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2009


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A Limiting Property of the Matrix Exponential with Application to Multi-loop Control

Trimpe, S., D’Andrea, R.

In Proceedings of the Joint 48th IEEE Conference on Decision (CDC) and Control and 28th Chinese Control Conference, 2009 (inproceedings)

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PDF DOI [BibTex]

2009


PDF DOI [BibTex]


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Haptic Display of Realistic Tool Contact Via Dynamically Compensated Control of a Dedicated Actuator

McMahan, W., Kuchenbecker, K. J.

In Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 3171-3177, St. Louis, Missouri, USA, 2009, Oral presentation given by McMahan (inproceedings)

hi

[BibTex]

[BibTex]


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Characterization of bacterial actuation of micro-objects

Behkam, B., Sitti, M.

In Robotics and Automation, 2009. ICRA’09. IEEE International Conference on, pages: 1022-1027, 2009 (inproceedings)

pi

[BibTex]

[BibTex]


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Compliant footpad design analysis for a bio-inspired quadruped amphibious robot

Park, H. S., Sitti, M.

In Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on, pages: 645-651, 2009 (inproceedings)

pi

[BibTex]

[BibTex]


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Path integral-based stochastic optimal control for rigid body dynamics

Theodorou, E. A., Buchli, J., Schaal, S.

In Adaptive Dynamic Programming and Reinforcement Learning, 2009. ADPRL ’09. IEEE Symposium on, pages: 219-225, 2009, clmc (inproceedings)

Abstract
Recent advances on path integral stochastic optimal control [1],[2] provide new insights in the optimal control of nonlinear stochastic systems which are linear in the controls, with state independent and time invariant control transition matrix. Under these assumptions, the Hamilton-Jacobi-Bellman (HJB) equation is formulated and linearized with the use of the logarithmic transformation of the optimal value function. The resulting HJB is a linear second order partial differential equation which is solved by an approximation based on the Feynman-Kac formula [3]. In this work we review the theory of path integral control and derive the linearized HJB equation for systems with state dependent control transition matrix. In addition we derive the path integral formulation for the general class of systems with state dimensionality that is higher than the dimensionality of the controls. Furthermore, by means of a modified inverse dynamics controller, we apply path integral stochastic optimal control over the new control space. Simulations illustrate the theoretical results. Future developments and extensions are discussed.

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link (url) [BibTex]

link (url) [BibTex]


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Learning locomotion over rough terrain using terrain templates

Kalakrishnan, M., Buchli, J., Pastor, P., Schaal, S.

In Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on, pages: 167-172, 2009, clmc (inproceedings)

Abstract
We address the problem of foothold selection in robotic legged locomotion over very rough terrain. The difficulty of the problem we address here is comparable to that of human rock-climbing, where foot/hand-hold selection is one of the most critical aspects. Previous work in this domain typically involves defining a reward function over footholds as a weighted linear combination of terrain features. However, a significant amount of effort needs to be spent in designing these features in order to model more complex decision functions, and hand-tuning their weights is not a trivial task. We propose the use of terrain templates, which are discretized height maps of the terrain under a foothold on different length scales, as an alternative to manually designed features. We describe an algorithm that can simultaneously learn a small set of templates and a foothold ranking function using these templates, from expert-demonstrated footholds. Using the LittleDog quadruped robot, we experimentally show that the use of terrain templates can produce complex ranking functions with higher performance than standard terrain features, and improved generalization to unseen terrain.

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link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Integrating indoor mobility, object manipulation, and intuitive interaction for domestic service tasks

Stueckler, J., Behnke, S.

In Proc. of the IEEE-RAS Int. Conf. on Humanoid Robots (Humanoids), pages: 506-513, December 2009 (inproceedings)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


Thumb xl tracking iccv09
Segmentation, Ordering and Multi-object Tracking Using Graphical Models

Wang, C., Gorce, M. D. L., Paragios, N.

In IEEE International Conference on Computer Vision (ICCV), 2009 (inproceedings)

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pdf [BibTex]

pdf [BibTex]


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Evaluating the potential of primary motor and premotor cortex for mutltidimensional neuroprosthetic control of complete reaching and grasping actions

Vargas-Irwin, C. E., Yadollahpour, P., Shakhnarovich, G., Black, M. J., Donoghue, J. P.

2009 Abstract Viewer and Itinerary Planner. Society for Neuroscience, Society for Neuroscience, 2009, Online (conference)

ps

[BibTex]

[BibTex]


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Modelling the interplay of central pattern generation and sensory feedback in the neuromuscular control of running

Daley, M., Righetti, L., Ijspeert, A.

In Comparative Biochemistry and Physiology - Part A: Molecular & Integrative Physiology. Annual Main Meeting for the Society for Experimental Biology, 153, Glasgow, Scotland, 2009 (inproceedings)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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A novel artificial hair receptor based on aligned PVDF micro/nano fibers

Weiting, Liu, Bilsay, Sumer, Cesare, Stefanini, Arianna, Menciassi, Fei, Li, Dajing, Chen, Paolo, Dario, Metin, Sitti, Xin, Fu

In Robotics and Biomimetics, 2008. ROBIO 2008. IEEE International Conference on, pages: 49-54, 2009 (inproceedings)

pi

[BibTex]

[BibTex]


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Waalbot: Agile climbing with synthetic fibrillar dry adhesives

Murphy, M. P., Sitti, M.

In Robotics and Automation, 2009. ICRA’09. IEEE International Conference on, pages: 1599-1600, 2009 (inproceedings)

pi

[BibTex]

[BibTex]


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Compact models of motor primitive variations for predictible reaching and obstacle avoidance

Stulp, F., Oztop, E., Pastor, P., Beetz, M., Schaal, S.

In IEEE-RAS International Conference on Humanoid Robots (Humanoids 2009), Paris, Dec.7-10, 2009, clmc (inproceedings)

Abstract
over and over again. This regularity allows humans and robots to reuse existing solutions for known recurring tasks. We expect that reusing a set of standard solutions to solve similar tasks will facilitate the design and on-line adaptation of the control systems of robots operating in human environments. In this paper, we derive a set of standard solutions for reaching behavior from human motion data. We also derive stereotypical reaching trajectories for variations of the task, in which obstacles are present. These stereotypical trajectories are then compactly represented with Dynamic Movement Primitives. On the humanoid robot Sarcos CB, this approach leads to reproducible, predictable, and human-like reaching motions.

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link (url) [BibTex]

link (url) [BibTex]


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Human optimization strategies under reward feedback

Hoffmann, H., Theodorou, E., Schaal, S.

In Abstracts of Neural Control of Movement Conference (NCM 2009), Waikoloa, Hawaii, 2009, 2009, clmc (inproceedings)

Abstract
Many hypothesis on human movement generation have been cast into an optimization framework, implying that movements are adapted to optimize a single quantity, like, e.g., jerk, end-point variance, or control cost. However, we still do not understand how humans actually learn when given only a cost or reward feedback at the end of a movement. Such a reinforcement learning setting has been extensively explored theoretically in engineering and computer science, but in human movement control, hardly any experiment studied movement learning under reward feedback. We present experiments probing which computational strategies humans use to optimize a movement under a continuous reward function. We present two experimental paradigms. The first paradigm mimics a ball-hitting task. Subjects (n=12) sat in front of a computer screen and moved a stylus on a tablet towards an unknown target. This target was located on a line that the subjects had to cross. During the movement, visual feedback was suppressed. After the movement, a reward was displayed graphically as a colored bar. As reward, we used a Gaussian function of the distance between the target location and the point of line crossing. We chose such a function since in sensorimotor tasks, the cost or loss function that humans seem to represent is close to an inverted Gaussian function (Koerding and Wolpert 2004). The second paradigm mimics pocket billiards. On the same experimental setup as above, the computer screen displayed a pocket (two bars), a white disk, and a green disk. The goal was to hit with the white disk the green disk (as in a billiard collision), such that the green disk moved into the pocket. Subjects (n=8) manipulated with the stylus the white disk to effectively choose start point and movement direction. Reward feedback was implicitly given as hitting or missing the pocket with the green disk. In both paradigms, subjects increased the average reward over trials. The surprising result was that in these experiments, humans seem to prefer a strategy that uses a reward-weighted average over previous movements instead of gradient ascent. The literature on reinforcement learning is dominated by gradient-ascent methods. However, our computer simulations and theoretical analysis revealed that reward-weighted averaging is the more robust choice given the amount of movement variance observed in humans. Apparently, humans choose an optimization strategy that is suitable for their own movement variance.

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[BibTex]

[BibTex]


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Dynamaid, an Anthropomorphic Robot for Research on Domestic Service Applications

Stueckler, J., Schreiber, M., Behnke, S.

In Proc. of the European Conference on Mobile Robots (ECMR), pages: 87-92, 2009 (inproceedings)

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link (url) [BibTex]

link (url) [BibTex]


Thumb xl thumb screen shot 2012 10 06 at 12.02.32 pm
Modeling and Evaluation of Human-to-Robot Mapping of Grasps

Romero, J., Kjellström, H., Kragic, D.

In International Conference on Advanced Robotics (ICAR), pages: 1-6, 2009 (inproceedings)

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Pdf [BibTex]

Pdf [BibTex]


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Piezoelectric ultrasonic resonant micromotor with a volume of less than 1 mm 3 for use in medical microbots

Watson, B., Friend, J., Yeo, L., Sitti, M.

In Robotics and Automation, 2009. ICRA’09. IEEE International Conference on, pages: 2225-2230, 2009 (inproceedings)

pi

[BibTex]

[BibTex]


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Dynamic modeling and analysis of pitch motion of a basilisk lizard inspired quadruped robot running on water

Park, H. S., Floyd, S., Sitti, M.

In Robotics and Automation, 2009. ICRA’09. IEEE International Conference on, pages: 2655-2660, 2009 (inproceedings)

pi

[BibTex]

[BibTex]


Thumb xl nips2009b
An additive latent feature model for transparent object recognition

Fritz, M., Black, M., Bradski, G., Karayev, S., Darrell, T.

In Advances in Neural Information Processing Systems 22, NIPS, pages: 558-566, MIT Press, 2009 (inproceedings)

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pdf slides [BibTex]

pdf slides [BibTex]


Thumb xl screen shot 2012 06 06 at 11.24.14 am
Let the kernel figure it out; Principled learning of pre-processing for kernel classifiers

Gehler, P., Nowozin, S.

In Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR), pages: 2836-2843, IEEE Computer Society, 2009 (inproceedings)

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doi project page pdf [BibTex]

doi project page pdf [BibTex]


Thumb xl thumb screen shot 2012 10 06 at 12.04.52 pm
Monocular Real-Time 3D Articulated Hand Pose Estimation

Romero, J., Kjellström, H., Kragic, D.

In IEEE-RAS International Conference on Humanoid Robots, pages: 87-92, 2009 (inproceedings)

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Pdf [BibTex]

Pdf [BibTex]


Thumb xl snap
Grasp Recognition and Mapping on Humanoid Robots

Do, M., Romero, J., Kjellström, H., Azad, P., Asfour, T., Kragic, D., Dillmann, R.

In IEEE-RAS International Conference on Humanoid Robots, pages: 465-471, 2009 (inproceedings)

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Pdf Video [BibTex]

Pdf Video [BibTex]


Thumb xl teaser wc
4D Cardiac Segmentation of the Epicardium and Left Ventricle

Pons-Moll, G., Tadmor, G., MacLeod, R. S., Rosenhahn, B., Brooks, D. H.

In World Congress of Medical Physics and Biomedical Engineering (WC), 2009 (inproceedings)

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[BibTex]

[BibTex]


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Geometric Potential Force for the Deformable Model

Si Yong Yeo, Xianghua Xie, Igor Sazonov, Perumal Nithiarasu

In The 20th British Machine Vision Conference, pages: 1-11, 2009 (inproceedings)

Abstract
We propose a new external force field for deformable models which can be conve- niently generalized to high dimensions. The external force field is based on hypothesized interactions between the relative geometries of the deformable model and image gradi- ents. The evolution of the deformable model is solved using the level set method. The dynamic interaction forces between the geometries can greatly improve the deformable model performance in acquiring complex geometries and highly concave boundaries, and in dealing with weak image edges. The new deformable model can handle arbi- trary cross-boundary initializations. Here, we show that the proposed method achieve significant improvements when compared against existing state-of-the-art techniques.

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[BibTex]

[BibTex]


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Learning and generalization of motor skills by learning from demonstration

Pastor, P., Hoffmann, H., Asfour, T., Schaal, S.

In International Conference on Robotics and Automation (ICRA2009), Kobe, Japan, May 12-19, 2009, 2009, clmc (inproceedings)

Abstract
We provide a general approach for learning robotic motor skills from human demonstration. To represent an observed movement, a non-linear differential equation is learned such that it reproduces this movement. Based on this representation, we build a library of movements by labeling each recorded movement according to task and context (e.g., grasping, placing, and releasing). Our differential equation is formulated such that generalization can be achieved simply by adapting a start and a goal parameter in the equation to the desired position values of a movement. For object manipulation, we present how our framework extends to the control of gripper orientation and finger position. The feasibility of our approach is demonstrated in simulation as well as on a real robot. The robot learned a pick-and-place operation and a water-serving task and could generalize these tasks to novel situations.

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link (url) [BibTex]

link (url) [BibTex]


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Compliant quadruped locomotion over rough terrain

Buchli, J., Kalakrishnan, M., Mistry, M., Pastor, P., Schaal, S.

In Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on, pages: 814-820, 2009, clmc (inproceedings)

Abstract
Many critical elements for statically stable walking for legged robots have been known for a long time, including stability criteria based on support polygons, good foothold selection, recovery strategies to name a few. All these criteria have to be accounted for in the planning as well as the control phase. Most legged robots usually employ high gain position control, which means that it is crucially important that the planned reference trajectories are a good match for the actual terrain, and that tracking is accurate. Such an approach leads to conservative controllers, i.e. relatively low speed, ground speed matching, etc. Not surprisingly such controllers are not very robust - they are not suited for the real world use outside of the laboratory where the knowledge of the world is limited and error prone. Thus, to achieve robust robotic locomotion in the archetypical domain of legged systems, namely complex rough terrain, where the size of the obstacles are in the order of leg length, additional elements are required. A possible solution to improve the robustness of legged locomotion is to maximize the compliance of the controller. While compliance is trivially achieved by reduced feedback gains, for terrain requiring precise foot placement (e.g. climbing rocks, walking over pegs or cracks) compliance cannot be introduced at the cost of inferior tracking. Thus, model-based control and - in contrast to passive dynamic walkers - active balance control is required. To achieve these objectives, in this paper we add two crucial elements to legged locomotion, i.e., floating-base inverse dynamics control and predictive force control, and we show that these elements increase robustness in face of unknown and unanticipated perturbations (e.g. obstacles). Furthermore, we introduce a novel line-based COG trajectory planner, which yields a simpler algorithm than traditional polygon based methods and creates the appropriate input to our control system.We show results from bot- h simulation and real world of a robotic dog walking over non-perceived obstacles and rocky terrain. The results prove the effectivity of the inverse dynamics/force controller. The presented results show that we have all elements needed for robust all-terrain locomotion, which should also generalize to other legged systems, e.g., humanoid robots.

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link (url) [BibTex]

link (url) [BibTex]


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A miniature ceiling walking robot with flat tacky elastomeric footpads

Unver, O., Sitti, M.

In Robotics and Automation, 2009. ICRA’09. IEEE International Conference on, pages: 2276-2281, 2009 (inproceedings)

pi

[BibTex]

[BibTex]


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Level Set Based Automatic Segmentation of Human Aorta

Si Yong Yeo, Xianghua Xie, Igor Sazonov, Perumal Nithiarasu

In International Conference on Computational & Mathematical Biomedical Engineering, pages: 242-245, 2009 (inproceedings)

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[BibTex]

[BibTex]


Thumb xl orthonormaity
In Defense of Orthonormality Constraints for Nonrigid Structure from Motion

Akhter, I., Sheikh, Y., Khan, S.

In Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on, pages: 2447-2453, 2009 (inproceedings)

Abstract
In factorization approaches to nonrigid structure from motion, the 3D shape of a deforming object is usually modeled as a linear combination of a small number of basis shapes. The original approach to simultaneously estimate the shape basis and nonrigid structure exploited orthonormality constraints for metric rectification. Recently, it has been asserted that structure recovery through orthonormality constraints alone is inherently ambiguous and cannot result in a unique solution. This assertion has been accepted as conventional wisdom and is the justification of many remedial heuristics in literature. Our key contribution is to prove that orthonormality constraints are in fact sufficient to recover the 3D structure from image observations alone. We characterize the true nature of the ambiguity in using orthonormality constraints for the shape basis and show that it has no impact on structure reconstruction. We conclude from our experimentation that the primary challenge in using shape basis for nonrigid structure from motion is the difficulty in the optimization problem rather than the ambiguity in orthonormality constraints.

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pdf [BibTex]

pdf [BibTex]


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Dynamic distortion correction for endoscopy systems with exchangeable optics

Stehle, T., Hennes, M., Gross, S., Behrens, A., Wulff, J., Aach, T.

In Bildverarbeitung für die Medizin 2009, pages: 142-146, Springer Berlin Heidelberg, 2009 (inproceedings)

Abstract
Endoscopic images are strongly affected by lens distortion caused by the use of wide angle lenses. In case of endoscopy systems with exchangeable optics, e.g. in bladder endoscopy or sinus endoscopy, the camera sensor and the optics do not form a rigid system but they can be shifted and rotated with respect to each other during an examination. This flexibility has a major impact on the location of the distortion centre as it is moved along with the optics. In this paper, we describe an algorithm for the dynamic correction of lens distortion in cystoscopy which is based on a one time calibration. For the compensation, we combine a conventional static method for distortion correction with an algorithm to detect the position and the orientation of the elliptic field of view. This enables us to estimate the position of the distortion centre according to the relative movement of camera and optics. Therewith, a distortion correction for arbitrary rotation angles and shifts becomes possible without performing static calibrations for every possible combination of shifts and angles beforehand.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Computational mechanisms for the recognition of time sequences of images in the visual cortex

Tan, C., Jhuang, H., Singer, J., Serre, T., Sheinberg, D., Poggio, T.

Society for Neuroscience, 2009 (conference)

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pdf [BibTex]

pdf [BibTex]


Thumb xl vriphys2009
Interactive Inverse Kinematics for Monocular Motion Estimation

Morten Engell-Norregaard, Soren Hauberg, Jerome Lapuyade, Kenny Erleben, Kim S. Pedersen

In The 6th Workshop on Virtual Reality Interaction and Physical Simulation (VRIPHYS), 2009 (inproceedings)

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Conference site Paper site [BibTex]

Conference site Paper site [BibTex]


Thumb xl thumb screen shot 2012 10 06 at 12.17.40 pm
A Comprehensive Grasp Taxonomy

Feix, T., Pawlik, R., Schmiedmayer, H., Romero, J., Kragic, D.

In Robotics, Science and Systems: Workshop on Understanding the Human Hand for Advancing Robotic Manipulation, 2009 (inproceedings)

ps

Pdf [BibTex]

Pdf [BibTex]


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Population coding of ground truth motion in natural scenes in the early visual system

Stanley, G., Black, M. J., Lewis, J., Desbordes, G., Jin, J., Alonso, J.

COSYNE, 2009 (conference)

ps

[BibTex]

[BibTex]


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Inertial parameter estimation of floating-base humanoid systems using partial force sensing

Mistry, M., Schaal, S., Yamane, K.

In IEEE-RAS International Conference on Humanoid Robots (Humanoids 2009), Paris, Dec.7-10, 2009, clmc (inproceedings)

Abstract
Recently, several controllers have been proposed for humanoid robots which rely on full-body dynamic models. The estimation of inertial parameters from data is a critical component for obtaining accurate models for control. However, floating base systems, such as humanoid robots, incur added challenges to this task (e.g. contact forces must be measured, contact states can change, etc.) In this work, we outline a theoretical framework for whole body inertial parameter estimation, including the unactuated floating base. Using a least squares minimization approach, conducted within the nullspace of unmeasured degrees of freedom, we are able to use a partial force sensor set for full-body estimation, e.g. using only joint torque sensors, allowing for estimation when contact force measurement is unavailable or unreliable (e.g. due to slipping, rolling contacts, etc.). We also propose how to determine the theoretical minimum force sensor set for full body estimation, and discuss the practical limitations of doing so.

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link (url) [BibTex]

link (url) [BibTex]


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Tankbot: A miniature, peeling based climber on rough and smooth surfaces

Unver, O., Sitti, M.

In Robotics and Automation, 2009. ICRA’09. IEEE International Conference on, pages: 2282-2287, 2009 (inproceedings)

pi

[BibTex]

[BibTex]


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Automated 2-D nanoparticle manipulation with an atomic force microscope

Onal, C. D., Ozcan, O., Sitti, M.

In Robotics and Automation, 2009. ICRA’09. IEEE International Conference on, pages: 1814-1819, 2009 (inproceedings)

pi

[BibTex]

[BibTex]


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Microparticle manipulation using multiple untethered magnetic micro-robots on an electrostatic surface

Floyd, S., Pawashe, C., Sitti, M.

In Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on, pages: 528-533, 2009 (inproceedings)

pi

[BibTex]

[BibTex]


Thumb xl miua1
Segmentation of Human Upper Airway Using a Level Set Based Deformable Model

Si Yong Yeo, Xianghua Xie, Igor Sazonov, Perumal Nithiarasu

In The 13th Medical Image Understanding and Analysis, 2009 (inproceedings)

ps

[BibTex]

[BibTex]


Thumb xl emmcvpr2009
Three Dimensional Monocular Human Motion Analysis in End-Effector Space

Soren Hauberg, Jerome Lapuyade, Morten Engell-Norregaard, Kenny Erleben, Kim S. Pedersen

In Energy Minimization Methods in Computer Vision and Pattern Recognition, 5681, pages: 235-248, Lecture Notes in Computer Science, (Editors: Cremers, Daniel and Boykov, Yuri and Blake, Andrew and Schmidt, Frank), Springer Berlin Heidelberg, 2009 (inproceedings)

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Publishers site Paper site PDF [BibTex]

Publishers site Paper site PDF [BibTex]


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Decoding visual motion from correlated firing of thalamic neurons

Stanley, G. B., Black, M. J., Desbordes, G., Jin, J., Wang, Y., Alonso, J.

2009 Abstract Viewer and Itinerary Planner. Society for Neuroscience, Society for Neuroscience, 2009 (conference)

ps

[BibTex]

[BibTex]

2003


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How to Deal with Large Dataset, Class Imbalance and Binary Output in SVM based Response Model

Shin, H., Cho, S.

In Proc. of the Korean Data Mining Conference, pages: 93-107, Korean Data Mining Conference, December 2003, Best Paper Award (inproceedings)

Abstract
[Abstract]: Various machine learning methods have made a rapid transition to response modeling in search of improved performance. And support vector machine (SVM) has also been attracting much attention lately. This paper presents an SVM response model. We are specifically focusing on the how-to’s to circumvent practical obstacles, such as how to face with class imbalance problem, how to produce the scores from an SVM classifier for lift chart analysis, and how to evaluate the models on accuracy and profit. Besides coping with the intractability problem of SVM training caused by large marketing dataset, a previously proposed pattern selection algorithm is introduced. SVM training accompanies time complexity of the cube of training set size. The pattern selection algorithm picks up important training patterns before SVM response modeling. We made comparison on SVM training results between the pattern selection algorithm and random sampling. Three aspects of SVM response models were evaluated: accuracies, lift chart analysis, and computational efficiency. The SVM trained with selected patterns showed a high accuracy, a high uplift in profit and in response rate, and a high computational efficiency.

ei

PDF [BibTex]

2003


PDF [BibTex]


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Characterizing the Human Wrist for Improved Haptic Interaction

Kuchenbecker, K. J., Park, J. G., Niemeyer, G.

In Proc. ASME International Mechanical Engineering Congress and Exposition, Symposium on Advances in Robot Dynamics and Control, 2, paper number 42017, Washington, D.C., USA, November 2003, Oral presentation given by Kuchenbecker (inproceedings)

hi

[BibTex]

[BibTex]


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Bayesian Monte Carlo

Rasmussen, CE., Ghahramani, Z.

In Advances in Neural Information Processing Systems 15, pages: 489-496, (Editors: Becker, S. , S. Thrun, K. Obermayer), MIT Press, Cambridge, MA, USA, Sixteenth Annual Conference on Neural Information Processing Systems (NIPS), October 2003 (inproceedings)

Abstract
We investigate Bayesian alternatives to classical Monte Carlo methods for evaluating integrals. Bayesian Monte Carlo (BMC) allows the incorporation of prior knowledge, such as smoothness of the integrand, into the estimation. In a simple problem we show that this outperforms any classical importance sampling method. We also attempt more challenging multidimensional integrals involved in computing marginal likelihoods of statistical models (a.k.a. partition functions and model evidences). We find that Bayesian Monte Carlo outperformed Annealed Importance Sampling, although for very high dimensional problems or problems with massive multimodality BMC may be less adequate. One advantage of the Bayesian approach to Monte Carlo is that samples can be drawn from any distribution. This allows for the possibility of active design of sample points so as to maximise information gain.

ei

PDF Web [BibTex]

PDF Web [BibTex]


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On the Complexity of Learning the Kernel Matrix

Bousquet, O., Herrmann, D.

In Advances in Neural Information Processing Systems 15, pages: 399-406, (Editors: Becker, S. , S. Thrun, K. Obermayer), The MIT Press, Cambridge, MA, USA, Sixteenth Annual Conference on Neural Information Processing Systems (NIPS), October 2003 (inproceedings)

Abstract
We investigate data based procedures for selecting the kernel when learning with Support Vector Machines. We provide generalization error bounds by estimating the Rademacher complexities of the corresponding function classes. In particular we obtain a complexity bound for function classes induced by kernels with given eigenvectors, i.e., we allow to vary the spectrum and keep the eigenvectors fix. This bound is only a logarithmic factor bigger than the complexity of the function class induced by a single kernel. However, optimizing the margin over such classes leads to overfitting. We thus propose a suitable way of constraining the class. We use an efficient algorithm to solve the resulting optimization problem, present preliminary experimental results, and compare them to an alignment-based approach.

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Control, Planning, Learning, and Imitation with Dynamic Movement Primitives

Schaal, S., Peters, J., Nakanishi, J., Ijspeert, A.

In IROS 2003, pages: 1-21, Workshop on Bilateral Paradigms on Humans and Humanoids, IEEE International Conference on Intelligent Robots and Systems, October 2003 (inproceedings)

ei

PDF [BibTex]

PDF [BibTex]


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Discriminative Learning for Label Sequences via Boosting

Altun, Y., Hofmann, T., Johnson, M.

In Advances in Neural Information Processing Systems 15, pages: 977-984, (Editors: Becker, S. , S. Thrun, K. Obermayer ), MIT Press, Cambridge, MA, USA, Sixteenth Annual Conference on Neural Information Processing Systems (NIPS), October 2003 (inproceedings)

Abstract
This paper investigates a boosting approach to discriminative learning of label sequences based on a sequence rank loss function.

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Multiple-step ahead prediction for non linear dynamic systems: A Gaussian Process treatment with propagation of the uncertainty

Girard, A., Rasmussen, CE., Quiñonero-Candela, J., Murray-Smith, R.

In Advances in Neural Information Processing Systems 15, pages: 529-536, (Editors: Becker, S. , S. Thrun, K. Obermayer), MIT Press, Cambridge, MA, USA, Sixteenth Annual Conference on Neural Information Processing Systems (NIPS), October 2003 (inproceedings)

Abstract
We consider the problem of multi-step ahead prediction in time series analysis using the non-parametric Gaussian process model. k-step ahead forecasting of a discrete-time non-linear dynamic system can be performed by doing repeated one-step ahead predictions. For a state-space model of the form y_t = f(y_{t-1},...,y_{t-L}), the prediction of y at time t + k is based on the point estimates of the previous outputs. In this paper, we show how, using an analytical Gaussian approximation, we can formally incorporate the uncertainty about intermediate regressor values, thus updating the uncertainty on the current prediction.

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Cluster Kernels for Semi-Supervised Learning

Chapelle, O., Weston, J., Schölkopf, B.

In Advances in Neural Information Processing Systems 15, pages: 585-592, (Editors: S Becker and S Thrun and K Obermayer), MIT Press, Cambridge, MA, USA, 16th Annual Conference on Neural Information Processing Systems (NIPS), October 2003 (inproceedings)

Abstract
We propose a framework to incorporate unlabeled data in kernel classifier, based on the idea that two points in the same cluster are more likely to have the same label. This is achieved by modifying the eigenspectrum of the kernel matrix. Experimental results assess the validity of this approach.

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Mismatch String Kernels for SVM Protein Classification

Leslie, C., Eskin, E., Weston, J., Noble, W.

In Advances in Neural Information Processing Systems 15, pages: 1417-1424, (Editors: Becker, S. , S. Thrun, K. Obermayer), MIT Press, Cambridge, MA, USA, Sixteenth Annual Conference on Neural Information Processing Systems (NIPS), October 2003 (inproceedings)

Abstract
We introduce a class of string kernels, called mismatch kernels, for use with support vector machines (SVMs) in a discriminative approach to the protein classification problem. These kernels measure sequence similarity based on shared occurrences of k-length subsequences, counted with up to m mismatches, and do not rely on any generative model for the positive training sequences. We compute the kernels efficiently using a mismatch tree data structure and report experiments on a benchmark SCOP dataset, where we show that the mismatch kernel used with an SVM classifier performs as well as the Fisher kernel, the most successful method for remote homology detection, while achieving considerable computational savings.

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PDF Web [BibTex]