Ruixuan Liu | DeepAI

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∙ 09/20/2023

Simulation-aided Learning from Demonstration for Robotic LEGO Construction

Recent advancements in manufacturing have a growing demand for fast, aut...

0 Ruixuan Liu, et al. ∙

∙ 09/05/2023

A Lightweight and Transferable Design for Robust LEGO Manipulation

LEGO is a well-known platform for prototyping pixelized objects. However...

0 Ruixuan Liu, et al. ∙

∙ 08/20/2023

Robotic Planning under Hierarchical Temporal Logic Specifications

Past research into robotic planning with temporal logic specifications, ...

0 Xusheng Luo, et al. ∙

∙ 06/20/2023

Proactive Human-Robot Co-Assembly: Leveraging Human Intention Prediction and Robust Safe Control

Human-robot collaboration (HRC) is one key component to achieving flexib...

0 Ruixuan Liu, et al. ∙

∙ 05/25/2023

Robotic LEGO Assembly and Disassembly from Human Demonstration

This paper studies automatic prototyping using LEGO. To satisfy individu...

0 Ruixuan Liu, et al. ∙

∙ 05/23/2023

GUARD: A Safe Reinforcement Learning Benchmark

Due to the trial-and-error nature, it is typically challenging to apply ...

0 Weiye Zhao, et al. ∙

∙ 03/17/2023

Zero-shot Transferable and Persistently Feasible Safe Control for High Dimensional Systems by Consistent Abstraction

Safety is critical in robotic tasks. Energy function based methods have ...

0 Tianhao Wei, et al. ∙

∙ 11/29/2022

Double Robust Bayesian Inference on Average Treatment Effects

We study a double robust Bayesian inference procedure on the average tre...

0 Christoph Breunig, et al. ∙

∙ 09/20/2022

Task-Agnostic Adaptation for Safe Human-Robot Handover

Human-robot interaction (HRI) is an important component to improve the f...

0 Ruixuan Liu, et al. ∙

∙ 04/18/2022

PrivateRec: Differentially Private Training and Serving for Federated News Recommendation

Privacy protection is an essential issue in personalized news recommenda...

0 Ruixuan Liu, et al. ∙

∙ 04/06/2022

Safe Interactive Industrial Robots using Jerk-based Safe Set Algorithm

The need to increase the flexibility of production lines is calling for ...

0 Ruixuan Liu, et al. ∙

∙ 03/28/2022

FLDP: Flexible strategy for local differential privacy

Local differential privacy (LDP), a technique applying unbiased statisti...

0 Dan Zhao, et al. ∙

∙ 02/16/2022

No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices

Federated learning (FL) is an important paradigm for training global mod...

0 Ruixuan Liu, et al. ∙

∙ 09/12/2021

Efficient-FedRec: Efficient Federated Learning Framework for Privacy-Preserving News Recommendation

News recommendation is critical for personalized news access. Most exist...

0 Jingwei Yi, et al. ∙

∙ 08/30/2021

FedKD: Communication Efficient Federated Learning via Knowledge Distillation

Federated learning is widely used to learn intelligent models from decen...

0 Chuhan Wu, et al. ∙

∙ 08/16/2021

IADA: Iterative Adversarial Data Augmentation Using Formal Verification and Expert Guidance

Neural networks (NNs) are widely used for classification tasks for their...

0 Ruixuan Liu, et al. ∙

∙ 09/17/2020

FLAME: Differentially Private Federated Learning in the Shuffle Model

Differentially private federated learning has been intensively studied. ...

0 Ruixuan Liu, et al. ∙

∙ 03/24/2020

FedSel: Federated SGD under Local Differential Privacy with Top-k Dimension Selection

As massive data are produced from small gadgets, federated learning on m...

0 Ruixuan Liu, et al. ∙

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