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 3426–3450 of 4891 papers

TitleStatusHype
An unsupervised, open-source workflow for 2D and 3D building mapping from airborne LiDAR data—0
Feature subset selection for kernel SVM classification via mixed-integer optimization—0
Laplace HypoPINN: Physics-Informed Neural Network for hypocenter localization and its predictive uncertainty—0
Will Bilevel Optimizers Benefit from Loops—0
Physics-Guided Hierarchical Reward Mechanism for Learning-Based Robotic Grasping—0
Orthogonal Stochastic Configuration Networks with Adaptive Construction Parameter for Data Analytics—0
Linear Algorithms for Robust and Scalable Nonparametric Multiclass Probability EstimationCode0
mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connectionsCode1
Randomly Initialized One-Layer Neural Networks Make Data Linearly Separable—0
Spatial Attention-based Implicit Neural Representation for Arbitrary Reduction of MRI Slice Spacing—0
Fast ABC-Boost: A Unified Framework for Selecting the Base Class in Multi-Class ClassificationCode1
Approximate Message Passing with Parameter Estimation for Heavily Quantized MeasurementsCode0
How Useful are Gradients for OOD Detection Really?—0
Diverse super-resolution with pretrained deep hiererarchical VAEs—0
Certified Error Control of Candidate Set Pruning for Two-Stage Relevance RankingCode0
Two-Step Question Retrieval for Open-Domain QACode0
Perfect Spectral Clustering with Discrete CovariatesCode0
M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems—0
Scalable Vehicle Re-Identification via Self-Supervision—0
Transkimmer: Transformer Learns to Layer-wise SkimCode1
Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNsCode0
Low-variance estimation in the Plackett-Luce model via quasi-Monte Carlo sampling—0
Contingency-constrained economic dispatch with safe reinforcement learning—0
View Synthesis with Sculpted Neural PointsCode1
Scalable Stochastic Parametric Verification with Stochastic Variational Smoothed Model Checking—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified