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Approximation error
Known as:
Percentage error
, Absolute Uncertainty
, Percent deviation
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The approximation error in some data is the discrepancy between an exact value and some approximation to it. An approximation error can occur because…
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Related topics
Related topics
22 relations
Algorithm
Approximation
Approximation theory
Belief propagation
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Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2018
Highly Cited
2018
Addressing Function Approximation Error in Actor-Critic Methods
Scott Fujimoto
,
H. V. Hoof
,
D. Meger
International Conference on Machine Learning
2018
Corpus ID: 3544558
In value-based reinforcement learning methods such as deep Q-learning, function approximation errors are known to lead to…
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Highly Cited
2015
Highly Cited
2015
Deep Reinforcement Learning with Double Q-Learning
H. V. Hasselt
,
A. Guez
,
David Silver
AAAI Conference on Artificial Intelligence
2015
Corpus ID: 6208256
The popular Q-learning algorithm is known to overestimate action values under certain conditions. It was not previously known…
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Highly Cited
2006
Highly Cited
2006
Improved Approximation Algorithms for Large Matrices via Random Projections
Tamás Sarlós
IEEE Annual Symposium on Foundations of Computer…
2006
Corpus ID: 1299951
Several results appeared that show significant reduction in time for matrix multiplication, singular value decomposition as well…
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Highly Cited
2003
Highly Cited
2003
ESTIMATING THE APPROXIMATION ERROR IN LEARNING THEORY
S. Smale
,
Ding-Xuan Zhou
2003
Corpus ID: 14849711
Let B be a Banach space and (ℋ,‖·‖ℋ) be a dense, imbedded subspace. For a ∈ B, its distance to the ball of ℋ with radius R…
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Highly Cited
2001
Highly Cited
2001
Greedy function approximation: A gradient boosting machine.
J. Friedman
2001
Corpus ID: 39450643
Function estimation/approximation is viewed from the perspective of numerical optimization in function space, rather than…
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Highly Cited
1998
Highly Cited
1998
Metro: Measuring Error on Simplified Surfaces
Paolo Cignoni
,
C. Rocchini
,
Roberto Scopigno
Computer graphics forum (Print)
1998
Corpus ID: 17783159
This paper presents a new tool, Metro, designed to compensate for a deficiency in many simplification methods proposed in…
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Highly Cited
1997
Highly Cited
1997
Wrappers for Feature Subset Selection
Ron Kohavi
,
George H. John
Artificial Intelligence
1997
Corpus ID: 15943670
Highly Cited
1997
Highly Cited
1997
Generalized Gradient Approximation Made Simple [Phys. Rev. Lett. 77, 3865 (1996)]
J. Perdew
,
K. Burke
,
M. Ernzerhof
1997
Corpus ID: 120827587
For the molecules Be2, F2, and P2 of Table I, the unrestricted Hartree-Fock solution breaks the singlet spin symmetry, even…
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Highly Cited
1996
Highly Cited
1996
Analysis of Temporal-Diffference Learning with Function Approximation
J. Tsitsiklis
,
Benjamin Van Roy
NIPS
1996
Corpus ID: 7353554
We present new results about the temporal-difference learning algorithm, as applied to approximating the cost-to-go function of a…
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Highly Cited
1993
Highly Cited
1993
Universal approximation bounds for superpositions of a sigmoidal function
A. Barron
IEEE Transactions on Information Theory
1993
Corpus ID: 15383918
Approximation properties of a class of artificial neural networks are established. It is shown that feedforward networks with one…
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