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 1726–1750 of 4891 papers

TitleStatusHype
Sparsity Turns Adversarial: Energy and Latency Attacks on Deep Neural Networks—0
Computationally and Statistically Efficient Truncated Regression—0
Computational Lower Bounds for Sparse PCA—0
Applications of Large Language Model Reasoning in Feature Generation—0
Computational Explorations in Biomedicine: Unraveling Molecular Dynamics for Cancer, Drug Delivery, and Biomolecular Insights using LAMMPS Simulations—0
Computational Efficiency under Covariate Shift in Kernel Ridge Regression—0
Applications of Knowledge Distillation in Remote Sensing: A Survey—0
Adversarial Purification for Data-Driven Power System Event Classifiers with Diffusion Models—0
A Comprehensive Review of Techniques, Algorithms, Advancements, Challenges, and Clinical Applications of Multi-modal Medical Image Fusion for Improved Diagnosis—0
3DSS-Mamba: 3D-Spectral-Spatial Mamba for Hyperspectral Image Classification—0
Perceptual Motor Learning with Active Inference Framework for Robust Lateral Control—0
Computational Efficiency in Multivariate Adversarial Risk Analysis Models—0
Application of Distributed Arithmetic to Adaptive Filtering Algorithms: Trends, Challenges and Future—0
On the Complexity of Winner Determination and Strategic Control in Conditional Approval Voting—0
Computational and Statistical Guarantees for Tensor-on-Tensor Regression with Tensor Train Decomposition—0
Appearance-based Gesture recognition in the compressed domain—0
Adversarial Imitation Learning via Random Search—0
Computational and Statistical Boundaries for Submatrix Localization in a Large Noisy Matrix—0
Appa: Bending Weather Dynamics with Latent Diffusion Models for Global Data Assimilation—0
Compression for Better: A General and Stable Lossless Compression Framework—0
Compressing Recurrent Neural Networks for FPGA-accelerated Implementation in Fluorescence Lifetime Imaging—0
A posteriori Trading-inspired Model-free Time Series Segmentation—0
Adversarial Contrastive Learning by Permuting Cluster Assignments—0
Compressed Sensing Based Residual Recovery Algorithms and Hardware for Modulo Sampling—0
Compressed Dynamic Mode Decomposition for Background Modeling—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified