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 4151–4200 of 4891 papers

TitleStatusHype
Advancing Distributed AC Optimal Power Flow for Integrated Transmission-Distribution Systems—0
Distributed Consensus Optimization with Consensus ALADIN—0
Distributed Cross-Channel Hierarchical Aggregation for Foundation Models—0
Distributed Differential Dynamic Programming Architectures for Large-Scale Multi-Agent Control—0
Distributed Differentially Private Data Analytics via Secure Sketching—0
Distributed Experiment Design and Control for Multi-agent Systems with Gaussian Processes—0
Distributed Flexible Nonlinear Tensor Factorization—0
Distributed Sketching Methods for Privacy Preserving Regression—0
Distributed Traffic Signal Control via Coordinated Maximum Pressure-plus-Penalty—0
Distributionally Robust Model Predictive Control with Total Variation Distance—0
Distribution-Aware Sampling and Weighted Model Counting for SAT—0
DITTO: Diffusion Inference-Time T-Optimization for Music Generation—0
Diverse super-resolution with pretrained deep hiererarchical VAEs—0
Divide-and-Conquer Strategy for Large-Scale Dynamic Bayesian Network Structure Learning—0
Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning—0
DLCM: a versatile multi-level solver for heterogeneous multicellular systems—0
DMFC-GraspNet: Differentiable Multi-Fingered Robotic Grasp Generation in Cluttered Scenes—0
DMRA: An Adaptive Line Spectrum Estimation Method through Dynamical Multi-Resolution of Atoms—0
DNA cyclization and looping in the wormlike limit: normal modes and the validity of the harmonic approximation—0
DNN-Compressed Domain Visual Recognition with Feature Adaptation—0
DN-ResNet: Efficient Deep Residual Network for Image Denoising—0
Do global forecasting models require frequent retraining?—0
DOLLAR: Few-Step Video Generation via Distillation and Latent Reward Optimization—0
Domain Adaptation Broad Learning System Based on Locally Linear Embedding—0
Domain Adaptation Extreme Learning Machines for Drift Compensation in E-nose Systems—0
Domain-Aware Few-Shot Learning for Optical Coherence Tomography Noise Reduction—0
Domain-Specific Japanese ELECTRA Model Using a Small Corpus—0
Don't Fall for Tuning Parameters: Tuning-Free Variable Selection in High Dimensions With the TREX—0
Don't forget, there is more than forgetting: new metrics for Continual Learning—0
Double Machine Learning for Adaptive Causal Representation in High-Dimensional Data—0
Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables—0
Do we become wiser with time? On causal equivalence with tiered background knowledge—0
DP-CDA: An Algorithm for Enhanced Privacy Preservation in Dataset Synthesis Through Randomized Mixing—0
DPERC: Direct Parameter Estimation for Mixed Data—0
DP-LET: An Efficient Spatio-Temporal Network Traffic Prediction Framework—0
DRACO: Co-Optimizing Hardware Utilization, and Performance of DNNs on Systolic Accelerator—0
DreamMesh4D: Video-to-4D Generation with Sparse-Controlled Gaussian-Mesh Hybrid Representation—0
DRL-based Dolph-Tschebyscheff Beamforming in Downlink Transmission for Mobile Users—0
DroidSpeak: KV Cache Sharing for Cross-LLM Communication and Multi-LLM Serving—0
DSMoE: Matrix-Partitioned Experts with Dynamic Routing for Computation-Efficient Dense LLMs—0
DST-TransitNet: A Dynamic Spatio-Temporal Deep Learning Model for Scalable and Efficient Network-Wide Prediction of Station-Level Transit Ridership—0
DS-VIO: Robust and Efficient Stereo Visual Inertial Odometry based on Dual Stage EKF—0
DTFSal: Audio-Visual Dynamic Token Fusion for Video Saliency Prediction—0
DTMNet: A Discrete Tchebichef Moments-Based Deep Neural Network for Multi-Focus Image Fusion—0
Dual Conditional Diffusion Models for Sequential Recommendation—0
Dual-control based approach to batch process operation under uncertainty based on optimality-conditions parameterization—0
DualFL: A Duality-based Federated Learning Algorithm with Communication Acceleration in the General Convex Regime—0
Dualformer: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces—0
Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to Non-smooth Concave Maximization—0
Dual optimization for convex constrained objectives without the gradient-Lipschitz assumption—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified