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 3901–3950 of 4891 papers

TitleStatusHype
Optimal scheduling of island integrated energy systems considering multi-uncertainties and hydrothermal simultaneous transmission: A deep reinforcement learning approach—0
Optimal Task and Motion Planning for Autonomous Systems Using Petri Nets—0
Optimal Thermal Management, Charging, and Eco-driving of Battery Electric Vehicles—0
Optimal transport for vector Gaussian mixture models—0
Optimal Transport-inspired Deep Learning Framework for Slow-Decaying Kolmogorov n-width Problems: Exploiting Sinkhorn Loss and Wasserstein Kernel—0
Optimising 4th-Order Runge-Kutta Methods: A Dynamic Heuristic Approach for Efficiency and Low Storage—0
Optimism in the Face of Ambiguity Principle for Multi-Armed Bandits—0
Optimistic Optimization of Gaussian Process Samples—0
Optimization and Scalability of Collaborative Filtering Algorithms in Large Language Models—0
Optimization from Structured Samples for Coverage Functions—0
Optimization of Beyond Diagonal RIS: A Universal Framework Applicable to Arbitrary Architectures—0
Optimization of Layer Skipping and Frequency Scaling for Convolutional Neural Networks under Latency Constraint—0
Optimization of Rocker-Bogie Mechanism using Heuristic Approaches—0
Optimization problems with low SWaP tactical Computing—0
Improved optimization strategies for deep Multi-Task Networks—0
Optimized CNNs for Rapid 3D Point Cloud Object Recognition—0
Optimizing Deep Decarbonization Pathways in California with Power System Planning Using Surrogate Level-based Lagrangian Relaxation—0
Optimized Feedforward Neural Network Training for Efficient Brillouin Frequency Shift Retrieval in Fiber—0
Optimized preprocessing and Tiny ML for Attention State Classification—0
Optimizing a Bayesian method for estimating the Hurst exponent in behavioral sciences—0
Optimizing Automatic Differentiation with Deep Reinforcement Learning—0
Optimizing Distributed Training on Frontier for Large Language Models—0
Optimizing Kernel Machines using Deep Learning—0
Optimizing Language Models for Grammatical Acceptability: A Comparative Study of Fine-Tuning Techniques—0
Optimizing Large Language Models with an Enhanced LoRA Fine-Tuning Algorithm for Efficiency and Robustness in NLP Tasks—0
Optimizing Memory Efficiency for Deep Convolutional Neural Networks on GPUs—0
Optimizing Over All Sequences of Orthogonal Polynomials—0
Optimizing Parameter Estimation for Electrochemical Battery Model: A Comparative Analysis of Operating Profiles on Computational Efficiency and Accuracy—0
Optimizing Quantized Neural Networks with Natural Gradient—0
Deep learning of transition probability densities for stochastic asset models with applications in option pricing—0
OptoGPT: A Foundation Model for Inverse Design in Optical Multilayer Thin Film Structures—0
Optuna vs Code Llama: Are LLMs a New Paradigm for Hyperparameter Tuning?—0
Oracle-Efficient Algorithms for Online Linear Optimization with Bandit Feedback—0
Oracle-Efficient Differentially Private Learning with Public Data—0
OrchestraLLM: Efficient Orchestration of Language Models for Dialogue State Tracking—0
Orchestration of Emulator Assisted Mobile Edge Tuning for AI Foundation Models: A Multi-Agent Deep Reinforcement Learning Approach—0
Orchid: Flexible and Data-Dependent Convolution for Sequence Modeling—0
Orientation-aware interaction-based deep material network in polycrystalline materials modeling—0
Orthogonal Stochastic Configuration Networks with Adaptive Construction Parameter for Data Analytics—0
OSPC: Artificial VLM Features for Hateful Meme Detection—0
Outlier-aware Tensor Robust Principal Component Analysis with Self-guided Data Augmentation—0
Overcoming the Stability Gap in Continual Learning—0
Overcoming Vocabulary Constraints with Pixel-level Fallback—0
PAC-Bayes Tree: weighted subtrees with guarantees—0
PADRe: A Unifying Polynomial Attention Drop-in Replacement for Efficient Vision Transformer—0
Pairwise Geometric Matching for Large-Scale Object Retrieval—0
PAM-UNet: Shifting Attention on Region of Interest in Medical Images—0
PanGu-Draw: Advancing Resource-Efficient Text-to-Image Synthesis with Time-Decoupled Training and Reusable Coop-Diffusion—0
Pan-LUT: Efficient Pan-sharpening via Learnable Look-Up Tables—0
Pan-Sharpening With a Hyper-Laplacian Penalty—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified