b'Dianbo Liu'

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Tim Miller
35 publications

research

∙ 05/27/2023

Attention Schema in Neural Agents

Attention has become a common ingredient in deep learning architectures....

0 Dianbo Liu, et al. ∙

research

∙ 05/26/2023

Enhancing Human Capabilities through Symbiotic Artificial Intelligence with Shared Sensory Experiences

The merging of human intelligence and artificial intelligence has long b...

0 Rui Hao, et al. ∙

research

∙ 02/21/2023

Reusable Slotwise Mechanisms

Agents that can understand and reason over the dynamics of objects can h...

0 Trang Nguyen, et al. ∙

research

∙ 12/20/2022

Construction of extra-large scale screening tools for risks of severe mental illnesses using real world healthcare data

Importance: The prevalence of severe mental illnesses (SMIs) in the Unit...

0 Dianbo Liu, et al. ∙

research

∙ 10/24/2022

GFlowOut: Dropout with Generative Flow Networks

Bayesian Inference offers principled tools to tackle many critical probl...

7 Dianbo Liu, et al. ∙

research

∙ 10/04/2022

Stateful active facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning

In cooperative multi-agent reinforcement learning, a team of agents work...

2 Dianbo Liu, et al. ∙

research

∙ 05/21/2022

Coordinating Policies Among Multiple Agents via an Intelligent Communication Channel

In Multi-Agent Reinforcement Learning (MARL), specialized channels are o...

41 Dianbo Liu, et al. ∙

research

∙ 05/19/2022

FedILC: Weighted Geometric Mean and Invariant Gradient Covariance for Federated Learning on Non-IID Data

Federated learning is a distributed machine learning approach which enab...

9 Lena Nehale-Ezzine, et al. ∙

research

∙ 02/02/2022

Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization

Vector Quantization (VQ) is a method for discretizing latent representat...

5 Dianbo Liu, et al. ∙

research

∙ 12/10/2021

PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical records

Federated machine learning is a versatile and flexible tool to utilize d...

0 Tianyi Zhang, et al. ∙

research

∙ 07/06/2021

Discrete-Valued Neural Communication

Deep learning has advanced from fully connected architectures to structu...

8 Dianbo Liu, et al. ∙

research

∙ 04/06/2021

hBert + BiasCorp – Fighting Racism on the Web

Subtle and overt racism is still present both in physical and online com...

21 Olawale Onabola, et al. ∙

research

∙ 12/01/2020

Patient similarity: methods and applications

Patient similarity analysis is important in health care applications. It...

0 Leyu Dai, et al. ∙

research

∙ 11/23/2020

FakeSafe: Human Level Data Protection by Disinformation Mapping using Cycle-consistent Adversarial Network

The concept of disinformation is to use fake messages to confuse people ...

0 Dianbo Liu, et al. ∙

research

∙ 04/08/2020

A machine learning methodology for real-time forecasting of the 2019-2020 COVID-19 outbreak using Internet searches, news alerts, and estimates from mechanistic models

We present a timely and novel methodology that combines disease estimate...

6 Dianbo Liu, et al. ∙

research

∙ 02/20/2020

Federated pretraining and fine tuning of BERT using clinical notes from multiple silos

Large scale contextual representation models, such as BERT, have signifi...

0 Dianbo Liu, et al. ∙

research

∙ 12/25/2019

Federated machine learning with Anonymous Random Hybridization (FeARH) on medical records

Sometimes electrical medical records are restricted and difficult to cen...

0 Jianfei Cui, et al. ∙

research

∙ 10/23/2019

Stochastic Channel-Based Federated Learning for Medical Data Privacy Preserving

Artificial neural network has achieved unprecedented success in the medi...

0 Rulin Shao, et al. ∙

research

∙ 10/04/2019

Privacy Preserving Stochastic Channel-Based Federated Learning with Neural Network Pruning

Artificial neural network has achieved unprecedented success in a wide v...

0 Rulin Shao, et al. ∙

research

∙ 10/04/2019

Confederated Machine Learning on Horizontally and Vertically Separated Medical Data for Large-Scale Health System Intelligence

A patient's health information is generally fragmented across silos. Tho...

0 Dianbo Liu, et al. ∙

research

∙ 08/14/2019

Two-stage Federated Phenotyping and Patient Representation Learning

A large percentage of medical information is in unstructured text format...

0 Dianbo Liu, et al. ∙

research

∙ 03/22/2019

Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records

Electronic medical records (EMRs) supports the development of machine le...

0 Li Huang, et al. ∙

research

∙ 12/23/2018

Artificial neural networks condensation: A strategy to facilitate adaption of machine learning in medical settings by reducing computational burden

Machine Learning (ML) applications on healthcare can have a great impact...

0 Dianbo Liu, et al. ∙

research

∙ 12/23/2018

Border Effect of Complex Network: An analysis on the cooperation network of movie stars across different regions

People always carry out social activities within certain geographic spac...

0 Wen Zhou, et al. ∙

research

∙ 12/23/2018

Movies Network as the Indicator of Globalization

The main research involving globalization nowadays is to describe the im...

0 Zilu Yu, et al. ∙

research

∙ 11/30/2018

LoAdaBoost:Loss-Based AdaBoost Federated Machine Learning on medical Data

Medical data are valuable for improvement of health care, policy making ...

0 Li Huang, et al. ∙

research

∙ 11/28/2018

FADL:Federated-Autonomous Deep Learning for Distributed Electronic Health Record

Electronic health record (EHR) data is collected by individual instituti...

0 Dianbo Liu, et al. ∙

research

∙ 11/04/2018

Genie: A Secure, Transparent Sharing and Services Platform for Genetic and Health Data

Artificial Intelligence (AI) incorporating genetic and medical informati...

0 Shifa Zhangy, et al. ∙

research

∙ 08/09/2017

DeepFaceLIFT: Interpretable Personalized Models for Automatic Estimation of Self-Reported Pain

Previous research on automatic pain estimation from facial expressions h...

0 Dianbo Liu, et al. ∙

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