-
1
-
-
0035807328
-
Search for single top production at DZero using neural networks
-
V.M. Abazov et al. Search for single top production at DZero using neural networks. Physics Letters B, 517:282, 2001.
-
(2001)
Physics Letters B
, vol.517
, pp. 282
-
-
Abazov, V.M.1
-
2
-
-
4243421500
-
Observation of top quark production in pp̄ collisions with the collider detector at FermiLab
-
F. Abe et al. Observation of top quark production in pp̄ collisions with the collider detector at FermiLab. Physical Review Letters, 74:2626,1995.
-
(1995)
Physical Review Letters
, vol.74
, pp. 2626
-
-
Abe, F.1
-
3
-
-
4244105738
-
Observation of the top quark
-
B. Abott et al. Observation of the top quark. Physical Review Letters, 74:2632, 1995.
-
(1995)
Physical Review Letters
, vol.74
, pp. 2632
-
-
Abott, B.1
-
4
-
-
85089707709
-
Measurement of the tt̄ production cross section in pp̄ collisions at √s = 1.96 TeV using dilepton events
-
A. Abulencia et al. Measurement of the tt̄ production cross section in pp̄ collisions at √s = 1.96 TeV using dilepton events. Physical Review Letters, 93:142001, 2004.
-
(2004)
Physical Review Letters
, vol.93
, pp. 142001
-
-
Abulencia, A.1
-
5
-
-
84875948962
-
Measurement of the J/ψ meson and b hadron production cross sections in pp collisions at √s = 1960 gev
-
A. Abulencia et al. Measurement of the J/ψ meson and b hadron production cross sections in pp collisions at √s = 1960 gev. Physical Review D, 71:032001, 2005.
-
(2005)
Physical Review D
, vol.71
, pp. 032001
-
-
Abulencia, A.1
-
6
-
-
33744520459
-
Top quark mass measurement from dilepton events at CDF II
-
A. Abulencia et al. Top quark mass measurement from dilepton events at CDF II. Physical Review Letters, 96:152002, 2005.
-
(2005)
Physical Review Letters
, vol.96
, pp. 152002
-
-
Abulencia, A.1
-
7
-
-
18444365885
-
Measurement of the cross section for tt̄ production in pp̄ collisions using the kinematics of lepton + jets events
-
D. Acosta et al. Measurement of the cross section for tt̄ production in pp̄ collisions using the kinematics of lepton + jets events. Physical Review D, 52:052003, 2005.
-
(2005)
Physical Review D
, vol.52
, pp. 052003
-
-
Acosta, D.1
-
8
-
-
85140808190
-
-
S. Agostinelli et al. GEANT4. Nuclear Instruments and Methods in Physics Research, A506:250-303, 2003.
-
S. Agostinelli et al. GEANT4. Nuclear Instruments and Methods in Physics Research, A506:250-303, 2003.
-
-
-
-
9
-
-
33744801423
-
Aging atom smasher runs all out in race for most coveted particle
-
A. Cho. Aging atom smasher runs all out in race for most coveted particle. Science, 312:1302-1303, 2006.
-
(2006)
Science
, vol.312
, pp. 1302-1303
-
-
Cho, A.1
-
10
-
-
17044413299
-
PhysicsGP: A genetic programming approach to event selection
-
K. Cranmer and R. S. Bowman. PhysicsGP: a genetic programming approach to event selection. Computer Physics Communications, 167:165, 2005.
-
(2005)
Computer Physics Communications
, vol.167
, pp. 165
-
-
Cranmer, K.1
Bowman, R.S.2
-
15
-
-
0036505670
-
A comparison of methods for multi-class support vector machines
-
C.-W. Hsu and C.-J. Lin. A comparison of methods for multi-class support vector machines. IEEE Transactions on Neural Networks, 13:415-425, 2002.
-
(2002)
IEEE Transactions on Neural Networks
, vol.13
, pp. 415-425
-
-
Hsu, C.-W.1
Lin, C.-J.2
-
16
-
-
36349003591
-
Combination of preliminary electroweak measurements and constraints on the standard model
-
The LEP Collaboration
-
The LEP Collaboration. Combination of preliminary electroweak measurements and constraints on the standard model. CERN-PH-EP/2004-069, 2004.
-
(2004)
CERN-PH-EP/2004-069
-
-
-
19
-
-
0035311478
-
High-energy physics event generation with PYTHIA 6.1
-
T. Sjostrand et al. High-energy physics event generation with PYTHIA 6.1. Computer Physics Communications, 135:238, 2001.
-
(2001)
Computer Physics Communications
, vol.135
, pp. 238
-
-
Sjostrand, T.1
-
20
-
-
0036594106
-
Evolving neural networks through augmenting topologies
-
K. O. Stanley and R. Miikkulainen. Evolving neural networks through augmenting topologies. Evolutionary Computation, 10(2):99-127, 2002.
-
(2002)
Evolutionary Computation
, vol.10
, Issue.2
, pp. 99-127
-
-
Stanley, K.O.1
Miikkulainen, R.2
-
21
-
-
24944537843
-
Large margin methods for structured and interdependent output variables
-
I. Tsochantaridis, T. Joachims, T. Hofmann, and Y. Altun. Large margin methods for structured and interdependent output variables. Journal of Machine Learning Research, 6:1453-1484, 2005.
-
(2005)
Journal of Machine Learning Research
, vol.6
, pp. 1453-1484
-
-
Tsochantaridis, I.1
Joachims, T.2
Hofmann, T.3
Altun, Y.4
-
22
-
-
0242351908
-
Support vector regression as a signal discriminator in high energy physics
-
D.O. Whiteson and N.A. Naumann. Support vector regression as a signal discriminator in high energy physics. Neurocomputing, 55:251, 2003.
-
(2003)
Neurocomputing
, vol.55
, pp. 251
-
-
Whiteson, D.O.1
Naumann, N.A.2
-
23
-
-
33646714634
-
Evolutionary function approximation for reinforcement learning
-
7(May):877-917
-
S. Whiteson and P. Stone. Evolutionary function approximation for reinforcement learning. Journal of Machine Learning Research, 7(May):877-917, 2006.
-
(2006)
Journal of Machine Learning Research
-
-
Whiteson, S.1
Stone, P.2
-
24
-
-
0033362601
-
Evolving artificial neural networks
-
X. Yao. Evolving artificial neural networks. Proceedings of the IEEE, 87(9): 1423-1447, 1999.
-
(1999)
Proceedings of the IEEE
, vol.87
, Issue.9
, pp. 1423-1447
-
-
Yao, X.1
|