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 3551–3560 of 4891 papers

TitleStatusHype
Graph Regularized Nonnegative Latent Factor Analysis Model for Temporal Link Prediction in Cryptocurrency Transaction Networks—0
A Screening Strategy for Structured Optimization Involving Nonconvex _q,p Regularization—0
A Real-time Edge-AI System for Reef Surveys—0
Neural Architecture Search on Efficient Transformers and Beyond—0
Distributed Differential Dynamic Programming Architectures for Large-Scale Multi-Agent Control—0
Integrating Statistical and Machine Learning Approaches to Identify Receptive Field Structure in Neural Populations—0
Statistical and Computational Trade-offs in Variational Inference: A Case Study in Inferential Model Selection—0
Fast Data Driven Estimation of Cluster Number in Multiplex Images using Embedded Density Outliers—0
Generalized Analysis and Unified Design of EM Skins—0
BIP: Boost Invariant Polynomials for Efficient Jet TaggingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified