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 2861–2870 of 4891 papers

TitleStatusHype
An Efficient Implicit Neural Representation Image Codec Based on Mixed Autoregressive Model for Low-Complexity Decoding—0
PlaceFormer: Transformer-based Visual Place Recognition using Multi-Scale Patch Selection and Fusion—0
Falcon: Fair Active Learning using Multi-armed BanditsCode0
A Review of Physics-Informed Machine Learning Methods with Applications to Condition Monitoring and Anomaly Detection—0
OnDev-LCT: On-Device Lightweight Convolutional Transformers towards federated learning—0
MOSformer: Momentum encoder-based inter-slice fusion transformer for medical image segmentation—0
DITTO: Diffusion Inference-Time T-Optimization for Music Generation—0
TIM: An Efficient Temporal Interaction Module for Spiking Transformer—0
A Fast Effective Greedy Approach for MU-MIMO Beam Selection in mm-Wave and THz Communications—0
Efficient Data Shapley for Weighted Nearest Neighbor Algorithms—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified