On the Pre-Image Problem in Kernel Methods (2007)
BakIr, G.H., Schölkopf, B., Weston, J.
In this chapter we are concerned with the problem of reconstructing patterns from their representation in feature space, known as the pre-image problem. We review existing algorithms and propose a...
The need for open source software in machine learning (2007)
Sonnenburg, S., Braun, M.L., Ong, C.S., Bengio, S., Bottou, L., Holmes, G., ...
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...
The Need for Open Source Software in Machine Learning (2007)
Sonnenburg, S., Braun, M.L., Ong, C.S., Bengio, S., Bottou, L., Holmes, G., ...
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...
Lal, T.N., Chapelle, O., Weston, J., Elisseeff, A., Guyon, I., Gunn, S., ...
Embedded methods are a relatively new approach to feature selection. Unlike filter methods, which do not incorporate learning, and wrapper approaches, which can be used with arbitrary classifiers, in...
Inference with the Universum (2006)
Weston, J., Collobert, R., Sinz, F., Bottou, L., Vapnik, V.
We study classification tasks where one is given a set of labeled examples, and a set of "non-examples" of meaningful concepts in the same domain that do not belong to either class (refered to as the...
Trading Convexity for Scalability (2006)
Collobert, R., Sinz, F., Weston, J., Bottou, L.
Convex learning algorithms, such as Support Vector Machines (SVMs), are often seen as highly desirable because they offer strong practical properties and are amenable to theoretical analysis....
Large Scale Transductive SVMs (2006)
Collobert, R., Sinz, F., Weston, J., Bottou, L.
We show how the Concave-Convex Procedure can be applied to the optimization of Transductive SVMs, which traditionally requires solving a combinatorial search problem. This provides for the first time...
Weston, J., Schölkopf, Bernhard, Bousquet, O.
We develop a methodology for solving high dimensional dependency estimation problems between pairs of data types, which is viable in the case where the output of interest has very high dimension,...
Breaking SVM Complexity with Cross-Training (2005)
Bakir, G.H., Bottou, L., Weston, J., Saul, L.K., Weiss, Y., Bottou, L.
We propose an algorithm for selectively removing examples from the training set using probabilistic estimates related to editing algorithms (Devijver and Kittler82). The procedure creates a separable...
Weston, J., Schölkopf, B., Bousquet, O., Cabestany, J., Prieto, A., Sandoval, F., ...
We develop a methodology for solving high dimensional dependency estimation problems between pairs of data types, which is viable in the case where the output of interest has very high dimension,...
Beckert, R., Fleischhauer, J., Darsen, A., Weston, J., Schenk, S., Batista, A., ...
Heterocycles, 65(2005) S.1311-1320
Lal, Thomas Navin, Chapelle, Olivier, Weston, J., Elisseeff, A
This chapter reviews recently proposed embedded methods for feature selection.
Support Vector Channel Selection in BCI (2004)
Lal, Thomas Navin, Schroeder, M., Hinterberger, T., Weston, J., Bogdan, M., Birbaumer, N., ...
Designing a Brain Computer Interface (BCI) system one can choose from a variety of features that may be useful for classifying brain activity during a mental task. For the special case of classifying...
Learning with Local and Global Consistency (2004)
Zhou,D., Bousquet,O., Lal,T.N., Weston,J., Schölkopf,B.
We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to semi-supervised...
Ranking on Data Manifolds (2004)
Zhou,D., Weston,J., Gretton,A., Bousquet,O., Schölkopf,B.
The Google search engine has enjoyed a huge success with its web page ranking algorithm, which exploits global, rather than local, hyperlink structure of the web using random walks. Here we propose a...
Semi-Supervised Protein Classification using Cluster Kernels (2004)
Weston,J., Leslie,C., Zhou,D., Elisseeff,A., Noble,W.S.
A key issue in supervised protein classification is the representation of input sequences of amino acids. Recent work using string kernels for protein data has achieved state-of-the-art...
Prediction on Spike Data Using Kernel Algorithms (2004)
Eichhorn,J., Tolias,A.S., Zien,A., Kuss,M., Rasmussen,C.E., Weston,J., ...
We report and compare the performance of different learning algorithms based on data from cortical recordings. The task is to predict the orientation of visual stimuli from the activity of a...
Learning to Find Pre-Images (2004)
Bakir,G.H., Weston,J., Schölkopf,B.
We consider the problem of reconstructing patterns from a feature map. Learning algorithms using kernels to operate in a reproducing kernel Hilbert space (RKHS) express their solutions in terms of...
Support Vector Channel Selection in BCI (2004)
Lal,T.N., Schröder,M., Hinterberger,T., Weston,J., Bogdan,M., Birbaumer,N., ...
Designing a Brain Computer Interface (BCI) system one can choose from a variety of features that may be useful for classifying brain activity during a mental task. For the special case of classifying...
Protein ranking: from local to global structure in the protein similarity network (2004)
Weston,J., Elisseeff,A., Zhou,D., Leslie,C., Noble,W.S.
Biologists regularly search databases of DNA or protein sequences for evolutionary or functional relationships to a given query sequence. We describe a ranking algorithm that exploits the entire...
Learning with Local and Global Consistency (2004)
Zhou, D., Bousquet, O., Lal, T.N., Weston, J., Schölkopf, B., Thrun, S., ...
We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to semi-supervised...
Ranking on Data Manifolds (2004)
Zhou, D., Weston, J., Gretton, A., Bousquet, O., Schölkopf, B., Thrun, S., ...
The Google search engine has enjoyed a huge success with its web page ranking algorithm, which exploits global, rather than local, hyperlink structure of the web using random walks. Here we propose a...
Semi-Supervised Protein Classification using Cluster Kernels (2004)
Weston, J., Leslie, C., Zhou, D., Elisseeff, A., Noble, W.S., Thrun, S., ...
A key issue in supervised protein classification is the representation of input sequences of amino acids. Recent work using string kernels for protein data has achieved state-of-the-art...
Prediction on Spike Data Using Kernel Algorithms (2004)
Eichhorn, J., Tolias, A.S., Zien, A., Kuss, M., Rasmussen, C.E., Weston, J., ...
We report and compare the performance of different learning algorithms based on data from cortical recordings. The task is to predict the orientation of visual stimuli from the activity of a...
Learning to Find Pre-Images (2004)
Bakir, G.H., Weston, J., Schölkopf, B., Thrun, S., Saul, L., Schölkopf, B.
We consider the problem of reconstructing patterns from a feature map. Learning algorithms using kernels to operate in a reproducing kernel Hilbert space (RKHS) express their solutions in terms of...
Support Vector Channel Selection in BCI (2004)
Lal, T.N., Schröder, M., Hinterberger, T., Weston, J., Bogdan, M., Birbaumer, N., ...
Designing a Brain Computer Interface (BCI) system one can choose from a variety of features that may be useful for classifying brain activity during a mental task. For the special case of classifying...
Protein ranking: from local to global structure in the protein similarity network (2004)
Weston, J., Elisseeff, A., Zhou, D., Leslie, C., Noble, W.S.
Biologists regularly search databases of DNA or protein sequences for evolutionary or functional relationships to a given query sequence. We describe a ranking algorithm that exploits the entire...
Intervet Symposium: bovine neosporosis (2004)
Schetters, T., Dubey, J.P., Adrianarivo, A., Frankena, K., Romero, J.J., Pérez, E., ...
Support Vector Channel Selection in BCI (2004)
Lal, T. M., Schröder, M., Hinterberger, T., Weston, J., Bogdan, M., Birbaumer, N., ...
Feature selection and transduction for prediction of molecular bioactivity for drug design (2003)
Weston,J., Pérez-Cruz,F., Bousquet,O., Chapelle,O., Elisseeff,A., Schölkopf,B.
Use of the Zero-Norm with Linear Models and Kernel Methods (2003)
Weston,J., Elisseeff,A., Schölkopf,B., Tipping,M.
We explore the use of the so-called zero-norm of the parameters of linear models in learning. Minimization of such a quantity has many uses in a machine learning context: for variable or feature...
Mika,S., Rätsch,G., Weston,J., Schölkopf,B., Smola,A.J.
We incorporate prior knowledge to construct nonlinear algorithms for invariant feature extraction and discrimination. Employing a unified framework in terms of a nonlinearized variant of the Rayleigh...
