Results for "sensitivity to data"

Practices for operationalizing ML: versioning, CI/CD, monitoring, retraining, and reliable production management.

Central system to store model versions, metadata, approvals, and deployment state.

Ability to replicate results given same code/data; harder in distributed training and nondeterministic ops.

Observing model inputs/outputs, latency, cost, and quality over time to catch regressions and drift.

Attacks that manipulate model instructions (especially via retrieved content) to override system goals or exfiltrate data.

Models that process or generate multiple modalities, enabling vision-language tasks, speech, video understanding, etc.

Updating beliefs about parameters using observed evidence and prior distributions.

A theoretical framework analyzing what classes of functions can be learned, how efficiently, and with what guarantees.

Bayesian parameter estimation using the mode of the posterior distribution.

Using same parameters across different parts of a model.

Techniques to handle longer documents without quadratic cost.

A single attention mechanism within multi-head attention.

Capabilities that appear only beyond certain model sizes.

Chooses which experts process each token.

Probabilistic energy-based neural network with hidden variables.

Central catalog of deployed and experimental models.

Probabilistic graphical model for structured prediction.

Probabilistic model for sequential data with latent states.

Autoencoder using probabilistic latent variables and KL regularization.

Generator produces limited variety of outputs.

Classical statistical time-series model.

Persistent directional movement over time.

Identifying abrupt changes in data generation.

Model execution path in production.

Models effects of interventions (do(X=x)).

Agents communicate via shared state.

Cost to run models in production.

Mathematical foundation for ML involving vector spaces, matrices, and linear transformations.

Decomposes a matrix into orthogonal components; used in embeddings and compression.

Number of linearly independent rows or columns.