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 1701–1725 of 4891 papers

TitleStatusHype
Approximate Steepest Coordinate Descent—0
Aeroengine performance prediction using a physical-embedded data-driven method—0
Approximate Model-Based Diagnosis Using Greedy Stochastic Search—0
Aerodynamic and structural airfoil shape optimisation via Transfer Learning-enhanced Deep Reinforcement Learning—0
A Comprehensive Survey of Action Quality Assessment: Method and Benchmark—0
4D Cardiac Ultrasound Standard Plane Location by Spatial-Temporal Correlation—0
Computing Forward Reachable Sets for Nonlinear Adaptive Multirotor Controllers—0
Computing Exact Shapley Values in Polynomial Time for Product-Kernel Methods—0
Approximately Aligned Decoding—0
Computation of safe disturbance sets using implicit RPI sets—0
Computation-efficient Virtual Sensing Approach with Multichannel Adjoint Least Mean Square Algorithm—0
Approximate Dynamic Programming for Constrained Piecewise Affine Systems with Stability and Safety Guarantees—0
A Dynamic Linear Bias Incorporation Scheme for Nonnegative Latent Factor Analysis—0
Computation and Communication Efficient Lightweighting Vertical Federated Learning for Smart Building IoT—0
Applying Incremental Learning in Binary-Addition-Tree Algorithm for Dynamic Binary-State Network Reliability—0
Accurate and efficient Simulation of very high-dimensional Neural Mass Models with distributed-delay Connectome Tensors—0
Computational-Statistical Tradeoffs from NP-hardness—0
Applications of Reinforcement Learning in Deregulated Power Market: A Comprehensive Review—0
A dynamic graph-cuts method with integrated multiple feature maps for segmenting kidneys in ultrasound images—0
Spike-and-slab shrinkage priors for structurally sparse Bayesian neural networks—0
Computationally Efficient State and Model Estimation via Interval Observers for Partially Unknown Systems—0
Computationally efficient spatial rendering of late reverberation in virtual acoustic environments—0
Applications of Nature-Inspired Algorithms for Dimension Reduction: Enabling Efficient Data Analytics—0
Computationally Efficient Safe Control of Linear Systems under Severe Sensor Attacks—0
Applications of ML-Based Surrogates in Bayesian Approaches to Inverse Problems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified