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 4301–4325 of 4891 papers

TitleStatusHype
Efficient MPC for Emergency Evasive Maneuvers, Part I: Hybridization of the Nonlinear Problem—0
Efficient Multi-Task Inferencing: Model Merging with Gromov-Wasserstein Feature Alignment—0
Efficient n-body simulations using physics informed graph neural networks—0
Breast Cancer Histopathology Classification using CBAM-EfficientNetV2 with Transfer Learning—0
Efficient Network Traffic Feature Sets for IoT Intrusion Detection—0
Efficient Neural Ranking using Forward Indexes and Lightweight Encoders—0
Efficient N:M Sparse DNN Training Using Algorithm, Architecture, and Dataflow Co-Design—0
Efficient Object-centric Representation Learning with Pre-trained Geometric Prior—0
Efficient Online Hyperparameter Optimization for Kernel Ridge Regression with Applications to Traffic Time Series Prediction—0
Efficient Optimization Accelerator Framework for Multistate Ising Problems—0
Efficient Oriented Object Detection with Enhanced Small Object Recognition in Aerial Images—0
Efficient or Powerful? Trade-offs Between Machine Learning and Deep Learning for Mental Illness Detection on Social Media—0
Efficient Output Kernel Learning for Multiple Tasks—0
Efficient PAC Learning from the Crowd—0
Efficient Parallel Audio Generation using Group Masked Language Modeling—0
Efficient Polyp Segmentation Via Integrity Learning—0
EfficientPose 6D: Scalable and Efficient 6D Object Pose Estimation—0
Noise-Aware Ensemble Learning for Efficient Radar Modulation Recognition—0
Efficient Regularized Least-Squares Algorithms for Conditional Ranking on Relational Data—0
Efficient Relational Learning with Hidden Variable Detection—0
Efficient Representations for High-Cardinality Categorical Variables in Machine Learning—0
Efficient safe learning for controller tuning with experimental validation—0
Efficient Scale Estimation Methods using Lightweight Deep Convolutional Neural Networks for Visual Tracking—0
Efficient Search-Based Weighted Model Integration—0
Efficient Second-Order Neural Network Optimization via Adaptive Trust Region Methods—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified