split learning, training techniques
Split learning partitions models across parties computing collaboratively without sharing data.
9,967 technical terms and definitions
Split learning partitions models across parties computing collaboratively without sharing data.
Split lots divide wafers for experimental conditions or parallel processing paths.
Run part of lot with change for comparison.
Split capacitance-voltage separates electron and hole accumulation measuring interface properties.
Capacitance-voltage measurement for interface states.
Compare process variations.
Handle hard-to-change and easy-to-change factors.
Combine split and federated learning.
Sulfuric acid + H2O2 for photoresist stripping and cleaning.
Sporadic losses are sudden unusual events causing obvious performance degradation.
Create play-by-play commentary.
Single Path One-Shot NAS trains supernet uniformly by sampling single paths improving architecture ranking accuracy.
Handle spot instance interruptions.
Spot/preemptible instances are 60-90% cheaper but can be terminated. Good for fault-tolerant batch training.
Spray cooling atomizes liquid into droplets that impinge and evaporate on surfaces for extreme heat removal.
Spray processors dispense chemicals as fine mist for uniform wafer treatment.
Measure resistivity vs depth.
Thermal spreading resistance increases when heat spreads from small die to larger heat spreader.
Sprint capacity temporarily increases output responding to demand spikes or recovering from disruptions.
Models learn shortcuts instead of true patterns.
Number of target atoms ejected per incident ion.
Bombard target with ions to eject atoms that deposit on wafer.
Combine IL and RL.
Soft Q Imitation Learning simplifies imitation learning by labeling expert demonstrations with reward one and agent experience with reward zero.
Generate database queries from natural language.
Generate SQL from natural language. Text-to-SQL models.
Text-to-SQL converts natural language to SQL queries. Requires schema understanding. Fine-tune or few-shot for accuracy.
I can help you design schemas, write SQL queries, optimize indexes, and explain Postgres/TimescaleDB features in simple terms.
Reading comprehension benchmark.
Stanford Question Answering Dataset tests reading comprehension.
Query-efficient black-box attack.
Squeeze-and-Excite adds channel attention. Recalibrate features. Small overhead, accuracy gain.
Channel-wise attention mechanism.
Squeeze-and-excitation blocks recalibrate channel-wise features through global pooling and gating.
Session-based Recommendation with Graph Neural Networks uses gated graph neural networks to model item transitions within sessions.
Tiny features on mask to improve main pattern.
Yield of memory arrays sensitive to variation.
Session-based recommendation with graph neural networks includes multiple architectural variants for capturing transitions.
Stochastic Recurrent Neural Network uses stochastic hidden states for modeling uncertainty in sequences.
Server-Sent Events stream data from server. One-way. Good for LLM token streaming.
Structural similarity measure.
Simultaneous Switching Output noise occurs when multiple drivers switch creating transient currents that couple into power and signal nets.
Statistical Static Timing Analysis propagates delay distributions through timing graphs.
Multi-class structured SVMs handle problems with structured inputs and multiple output classes using joint feature representations.
Consistency over time.
Measurement stability is consistency of bias over time.
Consistency of measurements over time.
Open-source latent diffusion model.
Stable Diffusion generates images through latent space diffusion with text conditioning.
Stable Diffusion generates images from text. Latent diffusion for efficiency. Open source, highly customizable.