beyond accuracy, recommendation systems
Beyond-accuracy objectives include diversity novelty serendipity and coverage in recommendation systems.
356 technical terms and definitions
Beyond-accuracy objectives include diversity novelty serendipity and coverage in recommendation systems.
Technologies after conventional transistors.
BF16 has same exponent as FP32, less precision. More stable than FP16. Preferred for training.
16-bit floating point format.
Size of solder balls.
Spacing between balls.
BGA X-ray inspection detects solder joint defects like voids bridges and insufficient wetting in ball grid array packages.
Encode query and documents separately.
Bi-encoders separately encode queries and documents for efficient similarity search.
Separate encoders for query and document.
Models exaggerating biases in data.
Datasets for measuring bias.
Bias evaluation measures unfair treatment across demographic groups.
Measurement bias is systematic offset between measured and true values.
Reduce bias in models.
Techniques to reduce unfair biases in model training data or outputs.
RF power applied to wafer electrode to control ion energy.
Systematic error in measurement.
HAST with voltage applied.
Each token can attend to all other tokens (BERT-style).
Predict from both directions.
Diverse challenging tasks.
BIG-Bench contains diverse tasks testing capabilities beyond current models.
Diverse collection of over 200 challenging tasks.
Sparse attention with random global and local.
BigBird uses sparse attention with local sliding window random and global connections.
Sparse attention with local global and random connections.
BigNAS scales once-for-all training to extremely large search spaces using improved sampling strategies.
BigVGAN uses large generators with anti-aliased periodic activation for high-fidelity neural vocoding.
BiLSTM-CRF combines bidirectional LSTMs with conditional random fields for sequence labeling with structured output constraints.
Bin color codes assign distinct colors to different test results for visual wafer map interpretation.
Bin map analysis examines spatial patterns in die sort categories revealing process and design issues.
Bin sorting classifies die into categories based on parametric measurements enabling product grading and yield reporting.
Breakdown of dies by performance bins.
Extreme quantization to 1-bit.
Simplified ion implant simulation.
Binary embeddings use binary vectors enabling extremely fast similarity computation.
Binary networks constrain weights and activations to binary values enabling extreme compression.
Weights and activations are binary.
Predict strength of molecular binding.
Sort chips into speed grades.
Binning converts continuous to categorical. Equal-width or equal-frequency.
Sort chips by performance speed power into different grades.
Biomedical semantic QA.
Biofilters use microorganisms to biologically degrade VOCs and odorous compounds.
BioGPT is Microsoft biomedical model. Literature mining.
Extract knowledge from medical literature.
Biplots simultaneously display observations and variables in reduced dimensional space.
On-chip test circuitry.
Built-In Self-Test incorporates on-chip test circuitry allowing devices to generate test patterns and evaluate responses without external equipment.