conftrace_

heterogeneous datum

119 papers

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Co-occurring keywords

federated learning (1333) distributed learning (563) representation learning (6206) data heterogeneity (115) domain adaptation (4595) large language model (13587) model aggregation (156) knowledge distillation (3725) client-server architecture (44) communication efficiency (297)

Papers

Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning IJCAI 2022
Gaussian Copula Embeddings NIPS 2022
Using Multimodal Data and AI to Dynamically Map Flood Risk AAAI 2022
Contribution-Aware Federated Learning for Smart Healthcare AAAI 2022
Tutorial on Multimodal Machine Learning NAACL 2022
Collaborative Learning by Detecting Collaboration Partners NIPS 2022
A Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources ICML 2022
Differentially Private Federated Learning on Heterogeneous Data AISTATS 2022
Subspace Recovery from Heterogeneous Data with Non-isotropic Noise NIPS 2022
CD2-pFed: Cyclic Distillation-Guided Channel Decoupling for Model Personalization in Federated Learning CVPR 2022
Learn From Others and Be Yourself in Heterogeneous Federated Learning CVPR 2022
Regularized and Smooth Double Core Tensor Factorization for Heterogeneous Data JMLR 2022
Causal discovery with heterogeneous observational data UAI 2022
RelaySum for Decentralized Deep Learning on Heterogeneous Data NIPS 2021
DeepCOVID: An Operational Deep Learning-driven Framework for Explainable Real-time COVID-19 Forecasting AAAI 2021
Latent Gaussian process with composite likelihoods and numerical quadrature AISTATS 2021
On Generalization in Coreference Resolution EMNLP 2021
Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity ICML 2021
Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes AISTATS 2021
Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data AISTATS 2021
Data-Free Knowledge Distillation for Heterogeneous Federated Learning ICML 2021
An Information-Theoretic Approach on Causal Structure Learning for Heterogeneous Data Characteristics of Real-World Scenarios IJCAI 2021
VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data NIPS 2020
General Latent Feature Models for Heterogeneous Datasets JMLR 2020
A Federated Approach in Training Acoustic Models INTERSPEECH 2020