US 11650968

Here's a concise summary of US Patent 11650968:

Title: Systems and methods for predictive early stopping in neural network training

Assignee: Comet Ml Inc.

Inventors: Dhruv Nair, Gideon Mendels, Nimrod Lahav

Filing Date: 2019-12-09

Issue Date: 2023-05-16

Abstract: Systems and methods may train neural networks (NNs) and determine when to stop training to not waste computing or other resources when improvement is no longer likely. After a training period for a NN, a model trained using training data from other NNs may return a probability of improvement in the loss of the NN or a probability that the likely best loss of the NN is lower than the best loss of the other NNs for which hyperparameters have been chosen. Training may be stopped if the probability is less than a threshold, or a wait value is greater than a wait threshold.

Plain-Language Overview of Independent Claims:

The patent has several independent claims. Here's an overview of key independent claims in plain language:

• Claim 1: This claim describes a computer-implemented method for predictively stopping the training of a neural network (NN). The method involves:

  1. Training a target NN over a series of training periods (epochs), computing a loss for each period.
  2. Using a predictive model, which was trained on loss data from other NNs (not the target NN), to determine a probability of improvement in the target NN's loss. This model takes the target NN's parameters and current/historic loss data as input.
  3. Stopping the target NN's training if this determined probability of improvement is below a certain threshold, OR if a "wait value" (a counter for non-improvement) exceeds another threshold.

• Claim 10: This claim describes a computer system configured to perform the method outlined in Claim 1. It includes a processor, memory, and code which, when executed, carries out the steps of training the NN, determining the probability of improvement using the trained model, and stopping the training based on the thresholds.

• Claim 16: This claim describes a computer program product (e.g., a non-transitory computer-readable medium) that stores instructions which, when executed by a processor, cause the processor to perform the method of predictively stopping NN training as described in Claim 1.

CAFC 2026 Dockets Search:

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