Sethu Vijayakumar//publications//
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 [For list arranged by Publication Year, click here]

[Online Learning: Nonparametric methods, Kernel Methods, Real-time Robot Learning] [Context Estimation] [RL and Optimal Control] [Variable Impedance Actuation] [Visual attention and Oculomotor control] [Bayesian Decision Making in Human Sensorimotor Control] [Haptics] [Shape Analysis] [Active Learning/Sparse representation] [Planning and Control in Topological Spaces]

  Online Incremental Learning: Nonparametric methods, Local learning
  • Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar and Stefan Schaal,
    Efficient Learning and Feature Selection in High Dimensional Regression,
    Neural Computation, vol. 22, no. 4, pp. 831-886 (2010). [pdf] 
  • Narayanan Edakunni and Sethu Vijayakumar,
    Efficient Online classification using an Ensemble of Bayesian Linear Logistic Regressors,
    Proc. 8th International Workshop on Multiple Classifier Systems (MCS ’09), Reykjavik, Iceland (2009). [pdf]
  • Jo-Anne Ting, Mrinal Kalakrishnan, Sethu Vijayakumar and Stefan Schaal,
    Bayesian Kernel Shaping for Learning Control,
    Proc. Advances in Neural Information Processing Systems (NIPS '08), Vancouver, Canada (2008).[pdf] [spotlight, audio]
  • Stefan Klanke, Sethu Vijayakumar and Stefan Schaal,
    A Library for Locally Weighted Projection Regression,
    Journal of Machine Learning Research (JMLR), vol. 9, pp. 623--626 (2008). [pdf][DOI]
  • Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar and Stefan Schaal,
    A Bayesian Approach to Empirical Local Linearization for Robotics,
    Proc. IEEE International Conference on Robotics and Automation (ICRA '08), Pasadena, CA (2008).[pdf]
  • Narayanan Edakunni, Stefan Schaal and Sethu Vijayakumar,
    Kernel Carpentry for Online Regression using Randomly Varying Coefficient Model,
    Proc. International Joint Conference on Artificial Intelligence (IJCAI '07), Hyderabad, India (2007). [pdf]
  • Sethu Vijayakumar, Aaron D'Souza and Stefan Schaal,
    Approximate nearest neighbor regression in very high dimensions,
    In (eds.) Shakhnarovich, Darrell and Indyk, Nearest Neighbor Methods in Learning and Vision, MIT Press, Cambridge, MA, pp. 103-142 (2006). [pdf]
  • Sethu Vijayakumar, Aaron D'Souza and Stefan Schaal,
    Incremental Online Learning in High Dimensions,
    Neural Computation, vol. 17, no. 12, pp. 2602-2634 (2005) [pdf].
    [More detailed version of the paper Tech Report EDI-INF-RR-0284 of UEDIN].
  • Aaron D'Souza, Sethu Vijayakumar and Stefan Schaal,
    Bayesian Backfitting Relevance Vector Machine,
    Proc. 21st Intl .Conf. on Machine Learning (ICML'04), Article No. 31, Banff, Canada, Jul 4-8 (2004).[pdf]
  • Aaron D'Souza, Sethu Vijayakumar and Stefan Schaal,
    Bayesian Backfitting for High Dimensional Regression,
    Proc. 10th Joint Symposium on Neural Computation, UC Irvine, May 17 (2003).[pdf]
  • Sethu Vijayakumar and Stefan Schaal,
    LWPR : An O(n) Algorithm for Incremental Real Time Learning in High Dimensional Space,
    Proc. of Seventeenth International Conference on Machine Learning (ICML2000) Stanford, California, pp.1079-1086 (2000) [pdf] [gzip-ed ps].
  • Sethu Vijayakumar and Stefan Schaal,
    Fast and Efficient Incremental Learning for High-dimensional Movement Systems,
    Proc. International Conference on Robotics and Automation (ICRA2000), San Francisco, California, vol.2, pp.1894-1899 (2000) [pdf] [gzip-ed ps].
  • Sethu Vijayakumar and Stefan Schaal,
    Robust local learning in high dimensional spaces,
    Proc. 5th Joint Symposium on Neural Computation, May 16,1998, San Diego, pp.186-193 (1998).
  • Sethu Vijayakumar and Stefan Schaal,
    Local Adaptive Subspace Regression,
    Neural Processing Letters, Vol.7, No.3, pp 139-149, Kluwer Academic Press (1998).
 Incremental Learning - Kernel methods, Filtering
  • Hannes Saal, Nicolas Heess and Sethu Vijayakumar,
    Multimodal Nonlinear Filtering using Gauss-Hermite Quadrature,
    Proc. 21st European Conference on Machine Learning (ECML PKDD 2011), Athen, Greece (2011). [pdf][poster]
  • Sethu Vijayakumar and Hidemitsu Ogawa,
    RKHS based Functional Analysis for Exact Incremental Learning
    Neurocomputing : Special Issue on Theoretical analysis of real valued function classes, Vol.29, No.1-3, pp.85-113, Elsevier Science (1999).
  • Sethu Vijayakumar and Hidemitsu Ogawa,
    Incremental Learning in Optimally Generalizing Neural Networks,
    IEICE Annual Paper Contest 1996, No.D-27, p.27 (1996).
  • Sethu Vijayakumar and Hidemitsu Ogawa,
    A Functional Analytic Approach to Incremental Learning in Optimally Generalizing NNs,
    Proc. IEEE International Conference on Neural Networks (ICNN '95), Australia, vol. 2, pp.777-782 (1995).[doi]
  • Sethu Vijayakumar and Hidemitsu Ogawa,
    Incremental Learning with Optimal Generalizing Ability in Neural Networks,
    Technical Report of the IEICE, NC95-9, pp.65-72 (1995).
 Context Estimation, Switching Models and Control
  • Kian Ming Chai, Stefan Klanke, Chris Williams and Sethu Vijayakumar,
    Multi-task Gaussian Process Learning of Robot Inverse Dynamics,
    Proc. Advances in Neural Information Processing Systems (NIPS '08), Vancouver, Canada (2008).[pdf] [spotlight]
  • Heiko Hoffmann, Georgios Petkos, Sebastian Bitzer and Sethu Vijayakumar,
    Sensor Assisted Adaptive Motor Control under continuously varying Context,
    Proc. International Conference on Informatics in Control, Automation and Robotics (ICINCO '07), Angers, France (2007). [pdf]
  • Georgios Petkos and Sethu Vijayakumar,
    Context Estimation and Learning Control through Latent Variable Extraction: From discrete to continuous contexts, Proc. IEEE International Conference on Robotics and Automation (ICRA '07), Rome, Italy (2007). [pdf]
  • Georgios Petkos, Marc Toussaint and Sethu Vijayakumar,
    Learning Multiple Models of Non-Linear Dynamics for Control under Varying Contexts,
    Proc. International Conference on Artificial Neural Networks (ICANN '06), Athens, Greece (2006). [pdf]
  • Marc Toussaint and Sethu Vijayakumar,
    Learning Discontinuities with Product-of-Sigmoids for Switching between Local Models,
    Proc. 22nd. International Conference on Machine Learning (ICML'05), Bonn, Germany, Aug 7-11 (2005).[pdf]
  • Marc Toussaint and Sethu Vijayakumar,
    Learning Discontinuities for Switching between Local Models,
    Proc. 19th. International Joint Conference on Artificial Intelligence (IJCAI '05), Edinburgh, UK (2005).[pdf]
     
Variable Impedance Actuation
  • Jun Nakanishi and Sethu Vijayakumar,
    Exploiting Passive Dynamics with Variable Stiffness Actuation in Robot Brachiation,
    Proc. Robotics: Science and Systems (R:SS 2012), Sydney, Australia (2012). [pdf][video]
  • Andreaa Radulescu, Matthew Howard, David Braun and Sethu Vijayakumar,
    Exploiting Variable Physical Damping in Rapid Movement Tasks,
    Proc. 2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Taiwan (2012). [pdf][video]
  • Jun Nakanishi, Konrad Rawlik and Sethu Vijayakumar,
    Stiffness and Temporal Optimization in Periodic Movements: An Optimal Control Approach,
    Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS 2011), San Francisco (2011). [pdf][video]
  • David Braun, Matthew Howard and Sethu Vijayakumar,
    Exploiting Variable Stiffness in Explosive Movement Tasks    ,
    Proc. Robotics: Science and Systems (R:SS 2011), Los Angeles, CA, USA (2011)    . [pdf][video][video-2link]
  • Djordje Mitrovic, Stefan Klanke and Sethu Vijayakumar,
    Learning Impedance Control of Antagonistic Systems based on Stochastic Optimisation Principles, International Journal of Robotic Research    , Vol. 30, No. 5, pp. 556-573 (2011). [pdf][DOI]
  • Matthew Howard, David Braun and Sethu Vijayakumar,
    Constraint-based Equilibrium and Stiffness Control of Variable Stiffness Actuators    ,
    Proc. IEEE International Conference on Robotics and Automation (ICRA 2011), Shanghai, China (2011)    . [pdf]
  • Djordje Mitrovic, Stefan Klanke, Rieko Osu, Mitsuo Kawato and Sethu Vijayakumar,
    A Computational Model of Limb Impedance Control based on Principles of Internal Model Uncertainty,
    PLoS ONE, Vol. 5, No. 10 (2010). [pdf][DOI]
  • Matthew Howard, Djordje Mitrovic and Sethu Vijayakumar,
    Transferring Impedance Control Strategies Between Heterogeneous Systems via Apprenticeship Learning    ,
    Proc. 2010 IEEE-RAS International Conference on Humanoid Robots, Nashville, TN, USA (2010). [pdf] [poster]
  • Djordje Mitrovic, Stefan Klanke, Matthew Howard and Sethu Vijayakumar,
    Exploiting Sensorimotor Stochasticity for Learning Control of Variable Impedance Actuators,
    Proc. 2010 IEEE-RAS International Conference on Humanoid Robots, Nashville, TN, USA (2010). [pdf] [poster]
  • Djordje Mitrovic, Stefan Klanke, Adrian Haith and Sethu Vijayakumar,
    A Theory of Impedance Control based on Internal Model Uncertainty,
    Proc. ESF Intl. Workshop on Computational Principles of Sensorimotor Learning, Irsee, Germany (2009).[pdf]
 Reinforcement Learning, Direct Policy Learning and Optimal Control
  • Konrad Rawlik, Marc Toussaint and Sethu Vijayakumar,
    On Stochastic Optimal Control and Reinforcement Learning by Approximate Inference,
    Proc. Robotics: Science and Systems (R:SS 2012), Sydney, Australia (2012). [pdf]
  • Takeshi Mori, Matthew Howard and Sethu Vijayakumar,
    Model Free Apprenticeship Learning for Transfer of Human Impedance Behaviour,
    Proc. 11th IEEE-RAS International Conference on Humanoid Robots, Bled, Slovenia (2011). [pdf]
  • Konrad Rawlik, Marc Toussaint and Sethu Vijayakumar,
    An Approximate Inference Approach to Temporal Optimization in Optimal Control,
    Proc. Advances in Neural Information Processing Systems (NIPS '10), Vancouver, Canada (2010).[pdf][poster]
  • Chris Towell, Matthew Howard and Sethu Vijayakumar,
    Learning Nullspace Policies,
    Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS 2010), Taiwan (2010). [pdf][video]
  • Djordje Mitrovic, Sho Nagashima, Stefan Klanke, Takamitsu Matsubara and Sethu Vijayakumar,
    Optimal Feedback Control for Anthropomorphic Manipulatorss,
    Proc. IEEE International Conference on Robotics and Automation (ICRA 2010), Anchorage, Alaska, USA (2010). [pdf]
  • Matthew Howard, Stefan Klanke, Michael Gienger, Christian Goerick and Sethu Vijayakumar,
    Methods for Learning Control Policies from Variable Constraint Demonstrations,
    In: O. Sigaud and J. Peters (eds.): From Motor Learning to Interaction Learning in Robots, SCI 264, pp. 253-291, Springer-Verlag (2010). [pdf]
  • Djordje Mitrovic, Stefan Klanke and Sethu Vijayakumar,
    Adaptive Optimal Feedback Control with Learned Internal Dynamics Models,
    In: O. Sigaud and J. Peters (eds.): From Motor Learning to Interaction Learning in Robots, SCI 264, pp. 65-84, Springer-Verlag (2010). [pdf]
  • Matthew Howard, Stefan Klanke, Michael Gienger, Christian Goerick and Sethu Vijayakumar,
    A novel method for learning policies from variable constraint data,
    Autonomous Robots, vol. 27, pp. 105-121 (2009). [pdf][ASIMO car wash video]
  • Matthew Howard, Stefan Klanke, Michael Gienger, Christian Goerick and Sethu Vijayakumar,
    Robust Constraint-consistent Learning,
    Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '09), St. Louis, MO, USA (2009). [pdf]
  • Matthew Howard, Stefan Klanke, Michael Gienger, Christian Goerick and Sethu Vijayakumar,
    A Novel Method for Learning Policies from Constrained Motion,
    Proc. IEEE International Conference on Robotics and Automation (ICRA '09), Kobe, Japan (2009). [pdf]
  • Matthew Howard, Stefan Klanke, Michael Gienger, Christian Goerick and Sethu Vijayakumar,
    Behaviour Generation in Humanoids by Learning Potential-based Policies from Constrained Motion,
    Applied Bionics and Biomechanics, Vol. 5, No. 4, pp.195-211, Taylor and Francis (2008). [pdf][video]
  • Matthew Howard, Stefan Klanke, Michael Gienger, Christian Goerick and Sethu Vijayakumar,
    Learning Potential-based Policies from Constrained Motion,
    Proc. 8th IEEE-RAS International Conference on Humanoid Robots (Humanoids), Dejong, Korea (2008) [pdf]
  • Djordje Mitrovic, Stefan Klanke, Sethu Vijayakumar,
    Adaptive Optimal Control for Redundantly Actuated Arms,
    Proc. Tenth International Conference on the Simulation of Adaptive Behavior (SAB '08), Osaka, Japan (2008). [pdf]
  • Masashi Sugiyama, Hirotaka Hachiya, Christopher Towell and Sethu Vijayakumar,
    Geodesic Gaussian kernels for value function approximation,
    Autonomous Robots, Vol. 25, pp. 287-304 (2008). [pdf][DOI]
  • Djordje Mitrovic, Stefan Klanke, Sethu Vijayakumar,
    Optimal control with adaptive internal dynamics models,
    Proc. Fifth International Conference on Informatics in Control, Automation and Robotics (ICINCO '08),  Madeira, Portugal (2008). [pdf]
  • Djordje Mitrovic, Stefan Klanke, Sethu Vijayakumar,
    Optimal control with adaptive internal dynamics models,
    In: Robotics Challenges for Machine Learning, Neural Information Processing Systems (NIPS 2007),  Whistler, Canada (2007). [poster]
  • Matthew Howard and Sethu Vijayakumar,
    Reconstructing Null-space Policies Subject to Dynamic Task Constraints in Redundant Manipulators,
    Proc. Workshop on Robotics and Mathematics (ROBOMAT '07), Coimbra, Portugal (2007). [pdf]
  • Masashi Sugiyama, Hirotaka Hachiya, Christopher Towell and Sethu Vijayakumar,
    Value Function Approximation on Non-Linear Manifolds for Robot Motor Control,
    Proc. IEEE International Conference on Robotics and Automation (ICRA '07), Rome, Italy (2007). [pdf]
  • Matthew Howard , Michael Gienger, Christian Goerick and Sethu Vijayakumar,
    Learning Utility Surfaces for Movement Selection,
    Proc. IEEE International Conference on Robotics and Biomimetics (ROBIO), Kunmin, China (2006). [pdf]
  • Masashi Sugiyama, Hirotaka Hachiya, Christopher Towell and Sethu Vijayakumar,
    Geodesic Gaussian kernels for value function approximation,
    Proc. 2006 Workshop on Information-Based Induction Sciences (IBIS), Osaka, Japan, (2006).[pdf]
  • Jan Peters, Sethu Vijayakumar, Stefan Schaal,
    Natural Actor-Critic,
    (in) Gama, J.;Camacho, R., Brazdil, P., Jorge, A.Torgo, L. (eds.) Proc. 16th European Conference on Machine Learning (ECML '05), Porto, Portugal, 3720, pp.280-291, Springer (2005). [pdf]
  • Jan Peters, Sethu Vijayakumar, and Stefan Schaal,
    Learning Motor Primitives with Reinforcement Learning,
    Proc. 11th Joint Symposium on Neural Computation (2004).
  • Jan Peters, Sethu Vijayakumar, Stefan Schaal,
    Natural Actor-Critic,
    (in) Proc. Advances in Neural Information Processing Systems 16 Workshop ''Planning for the Real World: The promises and challenges of dealing with uncertainty'' (2003).
  • Jan Peters, Sethu Vijayakumar, and Stefan Schaal,
    Reinforcement Learning for Humanoid Robots - policy gradients and beyond,
    Proc. Third IEEE International Conference on Humanoid Robotics 2003, Germany. [pdf]
  • Jan Peters, Sethu Vijayakumar, and Stefan Schaal,,
    Scaling Reinforcement Learning Paradigms for Motor Control,
    Proc. 10th Joint Symposium on Neural Computation, UC Irvine, May 17 (2003).[abstract]
  Real Time Learning for Robot Control & High Dimensional Systems
  • Jo-Anne-Ting, Sethu Vijayakumar and Stefan Schaal,
    Locally Weighted Regression for Control,
    In: Sammut, C. and Webb, G. I. (Eds.) Encyclopaedia of Machine Learning    , pp. 613-624, Springer (2010). [pdf]
  • Sethu Vijayakumar, Marc Toussaint, Georgios Petkos and Matthew Howard,
    Planning and Moving in Dynamic Environments: A statistical machine learning approach,
    in (eds.) Sendhoff, Koerner, Sporns, Ritter, Doya, Creating Brain Like Intelligence: From Principles to Complex Intelligent Systems, LNAI-Vol. 5436, Springer-Verlag ISBN: 978-3-642-00615-9 (2009). [pdf]
  • Georgios Petkos and Sethu Vijayakumar,
    Load estimation and control using learned dynamics models,
    Proc. IEEE International Conference on Intelligent Robots and Systems (IROS '07), San Diego, CA (2007). [pdf]
  • Sethu Vijayakumar, Aaron D'Souza, Tomohiro Shibata, Jorg Conradt and Stefan Schaal,
    Statistical Learning for Humanoid Robots,
    Autonomous Robot , Vol. 12, No.1, pp. 55-69 (2002).
  • Stefan Schaal, Chris Atkeson and Sethu Vijayakumar,
    Scalable Locally Weighted Statistical Techniques for Real Time Robot Learning,
    Applied Intelligence - Special issue on Scalable Robotic Applications of Neural Networks Vol. 17, No.1, pp.49-60 (2002).
  • Stefan Schaal, Sethu Vijayakumar, Aaron D'Souza, Auke Ijspeert and Jun Nakanishi,
    Real-time statistical learning for robotics and human augmentation,
    Proc. Tenth International Symposium on Robotics Research(ISRR), Victoria, Australia, pp. 117-124 (2001). [pdf].
  • Aaron D'Souza, Sethu Vijayakumar and Stefan Schaal,
    Learning Inverse Kinematics
    Proc. International Conference on Intelligence in Robotics and Autonomous Systems (IROS 2001), Hawaii, pp. 298-303 (2001) [pdf] [gzip-ed ps] .
  • Stefan Schaal, Sethu Vijayakumar and Aaron D'Souza,
    Online Statistical Robot Learning,
    Journal of the Robotics Society of Japan , Vol.19, No.5, pp.561-568(2001).
  • Sethu Vijayakumar and Stefan Schaal,
    Real Time Learning in Humanoids: A challenge for scalability of Online Algorithms,
    Humanoids2000, First IEEE-RAS Intl. Conf. on Humanoid Robots MIT,Cambridge, MA, USA (2000), CD Proceedings: http://www-slab.usc.edu/sethu/publications/humanoids00.pdf [pdf].
  • Chris Atkeson, Josh Hale, Mitsuo Kawato, Shinya Kotosaka, Frank Pollick, Marcia Riley, Stefan Schaal, Tomohiro Shibata, Gaurav Tevatia, Ales Ude and Sethu Vijayakumar,
    Using Humanoid Robots to Study Human Behaviour,
    IEEE Intelligent Systems, Vol.15, No.4, pp.46-56, IEEE Computer Society(2000).
  • Jorg Conradt, Gaurav Tevatia, Sethu Vijayakumar and Stefan Schaal,
    Online Learning for Humanoid Robot Systems,
    Proc. of Seventeenth International Conference on Machine Learning (ICML2000) Stanford, California, pp.191-198 (2000) [pdf] [gzip-ed ps].
  • Stefan Schaal, Chris Atkeson and Sethu Vijayakumar,
    Real time robot learning with locally weighted statistical learning,
    Proc. International Conference on Robotics and Automation (ICRA2000), San Francisco, California, vol.1, pp.288-293,(2000). [pdf] [gzip-ed ps].
Visual Attention, Saliency Detection and Oculomotor control
  • Adrian Haith and Sethu Vijayakumar,
    Implications of different classes of sensorimotor disturbance for cerebellar-based motor learning models,
    Biological Cybernetics, Springer-Verlag (2008).[pdf]
  • Adrian Haith and Sethu Vijayakumar,
    Robustness of VOR and OKR adaptation under kinematics and dynamics transformations,
    Proc. Sixth IEEE international Conference on Development and Learning (ICDL '07), London, UK (2007). [pdf]
  • Sethu Vijayakumar, Aaron D'Souza, Jan Peters, Jorg Conradt, Tomasz Rutkowski, Auke Ijspeert, Jun Nakanishi, Masato Inoue, Tom Shibata, Arleen Wiryo, Laurent Itti, Shun-ichi Amari and Stefan Schaal,
    Real-Time Statistical Learning for Oculomotor Control and Visuomotor Coordination,
    Proc. Neural Information Processing Systems (NIPS 15)- DemonstrationTrack (2002).
  • Tomohiro Shibata, Sethu Vijayakumar, Jorg Conradt and Stefan Schaal,
    Biomimetic Oculomotor Control,
    Adaptive Behaviour - Special Issue on Biologically Inspired and Biomimetic Systems, vol.9, No.3-4, pp. 189-208 (2001).[pdf] [gzip-ed ps]
  • Tomohiro Shibata, Sethu Vijayakumar, Jorg Conradt and Stefan Schaal,
    Humanoid Oculomotor Control Based on Concepts of Computational Neuroscience,
    Humanoids2001, Second IEEE-RAS Intl. Conf. on Humanoid Robots, Waseda Univ., Japan, pp. 278-285 (2001). [pdf] [gzip-ed ps] .
  • Sethu Vijayakumar, Jorg Conradt, Tomohiro Shibata and Stefan Schaal,
    Overt Visual Attention for a Humanoid Robot,
    Proc. International Conference on Intelligence in Robotics and Autonomous Systems (IROS 2001), Hawaii, pp.2332-2337 (2001) [pdf] [gzip-ed ps]
 Bayesian Decision Making in Human Sensorimotor Control
  • Ian Saunders and Sethu Vijayakumar,
    Continuous Evolution of Statistical Estimators for Optimal Decision-Making,
     PLoS ONE (in press). [pdf][DOI]
  • Sethu Vijayakumar, Timothy Hospedales and Adrian Haith,
    Generative Probabilistic Modeling: Understanding Causal Sensorimotor Integration,
    In Trommershauser, Kording & Landy (Eds), Sensory Cue Integration, pp. 63-81, Oxford University Press (2011) [OUP][preprint]
  • Luigi Acerbi and Sethu Vijayakumar,
    Bayesian Causal Inference Drives Temporal Sensorimotor Recalibration,
    Proc. Computational and Systems Neuroscience COSYNE '11,  Salt Lake City, Utah (2011). [abstract] [poster]
  • Ian Saunders and Sethu Vijayakumar,
    A Closed Loop Prosthetic Hand as a Model Sensorimotor Circuit,
    Proc. ESF Intl. Workshop on Computational Principles of Sensorimotor Learning, Irsee, Germany (2009). [pdf]
  • Timothy Hospedales and Sethu Vijayakumar,
    Multisensory Oddity Detection as Bayesian Inference,
    PLoS ONE, Vol. 4, No. 1 (2009). [pdf][DOI]
  • Adrian Haith, Carl Jackson, Chris Miall and Sethu Vijayakumar,
    Unifying the Sensory and Motor Components of Sensorimotor Adaptation,
    Proc. Advances in Neural Information Processing Systems (NIPS '08), Vancouver, Canada (2008).[pdf] [spotlight, audio]
  • Adrian Haith, Carl Jackson, Chris Miall and Sethu Vijayakumar,
    Interactions between sensory and motor components of adaptation predicted by a Bayesian model,
    In: Workshop on Advances in Computational Motor Control (ACMC 2008), Society for Neuroscience Meeting, Washington DC (2008).[pdf]
  • Adrian Haith and Sethu Vijayakumar,
    A Bayesian Model of Multimodal Visuo-motor Adaptation,
    Proc. 18th Meeting of the Society for Neural Control of Movement (NCM 2008), Florida, USA (2008). [poster]
  • Timothy Hospedales and Sethu Vijayakumar,
    Bayesian Structure Inference for Multisensory Scene Understanding,
    IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 12, pp. 2140-2157 (2008). [pdf][DOI]
  • Timothy Hospedales, Joel Cartwright and Sethu Vijayakumar,
    Structure Inference for Bayesian Multisensory Perception and Tracking,
    Proc. International Joint Conference on Artificial Intelligence (IJCAI '07), Hyderabad, India (2007). [pdf]
 Haptics: Encoding, Discrimination and Prosthetic Applications
  • Ian Saunders and Sethu Vijayakumar,
    The Role of Feed-Forward and Feedback Processes for Closed-Loop Prosthesis Control, 
    Journal of Neuroengineering and Rehabilitation (JNER)    , 8:60 (2011). [pdf][DOI]
  • Hannes Saal, Jo-Anne-Ting and Sethu Vijayakumar,
    Active Estimation of Object Dynamics Parameters with Tactile Sensors,
    Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS 2010), Taiwan (2010). [pdf][video]
  • Hannes Saal, Jo-Anne-Ting and Sethu Vijayakumar,
    Active sequential learning with tactile feedback,
    In: Teh YW and Titterington M (Eds.), Proc. 13th Int. Conf. on Artificial Intelligence and Statistics (AISTATS 2010), JMLR: W&CP 9:677-684, Chia Laguna, Sardinia, Italy (2010). [pdf]
  • Hannes Saal, Jo-Anne-Ting and Sethu Vijayakumar,
    Active Filtering for Robot Tactile Learning,
    In: Workshop on Adaptive Sensing, Active Learning, and Experimental Design, Neural Information Processing Systems (NIPS 2009), Whistler, Canada (2009). [pdf]
  • Hannes Saal, Sethu Vijayakumar and Roland Johansson,
    Information about Complex Fingertip Parameters in Individual Human Tactile Afferent neurons,
    The Journal of Neuroscience, 29(25):8022-8031, (2009). [pdf]
  • Hannes Saal, Roland Johansson and Sethu Vijayakumar,
    Spatiotemporal distribution of tactile information across the human fingertip,
    Proc. Sixth Forum of European Neuroscience (FENS 2008), Geneva, Switzerland (2008). [poster]
  • Hannes Saal, Sethu Vijayakumar and Roland Johansson,
    Information about present and past stimulus features in human tactile afferents,
    Proc. Computational and Systems Neuroscience COSYNE '08,  Salt Lake City, Utah (2008).    [poster]  
 Information Retrieval & Shape Analysis
  • Graham McNeill and Sethu Vijayakumar,
    Linear and Nonlinear Generative Probabilistic Class Models for Shape Contours,
    Proc. International Conference on Machine Learning (ICML '07), Oregon, USA (2007). [pdf]
  • Graham McNeill and Sethu Vijayakumar,
    Part-based Probabilistic Point Matching Using Equivalence Constraints,
    Proc. Advances in Neural Information Processing Systems (NIPS '06), Vancouver, Canada (2006). [pdf]
  • Graham McNeill and Sethu Vijayakumar,
    Part-based Probabilistic Point Matching,
    Proc. International Conference on Pattern Recognition (ICPR '06), Hong Kong (2006). [pdf]
  • Graham McNeill and Sethu Vijayakumar,
    A Probabilistic Approach To Robust Shape Matching,
    Proc. International Conference on Image Processing (ICIP '06), Atlanta, GA (2006). [pdf]
  • Graham McNeill and Sethu Vijayakumar,
    Hierarchical Procrustes Matching for Shape Retrieval,
    Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR '06), New York (2006). [pdf]
  • Graham McNeill and Sethu Vijayakumar,
    2D Shape Classification and Retrieval,
    Proc. 19th. International Joint Conference on Artificial Intelligence (IJCAI '05),     Edinburgh, UK (2005).[pdf]
Topology Spaces and Dimensionality Reduction for Planning & Control
  • Dmitry Zarubin, Vladimir Ivan, Taku Komura, Marc Toussaint and Sethu Vijayakumar,
    Hierarchical Motion Planning in Topological Spaces,
    Proc. Robotics: Science and Systems (R:SS 2012), Sydney, Australia (2012). [pdf][video]
  • Edmond Ho, Taku Komura, Subramanian Ramamoorthy and Sethu Vijayakumar,
    Controlling Humanoid Robots in Topology Coordinates,
    Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS 2010), Taiwan (2010). [pdf]
  • Sebastian Bitzer, Matthew Howard and Sethu Vijayakumar,
    Using Dimensionality Reduction to Exploit Constraints in Reinforcement Learning,
    Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS 2010), Taiwan (2010). [pdf][video]
  • Sebastian Bitzer and Sethu Vijayakumar,
    Latent Spaces for Dynamic Movement Primitives,
    Proc. 9th IEEE RAS International Conference on humanoid Robots (Humanoids ’09), Paris, France (2009). [pdf]
  • Jan Steffen, Stefan Klanke, Sethu Vijayakumar and Helge Ritter,
    Towards Semi-supervised Manifold Learning: UKR with Structural Hints,
    Proc. 7th International Workshop on Self Organizing Maps (WSOM’09), Florida, USA (2009). [pdf]
  • Sebastian Bitzer, Stefan Klanke and Sethu Vijayakumar,
    Does Dimensionality Reduction improve the Quality of Motion Interpolation?,
    Proc. 17th European Symposium on Artificial Neural Networks (ESANN ’09), Bruges, Belgium (2009). [pdf]
  • Jan Steffen, Stefan Klanke, Sethu Vijayakumar and Helge Ritter,
    Realizing Dexterous Manipulation with Structured Manifolds using Unsupervised Kernel Regression with Structural Hints,
    In Workshop: Approaches to Sensorimotor Learning on Humanoid Robots, IEEE International Conference on Robotics and Automation (ICRA '09), Kobe, Japan (2009). [pdf]
  • Heiko Hoffmann, Stefan Schaal and Sethu Vijayakumar,
    Local Dimensionality Reduction for Nonparametric Regression,
    Neural Processing Letters, , 29: 109-131, (2009). [pdf]
  • Sebastian Bitzer, Ioannis Havoutis and Sethu Vijayakumar,
    Synthesising Novel Movements through Latent Space Modulation of Scalable Control Policies,
    Asada et. al (eds.) Proc. Tenth International Conference on the Simulation of Adaptive Behavior (SAB '08), Springer-Verlag LNAI 5040, pp. 199-209, Osaka, Japan (2008). [pdf]
  • Aaron D'Souza, Sethu Vijayakumar and Stefan Schaal,
    Are Internal Models of the Entire Body Learnable?
    In: Society for Neuroscience Abstracts. Vol. 27, Program No. 406.2, (2001). [abstract]
  • Stefan Schaal, Sethu Vijayakumar and Chris Atkeson,
    Local Dimensionality Reduction,
    In: M. I. Jordan, M. J. Kearns, and S. A. Solla (eds.), Advances in Neural Information Processing Systems 10, pp.633-639, Cambridge, MA: MIT Press(1998). [pdf] [gzip-ed ps]
  • Sethu Vijayakumar and Stefan Schaal,
    Local Dimensionality Reduction for Locally Weighted Learning,
    Proc. IEEE International Symposium on Computational Intelligence in Robotics and Automation, (CIRA'97), July 10-11,1997,Monterey, California, pp.220-225 (1997). [pdf] [gzip-ed ps]
Sparse Representation and Active Learning
  • Phillip Robbel, Marc Toussaint and Sethu Vijayakumar,
    Active Learning in Motor Control,
    In: Robotics Challenges for Machine Learning, Neural Information Processing Systems (NIPS 2007), Whistler, Canada (2007).
  • Sethu Vijayakumar and Si Wu,
    A gradient based technique for generating sparse representation in function approximation,
    Proc. International Conference on Neural Information processing (ICONIP'99), Perth, Australia, pp.314-319 (1999). [pdf] [gzip-ed ps]
  • Sethu Vijayakumar and Si Wu,
    Sequential Support Vector Classifiers and Regression,
    Proc. International Conference on Soft Computing (SOCO'99),Genoa, Italy, pp.610-619 (1999). [pdf] [gzip-ed ps]
  • Sethu Vijayakumar and Hidemitsu Ogawa,
    Improving Generalization Ability through Active Learning,
    IEICE Transactions on Information and Systems IEICE-Japan, Vol.E82-D, No.2, pp.480-487(1999). [pdf] [gzip-ed ps]
  • Sethu Vijayakumar, Masashi Sugiyama and Hidemitsu Ogawa,
    Training Data Selection for Optimal Generalization with Noise Variance Reduction in Neural Networks,
    In: Marinaro & Tagliaferri(ed.), Neural Nets WIRN Vietri-98,,pp.153-166, Springer-Verlag(1998). [pdf] [gzip-ed ps]
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