Extension of the nu-SVM range for classification (2003)
Perez-Cruz, F., Weston, J., Herrmann, D.J.L., Schölkopf, B., Suykens, J., Horvath, G., ...
Feature selection and transduction for prediction of molecular bioactivity for drug design (2003)
Weston, J., Pérez-Cruz, F., Bousquet, O., Chapelle, O., Elisseeff, A., Schölkopf, B.
Dealing with large Diagonals in Kernel Matrices (2003)
Weston, J., Schölkopf, B., Eskin, E., Leslie, C., Noble, W.S.
Use of the Zero-Norm with Linear Models and Kernel Methods (2003)
Weston, J., Elisseeff, A., Schölkopf, B., Tipping, M.
We explore the use of the so-called zero-norm of the parameters of linear models in learning. Minimization of such a quantity has many uses in a machine learning context: for variable or feature...
Mika, S., Rätsch, G., Weston, J., Schölkopf, B., Smola, A.J.
We incorporate prior knowledge to construct nonlinear algorithms for invariant feature extraction and discrimination. Employing a unified framework in terms of a nonlinearized variant of the Rayleigh...
Mika, S., Ratsch, G., Weston, J., Schölkopf, B., Smola, A.
We incorporate prior knowledge to construct nonlinear algorithms for invariant feature extraction and discrimination. Employing a unified framework in terms of a nonlinearized variant of the Rayleigh...
A practical low-noise stretched pulse Yb3+ doped fiber laser (2002)
Lefort, L., Price, J.H.V., Richardson, D.J., Spuhler, G.J., Paschotta, R., Keller, U., ...
We report on the development of what we consider to be a practical and highly stable stretched-pulse laser based on Yb 3+ -doped silica fiber. The Fabry Perot cavity uses nonlinear polarization...
Metal-mediated reactions modeled after nature (2002)
Dieckmann, S., Weston, J., Anders, E., Boland, Wilhelm, Schönecker, B., Hettmann, T., ...
A Kernel Approach for Learning from almost Orthogonal Patterns (2002)
Schölkopf, B., Weston, J., Eskin, E., Leslie, C., Noble, W.S., Elomaa, T., ...
A practical low-noise stretched pulse Yb3+ doped fiber laser (2001)
Price, J.H.V., Lefort, L., Richardson, D.J., Spuhler, G.J., Paschotta, R., Keller, U., ...
We report on the development of what we believe to be a practical and highly-stable sketched pulse laser based on Yb3+ doped silica fiber. The laser generates high quality, 60 pJ pulses of
Feature Selection for SVMs (2001)
J. Weston, S. Mukherjee, O. Chapelle, M. Pontil, Tomaso Poggio, Vladimir Vapnik
We introduce a method of feature selection for Support Vector Machines. The method is based upon finding those features which minimize bounds on the leave-one-out error, which can be efficiently...
Invariant feature extraction and classification in kernel spaces (2000)
Mika, S., Rätsch, G., Weston, J., Schölkopf, B., Smola, A.J.
Feature selection for SVMs (2000)
J. Weston, S. Mukherjee, O. Chapelle, M. Pontil, T. Poggio, V. Vapnik
We introduce a method of feature selection for Support Vector Machines. The method is based upon finding those features which minimize bounds on the leave-one-out error. This search can be...
Feature selection for SVMs (2000)
J. Weston, S. Mukherjee, O. Chapelle, M. Pontil, T. Poggio, V. Vapnik
We introduce a method of feature selection for Support Vector Machines. The method is based upon finding those features which minimize bounds on the leave-one-out error. This search can be...
Support Vector Machines for Multi-Class Pattern Recognition (1999)
. The solution of binary classification problems using support vector machines (SVMs) is well developed, but multi-class problems with more than two classes have typically been solved by combining...
Support Vector Density Estimation (1999)
J. Weston, A. Gammerman, M. O. Stitson, V. Vapnik, V. Vovk, C. Watkins, ...
> (x); (1.1) 1. `(x) = ( 1; x ? 0 0; otherwise Generic author design sample pages 1999/07/12 15:50 2 Support Vector Density Estimation where instead of knowing the distribution function F (x) we...
Support Vector Machines for Multi-Class Pattern Recognition (1999)
Abstract. The solution of binary classi cation problems using support vector machines (SVMs) is well developed, but multi-class problems with more than two classes have typically been solved by...
Support Vector Machine - Reference Manual (1998)
Saunders, C., Stitson, M.O., Weston, J., Bottou, L., Schoelkopf., B., Smola, A.
Support Vector Machine - Reference Manual (1998)
Saunders, C., Stitson, M.O., Weston, J., Bottou, L., Schoelkopf., B., Smola, A.
Support Vector Machine - Reference Manual (1998)
Saunders, C., Stitson, M.O., Weston, J., Bottou, L., Schoelkopf., B., Smola, A.
Support vector machine reference manual (1998)
C. Saunders, M. O. Stitson, J. Weston, Royal Holloway, L. Bottou, B. Scholkopf, ...
The Support Vector Machine (SVM) is a new type of learning machine. The SVM is a general architecture that can be applied to pattern recognition, regression estimation and other problems. The...
Support Vector Machine - Reference Manual (1998)
C. Saunders, M. O. Stitson, J. Weston, Royal Holloway, L. Bottou, B. Schölkopf, ...
this document will describe these programs. To find out more about SVMs, see the bibliography. We will not describe how SVMs work here.
Support Vector Machine - Reference Manual (1998)
C. Saunders, M. O. Stitson, J. Weston, Royal Holloway, L. Bottou, B. Scholkopf, ...
this document will describe these programs. To find out more about SVMs, see the bibliography. We will not describe how SVMs work here.
Density Estimation using Support Vector Machines (1998)
J. Weston, A. Gammerman, M. Stitson, V. Vapnik, V. Vovk, C. Watkins
this report we describe how the Support Vector (SV) technique of solving linear operator equations can be applied to the problem of density estimation [4]. We present a new optimization procedure and...
ATHANASSIOU, P., IOAKIMIDIS, D., WESTON, J., GEORGANAS, K., KONTOMERKOS, T., DAVIES, K. A.
Thymic tumours are associated with a wide range of autoimmune and haematological disorders, notably myasthenia gravis, red cell aplasia, and systemic lupus erythematosus. An association with...
Frequency of glove puncture in the post mortem room.
The post mortem room is a potential source of danger from contamination caused by glove punctures. The objective of this study was to assess the incidence of hand injury and hand contamination during...
Frequency of glove puncture in the post mortem room.
The post mortem room is a potential source of danger from contamination caused by glove punctures. The objective of this study was to assess the incidence of hand injury and hand contamination during...
Studies on the enteropathy associated with primary hypogammaglobulinaemia.
Teahon, K, Webster, A D, Price, A B, Weston, J, Bjarnason, I
Twelve patients with primary hypogammaglobulinaemia with diarrhoea not associated with known microbial pathogens were investigated. Histological evidence of inflammation was common in the stomach and...
Reliability of pre-operative biopsies in the histological grading of colorectal adenocarcinomas.
Burton, S., Eddy, B., Li, W. Y., Reddy, K., Aslam, M., Owen, E., ...
BACKGROUND: Management of colorectal cancer depends on many patient and tumour variables. Decisions are sometimes based on the histological grade of tumour as assessed by initial biopsy. This...
Changing Motives for Share Repurchases
Net share repurchases have increased both in absolute terms and relative to cash dividends. Share repurchases during 1975-87 were predominantly fixed price tender offers and Dutch auctions, mainly...
A Unifying Theory of Value Based Management
We identify four alternative performance metrics used in value based management (VBM). (1) Basic is an intrinsic value analysis (IVA), the discounted cash flow (DCF) methodology. (2) We show that...
Deal Terms in the big Transactions of the Nineties
The 1990s have been called the era of strategic mergers. Powerful change forces have transformed the economic and financial environments. Global markets and exploding technologies have blurred...
Much concern has been expressed about the economic consequences of the high rate of merger and acquisition (M&A) activity. The total value of M&As in the United States in 1998 was $1.3 trillion. This...
Dennis, C-L, Hodnett, E, Kenton, L, Weston, J, Zupancic, J, Stewart, D E, ...
Objective To evaluate the effectiveness of telephone based peer support in the prevention of postnatal depression.