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Found 15 papers, 1 papers with code
Fast and Accurate Cooperative Radio Map Estimation Enabled by GAN
In the 6G era, real-time radio resource monitoring and management are urged to support diverse wireless-empowered applications.
Improving the Expressive Power of Deep Neural Networks through Integral Activation Transform
The impressive expressive power of deep neural networks (DNNs) underlies their widespread applicability.
Knowledge Base Enabled Semantic Communication: A Generative Perspective
Semantic communication is widely touted as a key technology for propelling the sixth-generation (6G) wireless networks.
Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation
Unlike existing diffusion models that train neural networks to learn the score function, we develop a training-free score estimation method.
An Ensemble Score Filter for Tracking High-Dimensional Nonlinear Dynamical Systems
A major drawback of existing filtering methods, e. g., particle filters or ensemble Kalman filters, is the low accuracy in handling high-dimensional and highly nonlinear problems.
Practical Batch Bayesian Sampling Algorithms for Online Adaptive Traffic Experimentation
As new web algorithms proliferate, experimentation platform faces an increasing demand on the velocity of online experiments, which encourages adaptive traffic testing methods to speed up identifying best variant by efficiently allocating traffic.
TransNet: Transferable Neural Networks for Partial Differential Equations
Transfer learning for partial differential equations (PDEs) is to develop a pre-trained neural network that can be used to solve a wide class of PDEs.
Clustering-based Imputation for Dropout Buyers in Large-scale Online Experimentation
In online experimentation, appropriate metrics (e. g., purchase) provide strong evidence to support hypotheses and enhance the decision-making process.
Merchandise Recommendation for Retail Events with Word Embedding Weighted Tf-idf and Dynamic Query Expansion
To recommend relevant merchandises for seasonal retail events, we rely on item retrieval from marketplace inventory.
Low-Latency Cooperative Spectrum Sensing via Truncated Vertical Federated Learning
To accelerate the training process, we propose a truncated vertical federated learning (T-VFL) algorithm, where the training latency is highly reduced by integrating the standard VFL algorithm with a channel-aware user scheduling policy.
Accelerating Federated Edge Learning via Topology Optimization
In this paper, a novel topology-optimized federated edge learning (TOFEL) scheme is proposed to tackle the heterogeneity issue in federated learning and to improve the communication-and-computation efficiency.
Turning Channel Noise into an Accelerator for Over-the-Air Principal Component Analysis
The novelty of this design lies in exploiting channel noise to accelerate the descent in the region around each saddle point encountered by gradient descent, thereby increasing the convergence speed of over-the-air PCA.
Moving Metric Detection and Alerting System at eBay
At eBay, there are thousands of product health metrics for different domain teams to monitor.
An Introduction to Communication Efficient Edge Machine Learning
The main theme in the area is to design new communication techniques and protocols for efficient implementation of different distributed learning frameworks (i. e., federated learning) in wireless networks.
Information Theory Signal Processing Information Theory
Efficient Multivariate Bandit Algorithm with Path Planning
In this paper, we solve the arms exponential exploding issue in multivariate Multi-Armed Bandit (Multivariate-MAB) problem when the arm dimension hierarchy is considered.
