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Found 13 papers, 1 papers with code
High Perceptual Quality Wireless Image Delivery with Denoising Diffusion Models
We consider the image transmission problem over a noisy wireless channel via deep learning-based joint source-channel coding (DeepJSCC) along with a denoising diffusion probabilistic model (DDPM) at the receiver.
Variations on a Theme by Blahut and Arimoto
The Blahut-Arimoto (BA) algorithm has played a fundamental role in the numerical computation of rate-distortion (RD) functions.
Trading off Quality for Efficiency of Community Detection: An Inductive Method across Graphs
The trained model is then directly generalized to new unseen graphs for online CD without additional optimization, where a better trade-off between quality and efficiency can be achieved.
GPPF: A General Perception Pre-training Framework via Sparsely Activated Multi-Task Learning
SIMT lays the foundation of pre-training with large-scale multi-task multi-domain datasets and is proved essential for stable training in our GPPF experiments.
A Tensor-BTD-based Modulation for Massive Unsourced Random Access
In this letter, we propose a novel tensor-based modulation scheme for massive unsourced random access.
PartialFed: Cross-Domain Personalized Federated Learning via Partial Initialization
The superiority of our algorithm is proved by demonstrating the new state-of-the-art results on cross-domain federated classification and detection.
Harmonic Retrieval with $L_1$-Tucker Tensor Decomposition
We also develop a novel subcarrier recovery method for the proposed model.
Branch and Bound in Mixed Integer Linear Programming Problems: A Survey of Techniques and Trends
In order to improve the speed of B&B algorithms, learning techniques have been introduced in this algorithm recently.
Trading Quality for Efficiency of Graph Partitioning: An Inductive Method across Graphs
IGP is also a generic framework that can capture the permutation invariant partitioning ground-truth of historical snapshots in the offline training and tackle the online GP on graphs with non-fixed number of nodes and clusters.
A Convergent Semi-Proximal Alternating Direction Method of Multipliers for Recovering Internet Traffics from Link Measurements
Our model can be divided into a series of subproblems, which only relate to the traffics in a certain individual time interval.
Optimization and Control
Lower Bound on the Optimal Access Bandwidth of ($K+2,K,2$)-MDS Array Code with Degraded Read Friendly
Accessing the data in the failed disk (degraded read) with low latency is crucial for an erasure-coded storage system.
Information Theory Information Theory
Asymmetric Gained Deep Image Compression With Continuous Rate Adaptation
With the development of deep learning techniques, the combination of deep learning with image compression has drawn lots of attention.
GCN-GAN: A Non-linear Temporal Link Prediction Model for Weighted Dynamic Networks
Different from conventional techniques of temporal link prediction that ignore the potential non-linear characteristics and the informative link weights in the dynamic network, we introduce a novel non-linear model GCN-GAN to tackle the challenging temporal link prediction task of weighted dynamic networks.
