Cross-entropy benchmarking (also referred to as XEB) is a quantum benchmarking protocol which can be used to demonstrate quantum supremacy. In XEB, a random...

quantum computing within the cloud. Cross-entropy benchmarking (also referred to as XEB), is quantum benchmarking protocol which can be used to demonstrate...

of pharmacological interest as well. Quantum random circuits Cross-entropy benchmarking Linear optical quantum computing KLM protocol Aaronson, Scott;...

problems a quantum computer can solve. Alternative benchmarks, such as Cross-entropy benchmarking, reliable Quantum Operations per Second (rQOPS) proposed...

qualifies as a quantum supercomputer. Alternative benchmarks include quantum volume, cross-entropy benchmarking, Circuit Layer Operations Per Second (CLOPS)...

{1}{N}}\sum _{i=1}^{N}\log _{b}q(x_{i})} may also be interpreted as a cross-entropy: H ( p ~ , q ) = − ∑ x p ~ ( x ) log b ⁡ q ( x ) {\displaystyle H({\tilde...

prevents creative writing benchmarks. Similarly, this prevents benchmarking writing proofs in natural language, though benchmarking proofs in a formal language...

Correlation entropy Approximate entropy Sample entropy Fourier entropy [uk] Wavelet entropy Dispersion entropy Fluctuation dispersion entropy Rényi entropy Higher-order...

M., 2001, "Updating and Estimating a Social Accounting Matrix Using Cross Entropy Methods", Economic Systems Research 13 (1), pp. 47–64. Stone, R. and...

evaluation and comparison of language models, cross-entropy is generally the preferred metric over entropy. The underlying principle is that a lower BPW...

expression is identical to the negative of the cross-entropy (see section on "Quantities of information (entropy)"). Therefore, finding the maximum of the...

The ORM is usually trained via logistic regression, i.e. minimizing cross-entropy loss. Given a PRM, an ORM can be constructed by multiplying the total...

sophisticated models, such as Good–Turing discounting or back-off models. Maximum entropy language models encode the relationship between a word and the n-gram history...

α Cross-correlation Cross-covariance Cross-entropy method Cross-sectional data Cross-sectional regression Cross-sectional study Cross-spectrum Cross tabulation...

bits of entropy. Because the technique obtains information about the user's GPU, the information entropy gained is "orthogonal" to the entropy of previous...

model corresponding to the subgraph is trained to minimize a canonical cross entropy loss. Multiple child models share parameters, ENAS requires fewer GPU-hours...

window and a fast entropy-coding stage. It uses both Huffman coding (used for entries in the Literals section) and finite-state entropy (FSE) – a fast tabled...

relying on gradient information. These include simulated annealing, cross-entropy search or methods of evolutionary computation. Many gradient-free methods...

The cross-entropy (CE) method generates candidate solutions via a parameterized probability distribution. The parameters are updated via cross-entropy minimization...

distances through past distances, use of move-to-front queue in entropy code selection, joint-entropy coding of literal and copy lengths, the use of graph algorithms...

been applied to the problem of POS tagging. Methods such as SVM, maximum entropy classifier, perceptron, and nearest-neighbor have all been tried, and most...

supervised model. In particular, it is trained to minimize the following cross-entropy loss function: L ( θ ) = − 1 ( K 2 ) E ( x , y w , y l ) [ log ⁡ ( σ...

codecs. Daala's entropy coder (daala_ec[citation needed]), a non-binary arithmetic coder, was selected for replacing VP9's binary entropy coder. The use...

optimization, river formation dynamics (see swarm intelligence), and the cross entropy method. This starts with a sub-tour such as the convex hull and then...

Retrieved 2018-10-04. "Google to Continue Collaboration with Quantum Benchmark". 24 October 2019. Metz, Cade (2017-11-13). "Yale Professors Race Google...

February 2006, pp. 104 - 112 Modis, Theodore (1 March 2022). "Links between entropy, complexity, and the technological singularity". Technological Forecasting...

predicting a single class of K mutually exclusive classes. Sigmoid cross-entropy loss is used for predicting K independent probability values in [ 0...

parameter Dyson's eternal intelligence – Hypothetical concept in astrophysics Entropy (arrow of time) – Use of the second law of thermodynamics to distinguish...

neural networks can be used to estimate the entropy of a stochastic process and called Neural Joint Entropy Estimator (NJEE). Such an estimation provides...

over the musical exposure created in each session a quantification of the cross communicability that produced clusters in line with the success of learning...