Results for "full pass through data"
Updated belief after observing data.
Running models locally.
Requirement to preserve relevant data.
Trend reversal when data is aggregated improperly.
A structured collection of examples used to train/evaluate models; quality, bias, and coverage often dominate outcomes.
A measurable property or attribute used as model input (raw or engineered), such as age, pixel intensity, or token ID.
A parameterized mapping from inputs to outputs; includes architecture + learned parameters.
When a model cannot capture underlying structure, performing poorly on both training and test data.
Systematic differences in model outcomes across groups; arises from data, labels, and deployment context.
Measure of consistency across labelers; low agreement indicates ambiguous tasks or poor guidelines.
Logging hyperparameters, code versions, data snapshots, and results to reproduce and compare experiments.
Structured dataset documentation covering collection, composition, recommended uses, biases, and maintenance.
Attacks that infer whether specific records were in training data, or reconstruct sensitive training examples.
Systematic review of model/data processes to ensure performance, fairness, security, and policy compliance.
Methods to protect model/data during inference (e.g., trusted execution environments) from operators/attackers.
Estimating parameters by maximizing likelihood of observed data.
Detecting unauthorized model outputs or data leaks.
Neural networks that operate on graph-structured data by propagating information along edges.
Models that define an energy landscape rather than explicit probabilities.
Attention between different modalities.
CNNs applied to time series.
End-to-end process for model training.
Centralized repository for curated features.
Scaling law optimizing compute vs data.
Belief before observing data.
Train/test environment mismatch.
Model trained on its own outputs degrades quality.
Storing results to reduce compute.
Software pipeline converting raw sensor data into structured representations.
Learning physical parameters from data.