Ingo Steinwart

2008
21	EE	Ingo Steinwart, Andreas Christmann: Sparsity of SVMs that use the epsilon-insensitive loss. NIPS 2008: 1569-1576
2007
20	EE	Nikolas List, Don R. Hush, Clint Scovel, Ingo Steinwart: Gaps in Support Vector Optimization. COLT 2007: 336-348
19	EE	Andreas Christmann, Ingo Steinwart: How SVMs can estimate quantiles and the median. NIPS 2007
18	EE	Andreas Christmann, Ingo Steinwart, Mia Hubert: Robust learning from bites for data mining. Computational Statistics & Data Analysis 52(1): 347-361 (2007)
17	EE	Don R. Hush, Clint Scovel, Ingo Steinwart: Stability of Unstable Learning Algorithms. Machine Learning 67(3): 197-206 (2007)
2006
16	EE	Ingo Steinwart, Don R. Hush, Clint Scovel: Function Classes That Approximate the Bayes Risk. COLT 2006: 79-93
15	EE	Ingo Steinwart, Don R. Hush, Clint Scovel: An Oracle Inequality for Clipped Regularized Risk Minimizers. NIPS 2006: 1321-1328
14	EE	Ingo Steinwart, Don R. Hush, Clint Scovel: An Explicit Description of the Reproducing Kernel Hilbert Spaces of Gaussian RBF Kernels. IEEE Transactions on Information Theory 52(10): 4635-4643 (2006)
13	EE	Don R. Hush, Patrick Kelly, Clint Scovel, Ingo Steinwart: QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines. Journal of Machine Learning Research 7: 733-769 (2006)
2005
12	EE	Ingo Steinwart, Clint Scovel: Fast Rates for Support Vector Machines. COLT 2005: 279-294
11	EE	Ingo Steinwart: Consistency of support vector machines and other regularized kernel classifiers. IEEE Transactions on Information Theory 51(1): 128-142 (2005)
10	EE	Ingo Steinwart, Don R. Hush, Clint Scovel: A Classification Framework for Anomaly Detection. Journal of Machine Learning Research 6: 211-232 (2005)
2004
9	EE	Ingo Steinwart, Don R. Hush, Clint Scovel: Density Level Detection is Classification. NIPS 2004
8	EE	Ingo Steinwart, Clint Scovel: Fast Rates to Bayes for Kernel Machines. NIPS 2004
7	EE	Ingo Steinwart: Entropy of convex hulls--some Lorentz norm results. Journal of Approximation Theory 128(1): 42-52 (2004)
6	EE	Andreas Christmann, Ingo Steinwart: On Robustness Properties of Convex Risk Minimization Methods for Pattern Recognition. Journal of Machine Learning Research 5: 1007-1034 (2004)
2003
5	EE	Ingo Steinwart: Sparseness of Support Vector Machines---Some Asymptotically Sharp Bounds. NIPS 2003
4	EE	Ingo Steinwart: On the Optimal Parameter Choice for v-Support Vector Machines. IEEE Trans. Pattern Anal. Mach. Intell. 25(10): 1274-1284 (2003)
3	EE	Ingo Steinwart: Sparseness of Support Vector Machines. Journal of Machine Learning Research 4: 1071-1105 (2003)
2002
2	EE	Ingo Steinwart: Support Vector Machines are Universally Consistent. J. Complexity 18(3): 768-791 (2002)
2001
1	EE	Ingo Steinwart: On the Influence of the Kernel on the Consistency of Support Vector Machines. Journal of Machine Learning Research 2: 67-93 (2001)

Coauthor Index

1	Andreas Christmann	[6] [18] [19] [21]
2	Mia Hubert	[18]
3	Don R. Hush	[9] [10] [13] [14] [15] [16] [17] [20]
4	Patrick Kelly	[13]
5	Nikolas List	[20]
6	Clint Scovel	[8] [9] [10] [12] [13] [14] [15] [16] [17] [20]

Colors in the list of coauthors