Header logo is


2009


no image
Displaying Realistic Contact Accelerations Via a Dedicated Vibration Actuator

McMahan, W., Kuchenbecker, K. J.

Hands-on demonstration presented at IEEE World Haptics Conference, Salt Lake City, Utah, Proc. IEEE World Haptics Conference, pp. 613–614, Salt Lake City, Utah, USA, March 2009, {B}est Demonstration Award (misc)

hi

[BibTex]

2009


[BibTex]


no image
The iTorqU 1.0 and 2.0

Winfree, K. N., Gewirtz, J., Mather, T., Fiene, J., Kuchenbecker, K. J.

Hands-on demonstration presented at IEEE World Haptics Conference, Salt Lake City, Utah, March 2009 (misc)

hi

[BibTex]

[BibTex]


no image
Vibrotactile Feedback System for Intuitive Upper-Limb Rehabilitation

Kapur, P., Premakumar, S., Jax, S. A., Buxbaum, L. J., Dawson, A. M., Kuchenbecker, K. J.

Hands-on demonstration presented at IEEE World Haptics Conference, Salt Lake City, Utah, USA, Proc. IEEE World Haptics Conference, pp. 621–622, March 2009 (misc)

hi

[BibTex]

[BibTex]


no image
The SlipGlove

Romano, J. M., Gray, S. R., Jacobs, N. T., Kuchenbecker, K. J.

Hands-on demonstration presented at IEEE World Haptics Conference, Salt Lake City, Utah, March 2009 (misc)

hi

[BibTex]

[BibTex]


no image
Real-Time Graphic and Haptic Simulation of Deformable Tissue Puncture

Romano, J. M., Safonova, A., Kuchenbecker, K. J.

Hands-on demonstration presented at Medicine Meets Virtual Reality, Long Beach, California, USA, January 2009 (misc)

hi

[BibTex]

[BibTex]

2007


no image
Predicting Structured Data

Bakir, G., Hofmann, T., Schölkopf, B., Smola, A., Taskar, B., Vishwanathan, S.

pages: 360, Advances in neural information processing systems, MIT Press, Cambridge, MA, USA, September 2007 (book)

Abstract
Machine learning develops intelligent computer systems that are able to generalize from previously seen examples. A new domain of machine learning, in which the prediction must satisfy the additional constraints found in structured data, poses one of machine learning’s greatest challenges: learning functional dependencies between arbitrary input and output domains. This volume presents and analyzes the state of the art in machine learning algorithms and theory in this novel field. The contributors discuss applications as diverse as machine translation, document markup, computational biology, and information extraction, among others, providing a timely overview of an exciting field.

ei

Web [BibTex]

2007


Web [BibTex]


no image
Large-Scale Kernel Machines

Bottou, L., Chapelle, O., DeCoste, D., Weston, J.

pages: 416, Neural Information Processing Series, MIT Press, Cambridge, MA, USA, September 2007 (book)

Abstract
Pervasive and networked computers have dramatically reduced the cost of collecting and distributing large datasets. In this context, machine learning algorithms that scale poorly could simply become irrelevant. We need learning algorithms that scale linearly with the volume of the data while maintaining enough statistical efficiency to outperform algorithms that simply process a random subset of the data. This volume offers researchers and engineers practical solutions for learning from large scale datasets, with detailed descriptions of algorithms and experiments carried out on realistically large datasets. At the same time it offers researchers information that can address the relative lack of theoretical grounding for many useful algorithms. After a detailed description of state-of-the-art support vector machine technology, an introduction of the essential concepts discussed in the volume, and a comparison of primal and dual optimization techniques, the book progresses from well-understood techniques to more novel and controversial approaches. Many contributors have made their code and data available online for further experimentation. Topics covered include fast implementations of known algorithms, approximations that are amenable to theoretical guarantees, and algorithms that perform well in practice but are difficult to analyze theoretically.

ei

Web [BibTex]

Web [BibTex]


no image
Comparing Visual and Haptic Position Feedback

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

Hands-on demonstration at IEEE World Haptics Conference, Tsukuba, Japan, March 2007 (misc)

hi

[BibTex]

[BibTex]


no image
Mathematik der Wahrnehmung: Wendepunkte

Wichman, F., Ernst, MO.

Akademische Mitteilungen zw{\"o}lf: F{\"u}nf Sinne, pages: 32-37, 2007 (misc)

ei

[BibTex]

[BibTex]


no image
Space exploration-towards bio-inspired climbing robots

Menon, C., Murphy, M., Sitti, M., Lan, N.

INTECH Open Access Publisher, 2007 (misc)

pi

[BibTex]

[BibTex]


no image
test jon
(book)

[BibTex]