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 4261–4270 of 4891 papers

TitleStatusHype
Efficient Global Multi-object Tracking Under Minimum-cost Circulation FrameworkCode0
Global Adaptive Generative Adjustment—0
Multi-scale Octave Convolutions for Robust Speech Recognition—0
Recovering BanditsCode0
A framework for deep learning emulation of numerical models with a case study in satellite remote sensingCode0
Quantum Computing based Hybrid Solution Strategies for Large-scale Discrete-Continuous Optimization Problems—0
Landmark Ordinal Embedding—0
Conditional Expectation Propagation—0
L*ReLU: Piece-wise Linear Activation Functions for Deep Fine-grained Visual Categorization—0
CrevNet: Conditionally Reversible Video Prediction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified