output
20052026
most cited6G Internet of Things: A Comprehensive Survey

1.4k citations

Showing 2020 · cs.LGShow all

8 papers · 2 filters

cs.LG2020

Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization

Kien Do, Truyen Tran, Svetha Venkatesh

We propose two generic methods for improving semi-supervised learning (SSL). The first integrates weight perturbation (WP) into existing "consistency regularization" (CR) based met…

cs.LG2020★ 3 cited

Robustness and Diversity Seeking Data-Free Knowledge Distillation

Pengchao Han, Jihong Park, Shiqiang Wang +1

Knowledge distillation (KD) has enabled remarkable progress in model compression and knowledge transfer. However, KD requires a large volume of original data or their representatio…

cs.LG2020★ 3 cited

Neurocoder: Learning General-Purpose Computation Using Stored Neural Programs

Hung Le, Svetha Venkatesh

Artificial Neural Networks are uniquely adroit at machine learning by processing data through a network of artificial neurons. The inter-neuronal connection weights represent the l…

cs.LG2020

Sequential Subspace Search for Functional Bayesian Optimization Incorporating Experimenter Intuition

Alistair Shilton, Sunil Gupta, Santu Rana +1

We propose an algorithm for Bayesian functional optimisation - that is, finding the function to optimise a process - guided by experimenter beliefs and intuitions regarding the exp…

cs.LG2020★ 1 cited

Mix2FLD: Downlink Federated Learning After Uplink Federated Distillation With Two-Way Mixup

Seungeun Oh, Jihong Park, Eunjeong Jeong +3

This letter proposes a novel communication-efficient and privacy-preserving distributed machine learning framework, coined Mix2FLD. To address uplink-downlink capacity asymmetry, l…

cs.LG2020★ 3 cited

A Comprehensive Survey on Outlying Aspect Mining Methods

Durgesh Samariya, Jiangang Ma, Sunil Aryal

In recent years, researchers have become increasingly interested in outlying aspect mining. Outlying aspect mining is the task of finding a set of feature(s), where a given data ob…