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Found 15 papers, 4 papers with code
CCFC++: Enhancing Federated Clustering through Feature Decorrelation
In federated clustering, multiple data-holding clients collaboratively group data without exchanging raw data.
CCFC: Bridging Federated Clustering and Contrastive Learning
Benefiting from representation learning, the clustering performance of CCFC even double those of the best baseline methods in some cases.
ClusterDDPM: An EM clustering framework with Denoising Diffusion Probabilistic Models
In the E-step, we aim to derive a mixture of Gaussian priors for the subsequent M-step.
Introspective Tips: Large Language Model for In-Context Decision Making
The emergence of large language models (LLMs) has substantially influenced natural language processing, demonstrating exceptional results across various tasks.
NoiseTrans: Point Cloud Denoising with Transformers
In addition, we also propose sparse encoding, which enables the Transformer to better perceive the structural relationships of the point cloud and improve the denoising performance.
Conservative State Value Estimation for Offline Reinforcement Learning
In this paper, we propose Conservative State Value Estimation (CSVE), a new approach that learns conservative V-function via directly imposing penalty on OOD states.
Privacy-Preserving Federated Deep Clustering based on GAN
Federated clustering (FC) is an essential extension of centralized clustering designed for the federated setting, wherein the challenge lies in constructing a global similarity measure without the need to share private data.
Federated clustering with GAN-based data synthesis
Federated clustering (FC) is an extension of centralized clustering in federated settings.
Drug repositioning for Alzheimer's disease with transfer learning
After training, the model is used for virtual screening to find potential drugs for Alzheimer's disease (AD) treatment.
Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach
This paper investigates a critical resource allocation problem in the first party cloud: scheduling containers to machines.
Selective clustering ensemble based on kappa and F-score
Clustering ensemble has an impressive performance in improving the accuracy and robustness of partition results and has received much attention in recent years.
A Surrogate Objective Framework for Prediction+Programming with Soft Constraints
Prediction+optimization is a common real-world paradigm where we have to predict problem parameters before solving the optimization problem.
A Surrogate Objective Framework for Prediction+Optimization with Soft Constraints
Prediction+optimization is a common real-world paradigm where we have to predict problem parameters before solving the optimization problem.
Kinetic Energy Distribution of Fragments for Thermal Neutron-Induced $^{235}$U and $^{239}$Pu Fission Reactions
(2) Every complementary pair of the primary fission fragments is approximatively described as two ellipsoids with large deformation at scission moment.
Nuclear Theory
Automatic Prosody Prediction for Chinese Speech Synthesis using BLSTM-RNN and Embedding Features
Prosody affects the naturalness and intelligibility of speech.
