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Efficient Neural Network

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Showing 151–175 of 224 papers

TitleStatusHype
LMR-CBT: Learning Modality-fused Representations with CB-Transformer for Multimodal Emotion Recognition from Unaligned Multimodal Sequences—0
Efficient Neural Network Training via Forward and Backward Propagation SparsificationCode0
DistIR: An Intermediate Representation and Simulator for Efficient Neural Network Distribution—0
On the Efficiency of Deep Neural Networks—0
Dynamic Neural Diversification: Path to Computationally Sustainable Neural Networks—0
Joint Matrix Decomposition for Deep Convolutional Neural Networks CompressionCode0
BasisNet: Two-stage Model Synthesis for Efficient Inference—0
Decentralized Inference with Graph Neural Networks in Wireless Communication Systems—0
A Survey of Quantization Methods for Efficient Neural Network Inference—0
Feature-Align Network with Knowledge Distillation for Efficient Denoising—0
SWIS -- Shared Weight bIt Sparsity for Efficient Neural Network Acceleration—0
Scaling the Convex Barrier with Sparse Dual Algorithms—0
UMEC: Unified model and embedding compression for efficient recommendation systems—0
MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training—0
CovSegNet: A Multi Encoder-Decoder Architecture for Improved Lesion Segmentation of COVID-19 Chest CT Scans—0
Rethinking Weight Decay For Efficient Neural Network PruningCode0
Evaluating Curriculum Learning Strategies in Neural Combinatorial Optimization—0
Neural Network Architectures for Location Estimation in the Internet of Things—0
Memformer: A Memory-Augmented Transformer for Sequence Modeling—0
Event-based update of synapses in voltage-based learning rules—0
On the Orthogonality of Knowledge Distillation with Other Techniques: From an Ensemble Perspective—0
Going deeper with brain morphometry using neural networks—0
Structured Convolutions for Efficient Neural Network Design—0
Dopant Network Processing Units: Towards Efficient Neural-network Emulators with High-capacity Nanoelectronic NodesCode0
Measurement error models: from nonparametric methods to deep neural networks—0
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