-
1
-
-
0038453192
-
Rademacher and Gaussian complexities: Risk bounds and structural results
-
P. L. Bartlett and S. Mendelson. Rademacher and Gaussian complexities: Risk bounds and structural results. Journal of Machine Learning Research, 3:463-482, 2002.
-
(2002)
Journal of Machine Learning Research
, vol.3
, pp. 463-482
-
-
Bartlett, P.L.1
Mendelson, S.2
-
4
-
-
0035882612
-
A note on approximating Max-Bisection on regular graphs
-
DOI 10.1016/S0020-0190(00)00189-7, PII S0020019000001897
-
U. Feige, M. Karpinski, and M. Langberg. A note on approximating Max-Bisection on regular graphs. Information Processing Letters, 79(4):181-188, 2001. (Pubitemid 32639105)
-
(2001)
Information Processing Letters
, vol.79
, Issue.4
, pp. 181-188
-
-
Feige, U.1
Karpinski, M.2
Langberg, M.3
-
6
-
-
0012588287
-
On learning perceptrons with binary weights
-
M. Golea and M. Marchand. On learning perceptrons with binary weights. Neural Computation, 5(5):767-782, 1993b.
-
(1993)
Neural Computation
, vol.5
, Issue.5
, pp. 767-782
-
-
Golea, M.1
Marchand, M.2
-
7
-
-
84855609314
-
On the complexity of linear prediction: Risk bounds, margin bounds, and regularization
-
S. M. Kakade, K. Sridharan, and A. Tewari. On the complexity of linear prediction: Risk bounds, margin bounds, and regularization. In Proceedings of the 22nd Annual Conference on Neural Information Processing Systems (NIPS), pages 793-800, 2008.
-
(2008)
Proceedings of the 22nd Annual Conference on Neural Information Processing Systems (NIPS)
, pp. 793-800
-
-
Kakade, S.M.1
Sridharan, K.2
Tewari, A.3
-
8
-
-
4243377862
-
Learning algorithm for a neural network with binary synapses
-
H. Köhler, S. Diederich, W. Kinzel, and M. Opper. Learning algorithm for a neural network with binary synapses. Zeitschrift fr Physik B Condensed Matter, 78:333-342, 1990.
-
(1990)
Zeitschrift Fr Physik B Condensed Matter
, vol.78
, pp. 333-342
-
-
Köhler, H.1
Diederich, S.2
Kinzel, W.3
Opper, M.4
-
9
-
-
0008238669
-
On the ability of the optimal perceptron to generalise
-
M. Opper, W. Kinzel, J. Kleinz, and R Nehl. On the ability of the optimal perceptron to generalise. Journal of Physics A: Mathematical and General, 23(11):L581-L586, 1990.
-
(1990)
Journal of Physics A: Mathematical and General
, vol.23
, Issue.11
-
-
Opper, M.1
Kinzel, W.2
Kleinz, J.3
Nehl, R.4
-
10
-
-
0024092215
-
Computational limitations on learning from examples
-
L. Pitt and L. G. Valiant. Computational limitations on learning from examples. J. ACM, 35(4):965-984, 1988.
-
(1988)
J. ACM
, vol.35
, Issue.4
, pp. 965-984
-
-
Pitt, L.1
Valiant, L.G.2
-
11
-
-
51249173817
-
Randomized rounding: A technique for probably good algorithms and algorithmic proofs
-
P. Raghavan and C. D. Thompson. Randomized rounding: A technique for probably good algorithms and algorithmic proofs. Combinatorica, 7(4):365-374, 1987.
-
(1987)
Combinatorica
, vol.7
, Issue.4
, pp. 365-374
-
-
Raghavan, P.1
Thompson, C.D.2
-
13
-
-
0027678679
-
Extracting refined rules from knowledge-based neural networks
-
G. G. Towell and J. W. Shavlik. Extracting refined rules from knowledge-based neural networks. Machine Learning, 13:71-101, 1993.
-
(1993)
Machine Learning
, vol.13
, pp. 71-101
-
-
Towell, G.G.1
Shavlik, J.W.2
|