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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3751–3775 of 4891 papers

TitleStatusHype
ZoPE: A Fast Optimizer for ReLU Networks with Low-Dimensional Inputs—0
Ex uno plures: Splitting One Model into an Ensemble of Subnetworks—0
Fast and More Powerful Selective Inference for Sparse High-order Interaction Model—0
Obtaining Better Static Word Embeddings Using Contextual Embedding ModelsCode1
End-to-end reconstruction meets data-driven regularization for inverse problemsCode0
Stochastic filtering for multiscale stochastic reaction networks based on hybrid approximationsCode0
Learning Routines for Effective Off-Policy Reinforcement Learning—0
Hierarchical Temperature Imaging Using Pseudo-Inversed Convolutional Neural Network Aided TDLAS Tomography—0
Nonuniform Defocus Removal for Image Classification—0
Gradient Boosted Binary Histogram Ensemble for Large-scale Regression—0
ProtoRes: Proto-Residual Network for Pose Authoring via Learned Inverse KinematicsCode0
Uni-Encoder: A Fast and Accurate Response Selection Paradigm for Generation-Based Dialogue SystemsCode0
Bottom-up and top-down approaches for the design of neuromorphic processing systems: Tradeoffs and synergies between natural and artificial intelligence—0
Smart Online Charging Algorithm for Electric Vehicles via Customized Actor-Critic Learning—0
A Question of Time: Revisiting the Use of Recursive Filtering for Temporal Calibration of Multisensor Systems—0
Sub-Character Tokenization for Chinese Pretrained Language ModelsCode1
Pixel super-resolved lensless on-chip sensor with scattering multiplexing—0
Not All Images are Worth 16x16 Words: Dynamic Transformers for Efficient Image RecognitionCode1
TransCamP: Graph Transformer for 6-DoF Camera Pose Estimation—0
Robust Regularization with Adversarial Labelling of Perturbed Samples—0
A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networksCode1
Federated Learning for Short-term Residential Load Forecasting—0
One4all User Representation for Recommender Systems in E-commerce—0
Revisiting 2D Convolutional Neural Networks for Graph-based Applications—0
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified