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2012


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Quasi-Newton Methods: A New Direction

Hennig, P., Kiefel, M.

In Proceedings of the 29th International Conference on Machine Learning, pages: 25-32, ICML ’12, (Editors: John Langford and Joelle Pineau), Omnipress, New York, NY, USA, ICML, July 2012 (inproceedings)

Abstract
Four decades after their invention, quasi- Newton methods are still state of the art in unconstrained numerical optimization. Although not usually interpreted thus, these are learning algorithms that fit a local quadratic approximation to the objective function. We show that many, including the most popular, quasi-Newton methods can be interpreted as approximations of Bayesian linear regression under varying prior assumptions. This new notion elucidates some shortcomings of classical algorithms, and lights the way to a novel nonparametric quasi-Newton method, which is able to make more efficient use of available information at computational cost similar to its predecessors.

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website+code pdf link (url) [BibTex]

2012


website+code pdf link (url) [BibTex]


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Surgical Instrument Vibrations are a Construct-Valid Measure of Technical Skill in Robotic Peg Transfer and Suturing Tasks

Bark, K., Gomez, E. D., Rivera, C., McMahan, W., Remington, A., Murayama, K., Lee, D. I., Dumon, K., Williams, N., Kuchenbecker, K. J.

In Proc. Hamlyn Symposium on Medical Robotics, pages: 50-51, London, England, July 2012, Oral presentation given by Bark (inproceedings)

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[BibTex]

[BibTex]


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Evaluation of Tactile Feedback Methods for Wrist Rotation Guidance

Stanley, A. A., Kuchenbecker, K. J.

IEEE Transactions on Haptics, 5(3):240-251, July 2012 (article)

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[BibTex]

[BibTex]


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Entropy Search for Information-Efficient Global Optimization

Hennig, P., Schuler, C.

Journal of Machine Learning Research, 13, pages: 1809-1837, -, June 2012 (article)

Abstract
Contemporary global optimization algorithms are based on local measures of utility, rather than a probability measure over location and value of the optimum. They thus attempt to collect low function values, not to learn about the optimum. The reason for the absence of probabilistic global optimizers is that the corresponding inference problem is intractable in several ways. This paper develops desiderata for probabilistic optimization algorithms, then presents a concrete algorithm which addresses each of the computational intractabilities with a sequence of approximations and explicitly adresses the decision problem of maximizing information gain from each evaluation.

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PDF Web Project Page [BibTex]

PDF Web Project Page [BibTex]


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Spectral Subtraction of Robot Motion Noise for Improved Vibrotactile Event Detection

McMahan, W., Kuchenbecker, K. J.

In Haptics: Perception, Devices, Mobility, and Communication: Proc. EuroHaptics, Part I, 7282, pages: 326-337, Lecture Notes in Computer Science, Springer, Tampere, Finland, June 2012, Oral presentation given by Kuchenbecker (inproceedings)

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[BibTex]

[BibTex]


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Learning Tracking Control with Forward Models

Bócsi, B., Hennig, P., Csató, L., Peters, J.

In pages: 259 -264, IEEE International Conference on Robotics and Automation (ICRA), May 2012 (inproceedings)

Abstract
Performing task-space tracking control on redundant robot manipulators is a difficult problem. When the physical model of the robot is too complex or not available, standard methods fail and machine learning algorithms can have advantages. We propose an adaptive learning algorithm for tracking control of underactuated or non-rigid robots where the physical model of the robot is unavailable. The control method is based on the fact that forward models are relatively straightforward to learn and local inversions can be obtained via local optimization. We use sparse online Gaussian process inference to obtain a flexible probabilistic forward model and second order optimization to find the inverse mapping. Physical experiments indicate that this approach can outperform state-of-the-art tracking control algorithms in this context.

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PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Creating realistic virtual textures from contact acceleration data

Romano, J. M., Kuchenbecker, K. J.

IEEE Transactions on Haptics, 5(2):109-119, April 2012, Cover article (article)

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[BibTex]

[BibTex]


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Refined Methods for Creating Realistic Haptic Virtual Textures from Tool-Mediated Contact Acceleration Data

Culbertson, H., Romano, J. M., Castillo, P., Mintz, M., Kuchenbecker, K. J.

In Proc. IEEE Haptics Symposium, pages: 385-391, Vancouver, Canada, March 2012, Poster presentation given by Culbertson (inproceedings)

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[BibTex]

[BibTex]


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VerroTouch: Detection of Instrument Vibrations for Haptic Feedback and Skill Assessment in Robotic Surgery

Gomez, E. D., Bark, K., McMahan, W., Rivera, C., Remington, A., Lee, D. I., Kuchenbecker, K. J.

In Proc. Annual Meeting of the Society of American Gastrointestinal and Endoscopic Surgeons (SAGES), San Diego, California, USA, March 2012, Emerging Technology Poster presentation given by Gomez. Poster available at \href{http://thesagesmeeting.org/}{http://thesagesmeeting.org/} (inproceedings)

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[BibTex]

[BibTex]


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Using Accelerometers to Localize Tactile Contact Events on a Robot Arm

McMahan, W., Romano, J. M., Kuchenbecker, K. J.

In Proc. Workshop on Advances in Tactile Sensing and Touch-Based Human-Robot Interaction, ACM/IEEE International Conference on Human-Robot Interaction, Boston, Massachusetts, March 2012, Oral presentation given by McMahan (inproceedings)

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[BibTex]

[BibTex]


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Recreating the feel of the human chest in a CPR manikin via programmable pneumatic damping

Stanley, A. A., Healey, S. K., Maltese, M. R., Kuchenbecker, K. J.

In Proc. IEEE Haptics Symposium, pages: 37-44, Vancouver, Canada, March 2012, Oral presentation given by Stanley (inproceedings)

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[BibTex]

[BibTex]


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HALO: Haptic Alerts for Low-hanging Obstacles in White Cane Navigation

Wang, Y., Kuchenbecker, K. J.

In Proc. IEEE Haptics Symposium, pages: 527-532, Vancouver, Canada, March 2012, Poster presentation given by Kuchenbecker (inproceedings)

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[BibTex]

[BibTex]


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Approximate Gaussian Integration using Expectation Propagation

Cunningham, J., Hennig, P., Lacoste-Julien, S.

In pages: 1-11, -, January 2012 (inproceedings) Submitted

Abstract
While Gaussian probability densities are omnipresent in applied mathematics, Gaussian cumulative probabilities are hard to calculate in any but the univariate case. We offer here an empirical study of the utility of Expectation Propagation (EP) as an approximate integration method for this problem. For rectangular integration regions, the approximation is highly accurate. We also extend the derivations to the more general case of polyhedral integration regions. However, we find that in this polyhedral case, EP's answer, though often accurate, can be almost arbitrarily wrong. These unexpected results elucidate an interesting and non-obvious feature of EP not yet studied in detail, both for the problem of Gaussian probabilities and for EP more generally.

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Web [BibTex]

Web [BibTex]


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Kernel Topic Models

Hennig, P., Stern, D., Herbrich, R., Graepel, T.

In Fifteenth International Conference on Artificial Intelligence and Statistics, 22, pages: 511-519, JMLR Proceedings, (Editors: Lawrence, N. D. and Girolami, M.), JMLR.org, AISTATS , 2012 (inproceedings)

Abstract
Latent Dirichlet Allocation models discrete data as a mixture of discrete distributions, using Dirichlet beliefs over the mixture weights. We study a variation of this concept, in which the documents' mixture weight beliefs are replaced with squashed Gaussian distributions. This allows documents to be associated with elements of a Hilbert space, admitting kernel topic models (KTM), modelling temporal, spatial, hierarchical, social and other structure between documents. The main challenge is efficient approximate inference on the latent Gaussian. We present an approximate algorithm cast around a Laplace approximation in a transformed basis. The KTM can also be interpreted as a type of Gaussian process latent variable model, or as a topic model conditional on document features, uncovering links between earlier work in these areas.

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PDF Web [BibTex]

PDF Web [BibTex]


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VerroTeach: Visuo-audio-haptic Training for Dental Caries Detection

Maggio, M. P., Parajon, R., Kuchenbecker, K. J.

In Proc. Annual American Dental Educator’s Association (ADEA) Conference, Orlando, Florida, 2012, Oral presentation given by Maggio (inproceedings)

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[BibTex]

[BibTex]


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A Data-Driven Method for Determining Natural Human-Robot Motion Mappings in Teleoperation

Pierce, R. M., Kuchenbecker, K. J.

In Proc. IEEE International Conference on Biomedical Robotics and Biomechatronics, pages: 169-176, Rome, Italy, 2012, Poster presentation given by Pierce (inproceedings)

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[BibTex]

[BibTex]


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Low Bitrate Source-filter Model Based Compression of Vibrotactile Texture Signals in Haptic Teleoperation

Chaudhari, R., Çizmeci, B., Kuchenbecker, K. J., Choi, S., Steinbach, E.

In Proc. ACM Multimedia, pages: 409-418, Nara, Japan, 2012, Oral presentation given by {Chaudhari} (inproceedings)

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[BibTex]

[BibTex]


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Robotic Learning of Haptic Adjectives Through Physical Interaction

McMahon, I., Chu, V., Riano, L., McDonald, C. G., He, Q. (., Perez-Tejada, J. M., Arrigo, M., Fitter, N., Nappo, J., Darrell, T., Kuchenbecker, K. J.

In Proc. IROS Workshop on Advances in Tactile Sensing and Touch-based Human-robot Interaction, Vilamoura, Algarve, Portugal, 2012, Oral presentation given by McMahon (inproceedings)

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[BibTex]

[BibTex]


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Construct Validity of Instrument Vibrations as a Measure of Robotic Surgical Skill

Gomez, E. D., Bark, K., Rivera, C., McMahan, W., Remington, A., Lee, D. I., Williams, N., Murayama, K., Dumon, K., Kuchenbecker, K. J.

Journal of the American College of Surgeons, 215(3):S119-120, Chicago, Illinois, USA, 2012, Oral presentation given by Gomez at the {\em American College of Surgeons (ACS) Clinical Congress} (article)

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[BibTex]

[BibTex]

2007


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Point-spread functions for backscattered imaging in the scanning electron microscope

Hennig, P., Denk, W.

Journal of Applied Physics , 102(12):1-8, December 2007 (article)

Abstract
One knows the imaging system's properties are central to the correct interpretation of any image. In a scanning electron microscope regions of different composition generally interact in a highly nonlinear way during signal generation. Using Monte Carlo simulations we found that in resin-embedded, heavy metal-stained biological specimens staining is sufficiently dilute to allow an approximately linear treatment. We then mapped point-spread functions for backscattered-electron contrast, for primary energies of 3 and 7 keV and for different detector specifications. The point-spread functions are surprisingly well confined (both laterally and in depth) compared even to the distribution of only those scattered electrons that leave the sample again.

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Web DOI [BibTex]

2007


Web DOI [BibTex]


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The power of external mentors for women pursuing academic careers in engineering and science: Stories of MentorNet ACE and its Proteges and Mentors

Muller, C. B., Smith, E. H. B., Chou-Green, J., Daniels-Race, T., Drummond, A., Kuchenbecker, K. J.

In Proc. Women in Engineering Programs and Advocates Network (WEPAN) National Conference, Lake Buena Vista, Florida, USA, June 2007, Oral presentation given by Muller (inproceedings)

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[BibTex]

[BibTex]


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Effects of Visual and Proprioceptive Position Feedback on Human Control of Targeted Movement

Kuchenbecker, K. J., Gurari, N., Okamura, A. M.

In Proc. IEEE International Conference on Rehabilitation Robotics, pages: 513-524, Noordwijk, Netherlands, June 2007, Oral and poster presentations given by Kuchenbecker (inproceedings)

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[BibTex]

[BibTex]


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Quantifying the value of visual and haptic position feedback in force-based motion control

Kuchenbecker, K. J., Gurari, N., Okamura, A. M.

In Proc. IEEE World Haptics Conference, pages: 561-562, Tsukuba, Japan, March 2007, Poster presentation given by Kuchenbecker (inproceedings)

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[BibTex]

[BibTex]


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Shaping event-based haptic transients via an improved understanding of real contact dynamics

Fiene, J. P., Kuchenbecker, K. J.

In Proc. IEEE World Haptics Conference, pages: 170-175, Tsukuba, Japan, March 2007, Oral presentation given by Fiene. {B}est Haptic Technology Paper Award (inproceedings)

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[BibTex]

[BibTex]