A note on entropy estimation
March 19, 2015 Β· Declared Dead Β· π Neural Computation
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Thomas SchΓΌrmann
arXiv ID
1503.05911
Category
physics.data-an
Cross-listed
cs.IT,
math.ST
Citations
13
Venue
Neural Computation
Last Checked
3 months ago
Abstract
We compare an entropy estimator $H_z$ recently discussed in [10] with two estimators $H_1$ and $H_2$ introduced in [6][7]. We prove the identity $H_z \equiv H_1$, which has not been taken into account in [10]. Then, we prove that the statistical bias of $H_1$ is less than the bias of the ordinary likelihood estimator of entropy. Finally, by numerical simulation we verify that for the most interesting regime of small sample estimation and large event spaces, the estimator $H_2$ has a significant smaller statistical error than $H_z$.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β physics.data-an
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
A deep convolutional neural network approach to single-particle recognition in cryo-electron microscopy
R.I.P.
π»
Ghosted
The Pandora Software Development Kit for Pattern Recognition
R.I.P.
π»
Ghosted
Emergence of Compositional Representations in Restricted Boltzmann Machines
R.I.P.
π»
Ghosted
Investigating echo state networks dynamics by means of recurrence analysis
R.I.P.
π»
Ghosted
Discovering state-parameter mappings in subsurface models using generative adversarial networks
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted