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 4826–4850 of 4891 papers

TitleStatusHype
Implicit Regularization or Implicit Conditioning? Exact Risk Trajectories of SGD in High Dimensions—0
Importance Filtering with Risk Models for Complex Driving Situations—0
ImPosing: Implicit Pose Encoding for Efficient Visual Localization—0
Improved Algorithms for Overlapping and Robust Clustering of Edge-Colored Hypergraphs: An LP-Based Combinatorial Approach—0
Improved Brain Tumor Detection in MRI: Fuzzy Sigmoid Convolution in Deep Learning—0
Improved Distributed Principal Component Analysis—0
Improved model-free bounds for multi-asset options using option-implied information and deep learning—0
Denoising Diffusion Probabilistic Models for Magnetic Resonance Fingerprinting—0
Improving Autoregressive NLP Tasks via Modular Linearized Attention—0
Structured Dropout Variational Inference for Bayesian Neural Networks—0
Improving Bias in Facial Attribute Classification: A Combined Impact of KL Divergence induced Loss Function and Dual Attention—0
Improving Building Temperature Forecasting: A Data-driven Approach with System Scenario Clustering—0
Improving Conversational Abilities of Quantized Large Language Models via Direct Preference Alignment—0
Improving Harmful Text Detection with Joint Retrieval and External Knowledge—0
Improving Human Decision-Making by Discovering Efficient Strategies for Hierarchical Planning—0
Improving LoRA in Privacy-preserving Federated Learning—0
Improving Low-Fidelity Models of Li-ion Batteries via Hybrid Sparse Identification of Nonlinear Dynamics—0
Improving Out-of-Distribution Detection via Epistemic Uncertainty Adversarial Training—0
Improving Out-of-Distribution Detection with Markov Logic Networks—0
Improving Prostate Gland Segmenting Using Transformer based Architectures—0
Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs—0
Improving Sampling Accuracy of Stochastic Gradient MCMC Methods via Non-uniform Subsampling of Gradients—0
Improving Satellite Imagery Masking using Multi-task and Transfer Learning—0
Improving Significant Wave Height Prediction Using Chronos Models—0
Improving Spiking Sparse Recovery via Non-Convex Penalties—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified