Jason Weston

2009
41	EE	Bing Bai, Jason Weston, Ronan Collobert, David Grangier: Supervised Semantic Indexing. ECIR 2009: 761-765
2008
40	EE	Frédéric Ratle, Jason Weston, Matthew L. Miller: Large-Scale Clustering through Functional Embedding. ECML/PKDD (2) 2008: 266-281
39	EE	Jason Weston, Frédéric Ratle, Ronan Collobert: Deep learning via semi-supervised embedding. ICML 2008: 1168-1175
38	EE	Ronan Collobert, Jason Weston: A unified architecture for natural language processing: deep neural networks with multitask learning. ICML 2008: 160-167
37	EE	Michael Karlen, Jason Weston, Ayse Erkan, Ronan Collobert: Large scale manifold transduction. ICML 2008: 448-455
2007
36	EE	Ronan Collobert, Jason Weston: Fast Semantic Extraction Using a Novel Neural Network Architecture. ACL 2007
35	EE	Antoine Bordes, Léon Bottou, Patrick Gallinari, Jason Weston: Solving multiclass support vector machines with LaRank. ICML 2007: 89-96
2006
34	EE	Jason Weston, Ronan Collobert, Fabian H. Sinz, Léon Bottou, Vladimir Vapnik: Inference with the Universum. ICML 2006: 1009-1016
33	EE	Ronan Collobert, Fabian H. Sinz, Jason Weston, Léon Bottou: Trading convexity for scalability. ICML 2006: 201-208
32	EE	Ronan Collobert, Fabian H. Sinz, Jason Weston, Léon Bottou: Large Scale Transductive SVMs. Journal of Machine Learning Research 7: 1687-1712 (2006)
2005
31	EE	Corinna Cortes, Mehryar Mohri, Jason Weston: A general regression technique for learning transductions. ICML 2005: 153-160
30	EE	Eugene Ie, Jason Weston, William Stafford Noble, Christina S. Leslie: Multi-class protein fold recognition using adaptive codes. ICML 2005: 329-336
29	EE	Jason Weston, Bernhard Schölkopf, Olivier Bousquet: Joint Kernel Maps. IWANN 2005: 176-191
28	EE	Jason Weston, Christina S. Leslie, Eugene Ie, Dengyong Zhou, André Elisseeff, William Stafford Noble: Semi-supervised protein classification using cluster kernels. Bioinformatics 21(15): 3241-3247 (2005)
27	EE	Rui Kuang, Jason Weston, William Stafford Noble, Christina S. Leslie: Motif-based protein ranking by network propagation. Bioinformatics 21(19): 3711-3718 (2005)
26	EE	Antoine Bordes, Seyda Ertekin, Jason Weston, Léon Bottou: Fast Kernel Classifiers with Online and Active Learning. Journal of Machine Learning Research 6: 1579-1619 (2005)
2004
25	EE	Gökhan H. Bakir, Léon Bottou, Jason Weston: Breaking SVM Complexity with Cross-Training. NIPS 2004
24	EE	Christina S. Leslie, Eleazar Eskin, Adiel Cohen, Jason Weston, William Stafford Noble: Mismatch string kernels for discriminative protein classification. Bioinformatics 20(4): (2004)
2003
23	EE	Gökhan H. Bakir, Jason Weston, Bernhard Schölkopf: Learning to Find Pre-Images. NIPS 2003
22	EE	Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal, Jason Weston, Bernhard Schölkopf: Learning with Local and Global Consistency. NIPS 2003
21	EE	Jan Eichhorn, Andreas S. Tolias, Alexander Zien, Malte Kuss, Carl Edward Rasmussen, Jason Weston, Nikos Logothetis, Bernhard Schölkopf: Prediction on Spike Data Using Kernel Algorithms. NIPS 2003
20	EE	Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf: Ranking on Data Manifolds. NIPS 2003
19	EE	Jason Weston, Christina S. Leslie, Dengyong Zhou, André Elisseeff, William Stafford Noble: Semi-supervised Protein Classification Using Cluster Kernels. NIPS 2003
18		Jason Weston, Fernando Pérez-Cruz, Olivier Bousquet, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf: Feature selection and transduction for prediction of molecular bioactivity for drug design. Bioinformatics 19(6): 764-771 (2003)
17	EE	Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller: Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces. IEEE Trans. Pattern Anal. Mach. Intell. 25(5): 623-633 (2003)
16	EE	Jason Weston, André Elisseeff, Bernhard Schölkopf, Michael E. Tipping: Use of the Zero-Norm with Linear Models and Kernel Methods. Journal of Machine Learning Research 3: 1439-1461 (2003)
2002
15	EE	Bernhard Schölkopf, Jason Weston, Eleazar Eskin, Christina S. Leslie, William Stafford Noble: A Kernel Approach for Learning from almost Orthogonal Patterns. ECML 2002: 511-528
14	EE	Christina S. Leslie, Eleazar Eskin, Jason Weston, William Stafford Noble: Mismatch String Kernels for SVM Protein Classification. NIPS 2002: 1417-1424
13	EE	Olivier Chapelle, Jason Weston, Bernhard Schölkopf: Cluster Kernels for Semi-Supervised Learning. NIPS 2002: 585-592
12	EE	Jason Weston, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf, Vladimir Vapnik: Kernel Dependency Estimation. NIPS 2002: 873-880
11	EE	Bernhard Schölkopf, Jason Weston, Eleazar Eskin, Christina S. Leslie, William Stafford Noble: A Kernel Approach for Learning from Almost Orthogonal Patterns. PKDD 2002: 494-511
10		Paul Pavlidis, Jason Weston, Jinsong Cai, William Stafford Noble: Learning Gene Functional Classifications from Multiple Data Types. Journal of Computational Biology 9(2): 401-411 (2002)
9		Isabelle Guyon, Jason Weston, Stephen Barnhill, Vladimir Vapnik: Gene Selection for Cancer Classification using Support Vector Machines. Machine Learning 46(1-3): 389-422 (2002)
2001
8	EE	André Elisseeff, Jason Weston: A kernel method for multi-labelled classification. NIPS 2001: 681-687
7	EE	Paul Pavlidis, Jason Weston, Jinsong Cai, William Noble Grundy: Gene functional classification from heterogeneous data. RECOMB 2001: 249-255
2000
6		Olivier Chapelle, Jason Weston, Léon Bottou, Vladimir Vapnik: Vicinal Risk Minimization. NIPS 2000: 416-422
5		Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso Poggio, Vladimir Vapnik: Feature Selection for SVMs. NIPS 2000: 668-674
1999
4	EE	Jason Weston, Chris Watkins: Support vector machines for multi-class pattern recognition. ESANN 1999: 219-224
3		Jason Weston: Leave-One-Out Support Vector Machines. IJCAI 1999: 727-733
2	EE	Olivier Chapelle, Vladimir Vapnik, Jason Weston: Transductive Inference for Estimating Values of Functions. NIPS 1999: 421-427
1	EE	Sebastian Mika, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, Alex J. Smola, Klaus-Robert Müller: Invariant Feature Extraction and Classification in Kernel Spaces. NIPS 1999: 526-532

Coauthor Index

1	Bing Bai	[41]
2	Gökhan H. Bakir	[23] [25]
3	Stephen Barnhill	[9]
4	Antoine Bordes	[26] [35]
5	Léon Bottou	[6] [25] [26] [32] [33] [34] [35]
6	Olivier Bousquet	[18] [20] [22] [29]
7	Jinsong Cai	[7] [10]
8	Olivier Chapelle	[2] [5] [6] [12] [13] [18]
9	Adiel Cohen	[24]
10	Ronan Collobert	[32] [33] [34] [36] [37] [38] [39] [41]
11	Corinna Cortes	[31]
12	Jan Eichhorn	[21]
13	André Elisseeff	[8] [12] [16] [18] [19] [28]
14	Ayse Erkan	[37]
15	Seyda Ertekin	[26]
16	Eleazar Eskin	[11] [14] [15] [24]
17	Patrick Gallinari	[35]
18	David Grangier	[41]
19	Arthur Gretton	[20]
20	William Noble Grundy	[7]
21	Isabelle Guyon	[9]
22	Eugene Ie	[28] [30]
23	Michael Karlen	[37]
24	Rui Kuang	[27]
25	Malte Kuss	[21]
26	Thomas Navin Lal	[22]
27	Christina S. Leslie	[11] [14] [15] [19] [24] [27] [28] [30]
28	Nikos Logothetis	[21]
29	Sebastian Mika	[1] [17]
30	Matthew L. Miller	[40]
31	Mehryar Mohri	[31]
32	Sayan Mukherjee	[5]
33	Klaus-Robert Müller	[1] [17]
34	William Stafford Noble	[10] [11] [14] [15] [19] [24] [27] [28] [30]
35	Paul Pavlidis	[7] [10]
36	Fernando Pérez-Cruz	[18]
37	Tomaso Poggio	[5]
38	Massimiliano Pontil	[5]
39	Carl Edward Rasmussen	[21]
40	Frédéric Ratle	[39] [40]
41	Gunnar Rätsch	[1] [17]
42	Bernhard Schölkopf	[1] [11] [12] [13] [15] [16] [17] [18] [20] [21] [22] [23] [29]
43	Fabian H. Sinz	[32] [33] [34]
44	Alexander J. Smola (Alex J. Smola)	[1] [17]
45	Michael E. Tipping	[16]
46	Andreas S. Tolias	[21]
47	Vladimir Vapnik	[2] [5] [6] [9] [12] [34]
48	Chris Watkins	[4]
49	Dengyong Zhou	[19] [20] [22] [28]
50	Alexander Zien	[21]

Colors in the list of coauthors