Shahar Mendelson

2008
27	EE	Shahar Mendelson: Lower Bounds for the Empirical Minimization Algorithm. IEEE Transactions on Information Theory 54(8): 3797-3803 (2008)
26	EE	Shahar Mendelson: Obtaining fast error rates in nonconvex situations. J. Complexity 24(3): 380-397 (2008)
2007
25	EE	Y. Gordon, A. E. Litvak, Shahar Mendelson, A. Pajor: Gaussian averages of interpolated bodies and applications to approximate reconstruction. Journal of Approximation Theory 149(1): 59-73 (2007)
2005
24	EE	Shahar Mendelson: On the Limitations of Embedding Methods. COLT 2005: 353-365
23	EE	Shahar Mendelson, A. Pajor: Ellipsoid Approximation Using Random Vectors. COLT 2005: 429-443
22	EE	Shahar Mendelson, A. Pajor, M. Rudelson: The Geometry of Random {-1, 1}-Polytopes. Discrete & Computational Geometry 34(3): 365-379 (2005)
21	EE	Shahar Mendelson: Embedding with a Lipschitz function. Random Struct. Algorithms 27(1): 25-45 (2005)
2004
20	EE	Peter L. Bartlett, Shahar Mendelson, Petra Philips: Local Complexities for Empirical Risk Minimization. COLT 2004: 270-284
19	EE	Shahar Mendelson, Petra Philips: On the Importance of Small Coordinate Projections. Journal of Machine Learning Research 5: 219-238 (2004)
2003
18		Shahar Mendelson, Alex J. Smola: Advanced Lectures on Machine Learning, Machine Learning Summer School 2002, Canberra, Australia, February 11-22, 2002, Revised Lectures Springer 2003
17	EE	Shahar Mendelson, Petra Philips: Random Subclass Bounds. COLT 2003: 329-343
16	EE	Shahar Mendelson: On the Performance of Kernel Classes. Journal of Machine Learning Research 4: 759-771 (2003)
2002
15	EE	Shahar Mendelson, Robert C. Williamson: Agnostic Learning Nonconvex Function Classes. COLT 2002: 1-13
14	EE	Shahar Mendelson, Roman Vershynin: Entropy, Combinatorial Dimensions and Random Averages. COLT 2002: 14-28
13	EE	Shahar Mendelson: Geometric Parameters of Kernel Machines. COLT 2002: 29-43
12	EE	Peter L. Bartlett, Olivier Bousquet, Shahar Mendelson: Localized Rademacher Complexities. COLT 2002: 44-58
11	EE	Shahar Mendelson: A Few Notes on Statistical Learning Theory. Machine Learning Summer School 2002: 1-40
10		Shahar Mendelson: Rademacher averages and phase transitions in Glivenko-Cantelli classes. IEEE Transactions on Information Theory 48(1): 251-263 (2002)
9		Shahar Mendelson: Improving the sample complexity using global data. IEEE Transactions on Information Theory 48(7): 1977-1991 (2002)
8	EE	Shahar Mendelson: Learnability in Hilbert Spaces with Reproducing Kernels. J. Complexity 18(1): 152-170 (2002)
7	EE	Peter L. Bartlett, Shahar Mendelson: Rademacher and Gaussian Complexities: Risk Bounds and Structural Results. Journal of Machine Learning Research 3: 463-482 (2002)
2001
6	EE	Peter L. Bartlett, Shahar Mendelson: Rademacher and Gaussian Complexities: Risk Bounds and Structural Results. COLT/EuroCOLT 2001: 224-240
5	EE	Shahar Mendelson: Geometric Methods in the Analysis of Glivenko-Cantelli Classes. COLT/EuroCOLT 2001: 256-272
4	EE	Shahar Mendelson: Learning Relatively Small Classes. COLT/EuroCOLT 2001: 273-288
3	EE	Shahar Mendelson: On the Size of Convex Hulls of Small Sets. Journal of Machine Learning Research 2: 1-18 (2001)
2		Shahar Mendelson: A New On-Line Learning Model. Neural Computation 13(4): 935-957 (2001)
2000
1		Shahar Mendelson, Naftali Tishby: Statistical Sufficiency for Classes in Empirical L2 Spaces. COLT 2000: 81-89

Coauthor Index

1	Peter L. Bartlett	[6] [7] [12] [20]
2	Olivier Bousquet	[12]
3	Y. Gordon	[25]
4	A. E. Litvak	[25]
5	A. Pajor	[22] [23] [25]
6	Petra Philips	[17] [19] [20]
7	M. Rudelson	[22]
8	Alexander J. Smola (Alex J. Smola)	[18]
9	Naftali Tishby	[1]
10	Roman Vershynin	[14]
11	Robert C. Williamson	[15]

Colors in the list of coauthors