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 3521–3530 of 4891 papers

TitleStatusHype
Random Fourier Features for Asymmetric Kernels—0
Computing Forward Reachable Sets for Nonlinear Adaptive Multirotor Controllers—0
Uncertainty-aware Efficient Subgraph Isomorphism using Graph Topology—0
GAGA: Deciphering Age-path of Generalized Self-paced Regularizer—0
Optimization of Rocker-Bogie Mechanism using Heuristic Approaches—0
SVNet: Where SO(3) Equivariance Meets Binarization on Point Cloud RepresentationCode0
A Non-Parametric Bootstrap for Spectral Clustering—0
Non-iterative generation of an optimal mesh for a blade passage using deep reinforcement learning—0
Hybrid Supervised and Reinforcement Learning for the Design and Optimization of Nanophotonic Structures—0
Multitask Learning via Shared Features: Algorithms and Hardness—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified