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

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Showing 1711–1720 of 4891 papers

TitleStatusHype
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
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified