PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization

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PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization

Chattez avec Graph Search

PROBING INTRACELLULAR ELASTICITY WITH MINIMAL-HESSIAN REGISTRATION

Communication-efficient distributed training of machine learning models

Feature-based encoding of face identity by single neurons in the human amygdala and hippocampus

Evaluation of the impact of lossy compression on event camera-based computer vision tasks

Posterior-Based Analysis of Spatio-Temporal Features for Sign Language Assessment

On the assessment of high-quality images: advances on the JPEG AIC-3 activity

A phase transition between positional and semantic learning in a solvable model of dot-product attention

Learning ground states of gapped quantum Hamiltonians with Kernel Methods

Probing the latent hierarchical structure of data via diffusion models

The JPEG AI Standard: Providing Efficient Human and Machine Visual Data Consumption

Advances on Real Time M/EEG Neural Feature Extraction

JPEG AIC-3 Dataset: Towards Defining the High Quality to Nearly Visually Lossless Quality Range

On the Performance of Subjective Visual Quality Assessment Protocols for Nearly Visually Lossless Image Compression

GraphFedAI framework for DDoS attack detection in IoT systems using federated learning and graph based artificial intelligence

Enhancing dynamic resource management in decentralized federated learning for collaborative edge Internet of Things

Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach

SoDaCam: Software-defined Cameras via Single-Photon Imaging

Time vs. Truth: Age-Distortion Tradeoffs and Strategies for Distributed Inference

Reliable Microsecond-Scale Distributed Computing

Building Chips Faster: Hardware-Compiler Co-Design for Accelerated RTL Simulation