SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

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Showing 3251–3260 of 4891 papers

TitleStatusHype
Fast and efficient speech enhancement with variational autoencoders—0
Accelerating Parallel Stochastic Gradient Descent via Non-blocking Mini-batches—0
Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean EstimationCode0
Ensemble transport smoothing. Part I: Unified frameworkCode0
QuaLA-MiniLM: a Quantized Length Adaptive MiniLM—0
PAGE: Prototype-Based Model-Level Explanations for Graph Neural NetworksCode1
Learning to Optimize Permutation Flow Shop Scheduling via Graph-based Imitation Learning—0
Neural network-based CUSUM for online change-point detection—0
An Efficient Memory-Augmented Transformer for Knowledge-Intensive NLP TasksCode1
Collaborative Honeypot Defense in UAV Networks: A Learning-Based Game Approach—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified