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 2251–2300 of 4891 papers

TitleStatusHype
Indirect Query Bayesian Optimization with Integrated Feedback—0
Deep Auto-Deferring Policy for Combinatorial Optimization—0
Deep-and-Wide Learning: Enhancing Data-Driven Inference via Synergistic Learning of Inter- and Intra-Data Representations—0
From S4 to Mamba: A Comprehensive Survey on Structured State Space Models—0
Deep Adaptive Interest Network: Personalized Recommendation with Context-Aware Learning—0
Deep Active Contours for Real-time 6-DoF Object Tracking—0
Action-Sufficient State Representation Learning for Control with Structural Constraints—0
Acc3D: Accelerating Single Image to 3D Diffusion Models via Edge Consistency Guided Score Distillation—0
Inference in Graphical Models via Semidefinite Programming Hierarchies—0
InfLocNet: Enhanced Lung Infection Localization and Disease Detection from Chest X-Ray Images Using Lightweight Deep Learning—0
Integrating Locality-Aware Attention with Transformers for General Geometry PDEs—0
Isogeometric Analysis for the Pricing of Financial Derivatives with Nonlinear Models: Convertible Bonds and Options—0
Decouple to Reconstruct: High Quality UHD Restoration via Active Feature Disentanglement and Reversible Fusion—0
A Hybrid Dynamic Subarray Architecture for Efficient DOA Estimation in THz Ultra-Massive Hybrid MIMO Systems—0
How Much is Enough? A Study on Diffusion Times in Score-based Generative Models—0
A Survey on Kolmogorov-Arnold Network—0
Action Recognition With Motion Diversification and Dynamic Selection—0
Improving the Efficiency of Gradient Descent Algorithms Applied to Optimization Problems with Dynamical Constraints—0
How Analysis Can Teach Us the Optimal Way to Design Neural Operators—0
HOPS: High-order Polynomials with Self-supervised Dimension Reduction for Load Forecasting—0
HoneyModels: Machine Learning Honeypots—0
Improving Spiking Sparse Recovery via Non-Convex Penalties—0
A Survey on Graph Condensation—0
Improving STDP-based Visual Feature Learning with Whitening—0
Improving the affordability of robustness training for DNNs—0
Improving trajectory continuity in drone-based crowd monitoring using a set of minimal-cost techniques and deep discriminative correlation filters—0
Decision Machines: Congruent Decision Trees—0
HLSAD: Hodge Laplacian-based Simplicial Anomaly Detection—0
Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs—0
hi-RF: Incremental Learning Random Forest for large-scale multi-class Data Classification—0
Improving Sampling Accuracy of Stochastic Gradient MCMC Methods via Non-uniform Subsampling of Gradients—0
High-Throughput Blind Co-Channel Interference Cancellation for Edge Devices Using Depthwise Separable Convolutions, Quantization, and Pruning—0
A Survey on Deep Learning Methods for Semantic Image Segmentation in Real-Time—0
High-Resolution Vision Transformers for Pixel-Level Identification of Structural Components and Damage—0
High-resolution efficient image generation from WiFi CSI using a pretrained latent diffusion model—0
Debiasing Classifiers by Amplifying Bias with Latent Diffusion and Large Language Models—0
A Hybrid Adaptive Nash Equilibrium Solver for Distributed Multi-Agent Systems with Game-Theoretic Jump Triggering—0
HMoE: Heterogeneous Mixture of Experts for Language Modeling—0
Holistic Evaluation Metrics: Use Case Sensitive Evaluation Metrics for Federated Learning—0
Decoder-only Architecture for Speech Recognition with CTC Prompts and Text Data Augmentation—0
Improving Satellite Imagery Masking using Multi-task and Transfer Learning—0
High Performance Visual Tracking with Circular and Structural Operators—0
High Performance Computing of Gene Regulatory Networks using a Message-Passing Model—0
High Order Collaboration-Oriented Federated Graph Neural Network for Accurate QoS Prediction—0
How Does Momentum Benefit Deep Neural Networks Architecture Design? A Few Case Studies—0
How important are faces for person re-identification?—0
Effective Probabilistic Time Series Forecasting with Fourier Adaptive Noise-Separated Diffusion—0
High Fidelity Text-to-Speech Via Discrete Tokens Using Token Transducer and Group Masked Language Model—0
How to Detect and Defeat Molecular Mirage: A Metric-Driven Benchmark for Hallucination in LLM-based Molecular Comprehension—0
DCT-SNN: Using DCT To Distribute Spatial Information Over Time for Low-Latency Spiking Neural Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified