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2010


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Visual Object-Action Recognition: Inferring Object Affordances from Human Demonstration

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

Computer Vision and Image Understanding, pages: 81-90, 2010 (article)

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Pdf [BibTex]

2010


Pdf [BibTex]


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Enhanced wet adhesion and shear of elastomeric micro-fiber arrays with mushroom tip geometry and a photopolymerized p (DMA-co-MEA) tip coating

Glass, P., Chung, H., Washburn, N. R., Sitti, M.

Langmuir, 26(22):17357-17362, American Chemical Society, 2010 (article)

pi

Project Page [BibTex]

Project Page [BibTex]


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Lateral transport of thermal capillary waves

Smith, T. H. R., Vasilyev, O., Maciolek, A., Schmidt, M.

{Europhysics Letters}, 89(1), 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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The formation and propagation of flux avalanches in tailored MgB2 films

Treiber, S., Albrecht, J.

{New Journal of Physics}, 12, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Direct imaging of current induced magnetic vortex gyration in an asymmetric potential well

Bisig, A., Rhensius, J., Kammerer, M., Curcic, M., Stoll, H., Schütz, G., Van Waeyenberge, B., Chou, K. W., Tyliszczak, T., Heyderman, L. J., Krzyk, S., von Bieren, A., Kläui, M.

{Applied Physics Letters}, 96, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Induced magnetism of carbon atoms at the graphene/Ni(111) interface

Weser, M., Rehder, Y., Horn, K., Sicot, M., Fonin, M., Preobrajenski, A. B., Voloshina, E. N., Goering, E., Dedkov, Y. S.

{Applied Physics Letters}, 96, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Photon counting system for time-resolved experiments in multibunch mode

Puzic, A., Korhonen, T., Kalantari, B., Raabe, J., Quitmann, C., Jüllig, P., Bommer, L., Goll, D., Schütz, G., Wintz, S., Strache, T., Körner, M., Markó, D., Bunce, C., Fassbender, J.

{Synchrotron Radiation News}, 23(2):26-32, 2010 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Coupling of Fe and uncompensated Mn moments in exchange-biased Fe/MnPd

Brück, S., Macke, S., Goering, E., Ji, X., Zhan, Q., Krishnan, K. M.

{Physical Review B}, 81(13), 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Remarks about spillover and hydrogen adsorption - Comments on the contributions of A.V. Talyzin and R.T. Yang

Hirscher, M.

{Microporous and Mesoporous Materials}, 135, pages: 209-210, 2010 (article)

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DOI [BibTex]


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Grain boundary ridges and triple lines

Straumal, B. B., Sursaeva, V. G., Baretzky, B.

{Scripta Materialia}, 62(12):924-927, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Expanding micelle nanolithography to the self-assembly of multicomponent core-shell nanoparticles

Mbenkum, B. N., D\’\iaz-Ortiz, A., Gu, L., van Aken, P. A., Schütz, G.

{Journal of the American Chemical Society}, 132(31):10671-10673, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Learning control in robotics – trajectory-based opitimal control techniques

Schaal, S., Atkeson, C. G.

Robotics and Automation Magazine, 17(2):20-29, 2010, clmc (article)

Abstract
In a not too distant future, robots will be a natural part of daily life in human society, providing assistance in many areas ranging from clinical applications, education and care giving, to normal household environments [1]. It is hard to imagine that all possible tasks can be preprogrammed in such robots. Robots need to be able to learn, either by themselves or with the help of human supervision. Additionally, wear and tear on robots in daily use needs to be automatically compensated for, which requires a form of continuous self-calibration, another form of learning. Finally, robots need to react to stochastic and dynamic environments, i.e., they need to learn how to optimally adapt to uncertainty and unforeseen changes. Robot learning is going to be a key ingredient for the future of autonomous robots. While robot learning covers a rather large field, from learning to perceive, to plan, to make decisions, etc., we will focus this review on topics of learning control, in particular, as it is concerned with learning control in simulated or actual physical robots. In general, learning control refers to the process of acquiring a control strategy for a particular control system and a particular task by trial and error. Learning control is usually distinguished from adaptive control [2] in that the learning system can have rather general optimization objectivesâ??not just, e.g., minimal tracking errorâ??and is permitted to fail during the process of learning, while adaptive control emphasizes fast convergence without failure. Thus, learning control resembles the way that humans and animals acquire new movement strategies, while adaptive control is a special case of learning control that fulfills stringent performance constraints, e.g., as needed in life-critical systems like airplanes. Learning control has been an active topic of research for at least three decades. However, given the lack of working robots that actually use learning components, more work needs to be done before robot learning will make it beyond the laboratory environment. This article will survey some ongoing and past activities in robot learning to assess where the field stands and where it is going. We will largely focus on nonwheeled robots and less on topics of state estimation, as typically explored in wheeled robots [3]â??6], and we emphasize learning in continuous state-action spaces rather than discrete state-action spaces [7], [8]. We will illustrate the different topics of robot learning with examples from our own research with anthropomorphic and humanoid robots.

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link (url) [BibTex]

link (url) [BibTex]


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Learning, planning, and control for quadruped locomotion over challenging terrain

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

International Journal of Robotics Research, 30(2):236-258, 2010, clmc (article)

Abstract
We present a control architecture for fast quadruped locomotion over rough terrain. We approach the problem by decomposing it into many sub-systems, in which we apply state-of-the-art learning, planning, optimization, and control techniques to achieve robust, fast locomotion. Unique features of our control strategy include: (1) a system that learns optimal foothold choices from expert demonstration using terrain templates, (2) a body trajectory optimizer based on the Zero- Moment Point (ZMP) stability criterion, and (3) a floating-base inverse dynamics controller that, in conjunction with force control, allows for robust, compliant locomotion over unperceived obstacles. We evaluate the performance of our controller by testing it on the LittleDog quadruped robot, over a wide variety of rough terrains of varying difficulty levels. The terrain that the robot was tested on includes rocks, logs, steps, barriers, and gaps, with obstacle sizes up to the leg length of the robot. We demonstrate the generalization ability of this controller by presenting results from testing performed by an independent external test team on terrain that has never been shown to us.

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link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Teleoperated 3-D force feedback from the nanoscale with an atomic force microscope

Onal, C. D., Sitti, M.

IEEE Transactions on nanotechnology, 9(1):46-54, IEEE, 2010 (article)

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[BibTex]

[BibTex]


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Roll and pitch motion analysis of a biologically inspired quadruped water runner robot

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

The International Journal of Robotics Research, 29(10):1281-1297, SAGE Publications Sage UK: London, England, 2010 (article)

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[BibTex]

[BibTex]


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Microstructured elastomeric surfaces with reversible adhesion and examples of their use in deterministic assembly by transfer printing

Kim, Seok, Wu, Jian, Carlson, Andrew, Jin, Sung Hun, Kovalsky, Anton, Glass, Paul, Liu, Zhuangjian, Ahmed, Numair, Elgan, Steven L, Chen, Weiqiu, others

Proceedings of the National Academy of Sciences, 107(40):17095-17100, National Acad Sciences, 2010 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Tankbot: A palm-size, tank-like climbing robot using soft elastomer adhesive treads

Unver, O., Sitti, M.

The International Journal of Robotics Research, 29(14):1761-1777, SAGE Publications Sage UK: London, England, 2010 (article)

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[BibTex]

[BibTex]


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Hydrogen spillover measurements of unbridged and bridged metal-organic frameworks - revisited

Campesi, R., Cuevas, F., Latroche, M., Hirscher, M.

{Physical Chemistry Chemical Physics}, 12, pages: 10457-10459, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Relating Gilbert damping and ultrafast laser-induced demagnetization

Fähnle, M., Seib, J., Illg, C.

{Physical Review B}, 82, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Ferromagnetic properties of the Mn-doped nanograined ZnO films

Straumal, B. B., Protasova, S. G., Mazilkin, A. A., Myatiev, A. A., Straumal, P. B., Schütz, G., Goering, E., Baretzky, B.

{Journal of Applied Physics}, 108, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Ubiquity of ferromagnetic signals in common diamagnetic oxide crystals

Khalid, M., Setzer, A., Ziese, M., Esquinazi, P., Spemann, D., Pöppl, A., Goering, E.

{Physical Review B}, 81(21), 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Calculation of the Gilbert damping matrix at low scattering rates in Gd

Seib, J., Fähnle, M.

{Physical Review B}, 82, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Swift heavy ions for controlled modification of soft magnetic properties of Fe0.85N0.15 thin film

Gupta, R., Gupta, A., Bhatt, R., Rüffer, R., Avasthi, D. K.

{Journal of Physics: Condensed Matter}, 22(22), 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Note: Aligned deposition and modal characterization of micron and submicron poly (methyl methacyrlate) fiber cantilevers

Nain, A. S., Filiz, S., Burak Ozdoganlar, O., Sitti, M., Amon, C.

Review of Scientific Instruments, 81(1):016102, AIP, 2010 (article)

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[BibTex]

[BibTex]


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Enhanced adhesion of dopamine methacrylamide elastomers via viscoelasticity tuning

Chung, H., Glass, P., Pothen, J. M., Sitti, M., Washburn, N. R.

Biomacromolecules, 12(2):342-347, American Chemical Society, 2010 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Laterally driven interfaces in the three-dimensional Ising lattice gas

Smith, T. H. R., Vasilyev, O., Maciolek, A., Schmidt, M.

{Physical Review E}, 82(2), 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Samarium-cobalt 2:17 magnets: identifying Smn+1Co5n-1 phases stabilized by Zr

Stadelmaier, H. H., Kronmüller, H., Goll, D.

{Scripta Materialia}, 63, pages: 843-846, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Planar metamaterial analogue of electromagnetically induced transparancy for plasmonic sensing

Liu, N., Weiss, T., Mesch, M., Langguth, L., Eigenthaler, U., Hirscher, M., Sönnichsen, C., Giessen, H.

{Nano Letters}, 10, pages: 1103-1107, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Explaining the paradoxical diversity of ultrafast last-induced demagnetization

Koopmans, B., Malinowski, G., Dalla Longa, F., Steiauf, D., Fähnle, M., Roth, T., Cinchetti, M., Aeschlimann, M.

{Nature Materials}, 9, pages: 259-265, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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A high heat of adsorption for hydrogen in magnesium formate

Schmitz, B., Krkljus, I., Leung, E., Höffken, H. W., Müller, U., Hirscher, M.

{ChemSusChem}, 3, pages: 758-761, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Force induced destabilization of adhesion complexes at defined integrin spacings on nanostructured surfaces

de Beer, A. G. F., Cavalcanti-Adam, E. A., Majer, G., López-Garc\’\ia, M., Kessler, H., Spatz, J. P.

{Physical Review E}, 81, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Anisotropic damping of the magnetization dynamics in Ni, Co, and Fe

Gilmore, K., Stiles, M. D., Seib, J., Steiauf, D., Fähnle, M.

{Physical Review B}, 81, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Influence of [Mo6Br8F6]2- cluster inclusion within the mesoporous solid MIL-101 on hydrogen storage performance

Dybtsev, D., Serre, C., Schmitz, B., Panella, B., Hirscher, M., Latroche, M., Llewellyn, P. L., Cordier, S., Molard, Y., Haouas, M., Taulelle, F., Férey, G.

{Langmuir}, 26(13):11283-11290, 2010 (article)

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DOI [BibTex]

DOI [BibTex]


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Grain boundary layers in nanocrystalline ferromagnetic zinc oxide

Straumal, B. B., Myatiev, A. A., Straumal, P. B., Mazilkin, A. A., Protasova, S. G., Goering, E., Baretzky, B.

{JETP Letters}, 92(6):396-400, 2010 (article)

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DOI [BibTex]

DOI [BibTex]

2007


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HPLC analysis and pharmacokinetic study of quercitrin and isoquercitrin in rat plasma after administration of Hypericum japonicum thunb. extract.

Li, J., Wang, W., Zhang, L., Chen, H., Bi, S.

Biomedical Chromatography, 22(4):374-378, December 2007 (article)

Abstract
A simple HPLC method was developed for determination of quercitrin and isoquercitrin in rat plasma. Reversed-phase HPLC was employed for the quantitative analysis using kaempferol-3-O--d-glucopyranoside-7-O--l-rhamnoside as an internal standard. Following extraction from the plasma samples with ethyl acetate-isopropanol (95:5, v/v), these two compounds were successfully separated on a Luna C18 column (250 × 4.6 mm, 5 µm) with isocratic elution of acetonitrile-0.5% aqueous acetic acid (17:83, v/v) as the mobile phase. The flow-rate was set at 1 mL/min and the eluent was detected at 350 nm for both quercitrin and isoquercitrin. The method was linear over the studied ranges of 50-6000 and 50-5000 ng/mL for quercitrin and isoquercitrin, respectively. The intra- and inter-day precisions of the analysis were better than 13.1 and 13.2%, respectively. The lower limits of quantitation for quercitrin and isoquercitrin in plasma were both of 50 ng/mL. The mean extraction recoveries were 73 and 61% for quercitrin and i soquercitrin, respectively. The validated method was successfully applied to pharmacokinetic studies of the two analytes in rat plasma after the oral administration of Hypericum japonicum thunb. ethanol extract.

ei

Web DOI [BibTex]

2007



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Graph sharpening plus graph integration: a synergy that improves protein functional classification

Shin, HH., Lisewski, AM., Lichtarge, O.

Bioinformatics, 23(23):3217-3224, December 2007 (article)

ei

Web DOI [BibTex]

Web DOI [BibTex]


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A Tutorial on Spectral Clustering

von Luxburg, U.

Statistics and Computing, 17(4):395-416, December 2007 (article)

Abstract
In recent years, spectral clustering has become one of the most popular modern clustering algorithms. It is simple to implement, can be solved efficiently by standard linear algebra software, and very often outperforms traditional clustering algorithms such as the k-means algorithm. On the first glance spectral clustering appears slightly mysterious, and it is not obvious to see why it works at all and what it really does. The goal of this tutorial is to give some intuition on those questions. We describe different graph Laplacians and their basic properties, present the most common spectral clustering algorithms, and derive those algorithms from scratch by several different approaches. Advantages and disadvantages of the different spectral clustering algorithms are discussed.

ei

PDF PDF DOI [BibTex]

PDF PDF DOI [BibTex]


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A Tutorial on Kernel Methods for Categorization

Jäkel, F., Schölkopf, B., Wichmann, F.

Journal of Mathematical Psychology, 51(6):343-358, December 2007 (article)

Abstract
The abilities to learn and to categorize are fundamental for cognitive systems, be it animals or machines, and therefore have attracted attention from engineers and psychologists alike. Modern machine learning methods and psychological models of categorization are remarkably similar, partly because these two fields share a common history in artificial neural networks and reinforcement learning. However, machine learning is now an independent and mature field that has moved beyond psychologically or neurally inspired algorithms towards providing foundations for a theory of learning that is rooted in statistics and functional analysis. Much of this research is potentially interesting for psychological theories of learning and categorization but also hardly accessible for psychologists. Here, we provide a tutorial introduction to a popular class of machine learning tools, called kernel methods. These methods are closely related to perceptrons, radial-basis-function neural networks and exemplar theories of catego rization. Recent theoretical advances in machine learning are closely tied to the idea that the similarity of patterns can be encapsulated in a positive definite kernel. Such a positive definite kernel can define a reproducing kernel Hilbert space which allows one to use powerful tools from functional analysis for the analysis of learning algorithms. We give basic explanations of some key concepts—the so-called kernel trick, the representer theorem and regularization—which may open up the possibility that insights from machine learning can feed back into psychology.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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A semigroup approach to queueing systems

Haji, A., Radl, A.

Semigroup Forum, 75(3):610-624, December 2007 (article)

Abstract
We prove asymptotic stability of the solutions of equations describing a simple queueing system consisting of two machines separated by a finite storage buffer. Following an approach by G. Gupur, we apply the theory of C0-semigroups and spectral theory of positive operators.

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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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.

ei pn

Web DOI [BibTex]

Web DOI [BibTex]


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Accurate Splice site Prediction Using Support Vector Machines

Sonnenburg, S., Schweikert, G., Philips, P., Behr, J., Rätsch, G.

BMC Bioinformatics, 8(Supplement 10):1-16, December 2007 (article)

Abstract
Background: For splice site recognition, one has to solve two classification problems: discriminating true from decoy splice sites for both acceptor and donor sites. Gene finding systems typically rely on Markov Chains to solve these tasks. Results: In this work we consider Support Vector Machines for splice site recognition. We employ the so-called weighted degree kernel which turns out well suited for this task, as we will illustrate in several experiments where we compare its prediction accuracy with that of recently proposed systems. We apply our method to the genome-wide recognition of splice sites in Caenorhabditis elegans, Drosophila melanogaster, Arabidopsis thaliana, Danio rerio, and Homo sapiens. Our performance estimates indicate that splice sites can be recognized very accurately in these genomes and that our method outperforms many other methods including Markov Chains, GeneSplicer and SpliceMachine. We provide genome-wide predictions of splice sites and a stand-alone prediction tool ready to be used for incorporation in a gene finder. Availability: Data, splits, additional information on the model selection, the whole genome predictions, as well as the stand-alone prediction tool are available for download at http:// www.fml.mpg.de/raetsch/projects/splice.

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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A unifying framework for robot control with redundant DOFs

Peters, J., Mistry, M., Udwadia, F., Nakanishi, J., Schaal, S.

Autonomous Robots, 24(1):1-12, October 2007 (article)

Abstract
Recently, Udwadia (Proc. R. Soc. Lond. A 2003:1783–1800, 2003) suggested to derive tracking controllers for mechanical systems with redundant degrees-of-freedom (DOFs) using a generalization of Gauss’ principle of least constraint. This method allows reformulating control problems as a special class of optimal controllers. In this paper, we take this line of reasoning one step further and demonstrate that several well-known and also novel nonlinear robot control laws can be derived from this generic methodology. We show experimental verifications on a Sarcos Master Arm robot for some of the derived controllers. The suggested approach offers a promising unification and simplification of nonlinear control law design for robots obeying rigid body dynamics equations, both with or without external constraints, with over-actuation or underactuation, as well as open-chain and closed-chain kinematics.

ei

PDF PDF DOI [BibTex]

PDF PDF DOI [BibTex]


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The Need for Open Source Software in Machine Learning

Sonnenburg, S., Braun, M., Ong, C., Bengio, S., Bottou, L., Holmes, G., LeCun, Y., Müller, K., Pereira, F., Rasmussen, C., Rätsch, G., Schölkopf, B., Smola, A., Vincent, P., Weston, J., Williamson, R.

Journal of Machine Learning Research, 8, pages: 2443-2466, October 2007 (article)

Abstract
Open source tools have recently reached a level of maturity which makes them suitable for building large-scale real-world systems. At the same time, the field of machine learning has developed a large body of powerful learning algorithms for diverse applications. However, the true potential of these methods is not realized, since existing implementations are not openly shared, resulting in software with low usability, and weak interoperability. We argue that this situation can be significantly improved by increasing incentives for researchers to publish their software under an open source model. Additionally, we outline the problems authors are faced with when trying to publish algorithmic implementations of machine learning methods. We believe that a resource of peer reviewed software accompanied by short articles would be highly valuable to both the machine learning and the general scientific community.

ei

PDF Web [BibTex]

PDF Web [BibTex]


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On the Representer Theorem and Equivalent Degrees of Freedom of SVR

Dinuzzo, F., Neve, M., De Nicolao, G., Gianazza, U.

Journal of Machine Learning Research, 8, pages: 2467-2495, October 2007 (article)

Abstract
Support Vector Regression (SVR) for discrete data is considered. An alternative formulation of the representer theorem is derived. This result is based on the newly introduced notion of pseudoresidual and the use of subdifferential calculus. The representer theorem is exploited to analyze the sensitivity properties of ε-insensitive SVR and introduce the notion of approximate degrees of freedom. The degrees of freedom are shown to play a key role in the evaluation of the optimism, that is the difference between the expected in-sample error and the expected empirical risk. In this way, it is possible to define a Cp-like statistic that can be used for tuning the parameters of SVR. The proposed tuning procedure is tested on a simulated benchmark problem and on a real world problem (Boston Housing data set).

ei

Web [BibTex]

Web [BibTex]


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Some observations on the masking effects of Mach bands

Curnow, T., Cowie, DA., Henning, GB., Hill, NJ.

Journal of the Optical Society of America A, 24(10):3233-3241, October 2007 (article)

Abstract
There are 8 cycle / deg ripples or oscillations in performance as a function of location near Mach bands in experiments measuring Mach bands’ masking effects on random polarity signal bars. The oscillations with increments are 180 degrees out of phase with those for decrements. The oscillations, much larger than the measurement error, appear to relate to the weighting function of the spatial-frequency-tuned channel detecting the broad- band signals. The ripples disappear with step maskers and become much smaller at durations below 25 ms, implying either that the site of masking has changed or that the weighting function and hence spatial-frequency tuning is slow to develop.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Bayesian Estimators for Robins-Ritov’s Problem

Harmeling, S., Toussaint, M.

(EDI-INF-RR-1189), School of Informatics, University of Edinburgh, October 2007 (techreport)

Abstract
Bayesian or likelihood-based approaches to data analysis became very popular in the field of Machine Learning. However, there exist theoretical results which question the general applicability of such approaches; among those a result by Robins and Ritov which introduce a specific example for which they prove that a likelihood-based estimator will fail (i.e. it does for certain cases not converge to a true parameter estimate, even given infinite data). In this paper we consider various approaches to formulate likelihood-based estimators in this example, basically by considering various extensions of the presumed generative model of the data. We can derive estimators which are very similar to the classical Horvitz-Thompson and which also account for a priori knowledge of an observation probability function.

ei

PDF [BibTex]

PDF [BibTex]


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Mining complex genotypic features for predicting HIV-1 drug resistance

Saigo, H., Uno, T., Tsuda, K.

Bioinformatics, 23(18):2455-2462, September 2007 (article)

Abstract
Human immunodeficiency virus type 1 (HIV-1) evolves in human body, and its exposure to a drug often causes mutations that enhance the resistance against the drug. To design an effective pharmacotherapy for an individual patient, it is important to accurately predict the drug resistance based on genotype data. Notably, the resistance is not just the simple sum of the effects of all mutations. Structural biological studies suggest that the association of mutations is crucial: Even if mutations A or B alone do not affect the resistance, a significant change might happen when the two mutations occur together. Linear regression methods cannot take the associations into account, while decision tree methods can reveal only limited associations. Kernel methods and neural networks implicitly use all possible associations for prediction, but cannot select salient associations explicitly. Our method, itemset boosting, performs linear regression in the complete space of power sets of mutations. It implements a forward feature selection procedure where, in each iteration, one mutation combination is found by an efficient branch-and-bound search. This method uses all possible combinations, and salient associations are explicitly shown. In experiments, our method worked particularly well for predicting the resistance of nucleotide reverse transcriptase inhibitors (NRTIs). Furthermore, it successfully recovered many mutation associations known in biological literature.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Learning with Transformation Invariant Kernels

Walder, C., Chapelle, O.

(165), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, September 2007 (techreport)

Abstract
Abstract. This paper considers kernels invariant to translation, rotation and dilation. We show that no non-trivial positive definite (p.d.) kernels exist which are radial and dilation invariant, only conditionally positive definite (c.p.d.) ones. Accordingly, we discuss the c.p.d. case and provide some novel analysis, including an elementary derivation of a c.p.d. representer theorem. On the practical side, we give a support vector machine (s.v.m.) algorithm for arbitrary c.p.d. kernels. For the thin-plate kernel this leads to a classifier with only one parameter (the amount of regularisation), which we demonstrate to be as effective as an s.v.m. with the Gaussian kernel, even though the Gaussian involves a second parameter (the length scale).

ei

PDF [BibTex]

PDF [BibTex]


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Scalable Semidefinite Programming using Convex Perturbations

Kulis, B., Sra, S., Jegelka, S.

(TR-07-47), University of Texas, Austin, TX, USA, September 2007 (techreport)

Abstract
Several important machine learning problems can be modeled and solved via semidefinite programs. Often, researchers invoke off-the-shelf software for the associated optimization, which can be inappropriate for many applications due to computational and storage requirements. In this paper, we introduce the use of convex perturbations for semidefinite programs (SDPs). Using a particular perturbation function, we arrive at an algorithm for SDPs that has several advantages over existing techniques: a) it is simple, requiring only a few lines of MATLAB, b) it is a first-order method which makes it scalable, c) it can easily exploit the structure of a particular SDP to gain efficiency (e.g., when the constraint matrices are low-rank). We demonstrate on several machine learning applications that the proposed algorithm is effective in finding fast approximations to large-scale SDPs.

ei

PDF [BibTex]

PDF [BibTex]