learning, a neural scaling law is an empirical scaling law that describes how neural network performance changes as key factors are scaled up or down....

power laws are Pareto's law of income distribution, structural self-similarity of fractals, scaling laws in biological systems, and scaling laws in cities...

performance; see Neural scaling law Tooth scaling, in dentistry, the removal of plaque and calculus Fouling, i.e., formation of a deposit layer (scale) on a solid...

laws – Adages and sayings named after a person List of laws § Technology Microprocessor chronology – Timeline of microprocessors Neural scaling law –...

been confirmed numerically. The scaling behavior of double descent has been found to follow a broken neural scaling law functional form. Grokking (machine...

"Scaling laws" are empirical statistical laws that predict LLM performance based on such factors. One particular scaling law ("Chinchilla scaling") for...

Language Models". arXiv:2203.15556 [cs.CL]. Table 20 and page 66 of PaLM: Scaling Language Modeling with Pathways Archived 2023-06-10 at the Wayback Machine...

Machine Intelligence Research Institute Machine learning Neural scaling law – Statistical law in machine learning Noosphere – Philosophical concept of...

scaling may refer to: Applying a scale ratio to create a scale model, a physical representation of an object Scaling up a neural network; see neural scaling...

these applications. The prior knowledge of general physical laws acts in the training of neural networks (NNs) as a regularization agent that limits the...

with infinite-dimensional noise. Backtracking line search Broken Neural Scaling Law Coordinate descent – changes one coordinate at a time, rather than...

Solving multiple machine learning tasks at the same time Neural scaling law – Statistical law in machine learning Outline of artificial intelligence –...

In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a computational model inspired by the structure...

Ethan; Gupta, Kshitij; Rish, Irina; Krueger, David (2022). Broken Neural Scaling Laws. International Conference on Learning Representations (ICLR), 2023...

Rewon; Gray, Scott; Radford, Alec; Wu, Jeffrey (22 January 2020), Scaling Laws for Neural Language Models, arXiv:2001.08361 Jo, Eun Seo; Gebru, Timnit (27...

language models. It is an emergent property of model scale, meaning that breaks in downstream scaling laws occur, leading to its efficacy increasing at a different...

Ethan; Gupta, Kshitij; Rish, Irina; Krueger, David (2022). "Broken Neural Scaling Laws". arXiv:2210.14891 [cs.LG]. Dominguez, Daniel (May 19, 2022). "DeepMind...

behind NTK is not specific to neural networks and can be observed in generic nonlinear models, usually by a suitable scaling. Let f ( x ; θ ) {\displaystyle...

applications do not scale horizontally. Network function virtualization defines these terms differently: scaling out/in is the ability to scale by adding/removing...

Perception Sone Buchsbaum, M.; Stevens, S. S. (1971-04-30). "Neural Events and Psychophysical Law". Science. 170 (3962): 1043. Bibcode:1971Sci...172..502B...

is a subset of machine learning that focuses on utilizing multilayered neural networks to perform tasks such as classification, regression, and representation...

different units, hatching feature scaling – a method used to rescale data to a fixed range – like min-max scaling and robust scaling. This modern normalization...

An optical neural network is a physical implementation of an artificial neural network with optical components. Early optical neural networks used a photorefractive...

Neural adaptation or sensory adaptation is a gradual decrease over time in the responsiveness of the sensory system to a constant stimulus. It is usually...

argued that 1/f scaling in EEG recordings are inconsistent with critical states, and whether SOC is a fundamental property of neural systems remains an...

Neural Network Quantum States (NQS or NNQS) is a general class of variational quantum states parameterized in terms of an artificial neural network. It...

least approximately) fall into the class of scale-free networks, meaning that they have power-law (or scale-free) degree distributions, while random graph...

LeNet is a series of convolutional neural network architectures created by a research group in AT&T Bell Laboratories during the 1988 to 1998 period, centered...

A scale-free network is a network whose degree distribution follows a power law, at least asymptotically. That is, the fraction P(k) of nodes in the network...

re-phrased as scaling hierarchy of far more small things than large ones. It has been formulated as a scaling law. Spatial heterogeneity or scaling hierarchy...