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Jia Shi

8 accepted papers

2026

Federated Manifold Learning (FML): Tackling Domain Heterogeneity with Structural Knowledge Transfer

ICML 2026poster

Federated Learning (FL) faces significant challenges due to domain heterogeneity, where data from different clients exhibit substantial statistical shifts that hinder the generalization of the global model. Although existing methods attempt to mitigate this by exchanging class prototypes, they fall …

Cited by 0SourceScholar
2024

Design-Modeling and Control of a Novel Wearable Exoskeleton for Lower-Limb Enhancement

RA-L 2024

In this paper, a novel powered lower limb exoskeleton prototype called PTEXO for reducing user burden and enhancing following comfort is presented. The PTEXO is designed with a new control strategy, Enhanced Sensitivity Amplification Control (ESAC), and improves comfort of lower-limb locomotion thro

Cited by 5SourceScholar
2024

LCA-on-the-Line: Benchmarking Out of Distribution Generalization with Class Taxonomies

ICML 2024oral

We tackle the challenge of predicting models' Out-of-Distribution (OOD) performance using in-distribution (ID) measurements without requiring OOD data. Existing evaluations with ``Effective robustness'', which use ID accuracy as an indicator of OOD accuracy, encounter limitations when models are tra…

2022

Physically-Based Editing of Indoor Scene Lighting from a Single Image

ECCV 2022poster

"We present a method to edit complex indoor lighting from a single image with its predicted depth and light source segmentation masks. This is an extremely challenging problem that requires modeling complex light transport, and disentangling HDR lighting from material and geometry with only a partia…

Cited by 61SourcePDFScholar
2021

OpenRooms: An Open Framework for Photorealistic Indoor Scene Datasets

CVPR 2021poster

We propose a novel framework for creating large-scale photorealistic datasets of indoor scenes, with ground truth geometry, material, lighting and semantics. Our goal is to make the dataset creation process widely accessible, allowing researchers to transform scans into datasets with highquality gro…

Cited by 93PDFScholar
2021

The CLEAR Benchmark: Continual LEArning on Real-World Imagery

NeurIPS 2021poster

Continual learning (CL) is widely regarded as crucial challenge for lifelong AI. However, existing CL benchmarks, e.g. Permuted-MNIST and Split-CIFAR, make use of artificial temporal variation and do not align with or generalize to the real- world. In this paper, we introduce CLEAR, the first contin…

Cited by 112SourcecodeScholar
2020

A Multi-Channel Reinforcement Learning Framework for Robotic Mirror Therapy

RA-L 2020

In the letter, a robotic framework is proposed for hemiparesis rehabilitation. Mirror therapy is applied to transfer therapeutic training from the patient's function limb (FL) to the impaired limb (IL). The IL mimics the action prescribed by the FL with the assistance of the wearable robot, stimulat

Cited by 29SourceScholar