SOCO, 1999, pp:- [Conf]
  12. Graham McNeill, Sethu Vijayakumar
    2D Shape Classification and Retrieval. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2005, pp:1483-1488 [Conf]
  13. Marc Toussaint, Sethu Vijayakumar
    Learning discontinuities for switching between local models. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2005, pp:1744-1745 [Conf]
  14. Timothy M. Hospedales, Joel J. Cartwright, Sethu Vijayakumar
    Structure Inference for Bayesian Multisensory Perception and Tracking. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2007, pp:2122-2128 [Conf]
  15. Narayanan U. Edakunni, Stefan Schaal, Sethu Vijayakumar
    Kernel Carpentry for Online Regression Using Randomly Varying Coefficient Model. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2007, pp:762-767 [Conf]
  16. Stefan Schaal, Sethu Vijayakumar, Christopher G. Atkeson
    Local Dimensionality Reduction. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  17. Stefan Schaal, Christopher G. Atkeson, Sethu Vijayakumar
    Scalable Techniques from Nonparametric Statistics for Real Time Robot Learning. [Citation Graph (0, 0)][DBLP]
    Appl. Intell., 2002, v:17, n:1, pp:49-60 [Journal]
  18. Sethu Vijayakumar, Aaron D'Souza, Tomohiro Shibata, Jörg Conradt, Stefan Schaal
    Statistical Learning for Humanoid Robots. [Citation Graph (0, 0)][DBLP]
    Auton. Robots, 2002, v:12, n:1, pp:55-69 [Journal]
  19. Christopher G. Atkeson, Joshua G. Hale, Frank E. Pollick, Marcia Riley, Shinya Kotosaka, Stefan Schaal, Tomohiro Shibata, Gaurav Tevatia, Ales Ude, Sethu Vijayakumar, Mitsuo Kawato
    Using Humanoid Robots to Study Human Behavior. [Citation Graph (0, 0)][DBLP]
    IEEE Intelligent Systems, 2000, v:15, n:4, pp:46-56 [Journal]
  20. Sethu Vijayakumar, Hidemitsu Ogawa
    RKHS-based functional analysis for exact incremental learning. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 1999, v:29, n:1-3, pp:85-113 [Journal]
  21. Sethu Vijayakumar, Aaron D'Souza, Stefan Schaal
    Incremental Online Learning in High Dimensions. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2005, v:17, n:12, pp:2602-2634 [Journal]
  22. Sethu Vijayakumar, Stefan Schaal
    Local Adaptive Subspace Regression. [Citation Graph (0, 0)][DBLP]
    Neural Processing Letters, 1998, v:7, n:3, pp:139-149 [Journal]
  23. Heiko Hoffmann, Georgios Petkos, Sebastian Bitzer, Sethu Vijayakumar
    Sensor-assisted adaptive motor control under continuously varying context. [Citation Graph (0, 0)][DBLP]
    ICINCO-ICSO, 2007, pp:262-269 [Conf]
  24. Graham McNeill, Sethu Vijayakumar
    A Probabilistic Approach to Robust Shape Matching. [Citation Graph (0, 0)][DBLP]
    ICIP, 2006, pp:937-940 [Conf]
  25. Graham McNeill, Sethu Vijayakumar
    Linear and nonlinear generative probabilistic class models for shape contours. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:617-624 [Conf]
  26. Masashi Sugiyama, Hirotaka Hachiya, Christopher Towell, Sethu Vijayakumar
    Value Function Approximation on Non-Linear Manifolds for Robot Motor Control. [Citation Graph (0, 0)][DBLP]
    ICRA, 2007, pp:1733-1740 [Conf]
  27. Georgios Petkos, Sethu Vijayakumar
    Context Estimation and Learning Control through Latent Variable Extraction: From discrete to continuous contexts. [Citation Graph (0, 0)][DBLP]
    ICRA, 2007, pp:2117-2123 [Conf]
  28. Graham McNeill, Sethu Vijayakumar
    Part-based Probabilistic Point Matching using Equivalence Constraints. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:969-976 [Conf]

  29. Optimal Control with Adaptive Internal Dynamics Models. [Citation Graph (, )][DBLP]

  30. A Bayesian approach to empirical local linearization for robotics. [Citation Graph (, )][DBLP]

  31. A novel method for learning policies from constrained motion. [Citation Graph (, )][DBLP]

  32. Optimal Feedback Control for anthropomorphic manipulators. [Citation Graph (, )][DBLP]

  33. Efficient Online Classification Using an Ensemble of Bayesian Linear Logistic Regressors. [Citation Graph (, )][DBLP]

  34. Bayesian Kernel Shaping for Learning Control. [Citation Graph (, )][DBLP]

  35. Multi-task Gaussian Process Learning of Robot Inverse Dynamics. [Citation Graph (, )][DBLP]

  36. Unifying the Sensory and Motor Components of Sensorimotor Adaptation. [Citation Graph (, )][DBLP]

  37. Synthesising Novel Movements through Latent Space Modulation of Scalable Control Policies. [Citation Graph (, )][DBLP]

  38. Adaptive Optimal Control for Redundantly Actuated Arms. [Citation Graph (, )][DBLP]

  39. Load estimation and control using learned dynamics models. [Citation Graph (, )][DBLP]

  40. Robust constraint-consistent learning. [Citation Graph (, )][DBLP]

  41. Towards Semi-supervised Manifold Learning: UKR with Structural Hints. [Citation Graph (, )][DBLP]

  42. Learning Utility Surfaces for Movement Selection. [Citation Graph (, )][DBLP]

  43. Geodesic Gaussian kernels for value function approximation. [Citation Graph (, )][DBLP]

  44. A novel method for learning policies from variable constraint data. [Citation Graph (, )][DBLP]

  45. Implications of different classes of sensorimotor disturbance for cerebellar-based motor learning models. [Citation Graph (, )][DBLP]

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