papers

Publications (5)

cs.NE2019

Inference with Hybrid Bio-hardware Neural Networks

Yuan Zeng, Zubayer Ibne Ferdous, Weixiang Zhang +6

To understand the learning process in brains, biologically plausible algorithms have been explored by modeling the detailed neuron properties and dynamics. On the other hand, simpl…

cs.RO2026

Towards a Data Flywheel for Embodied Intelligence in Logistics

Anlan Yu, Zaishu Chen, Zhiqing Hong +1

Embodied intelligence is moving from laboratory demonstrations toward industrial deployment, with the logistics industry serving as a key application scenario. Learning-based polic…

cs.LG2024

FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data

Shusen Jing, Anlan Yu, Shuai Zhang +1

Recent efforts have been made to integrate self-supervised learning (SSL) with the framework of federated learning (FL). One unique challenge of federated self-supervised learning…

cs.CV2026

BenchHAR: Benchmarking Self-Supervised Learning for Generalizable Sensor-based Activity Recognition

Yize Cai, Rui Feng, Anlan Yu +2

Human Activity Recognition (HAR) from wearable sensors supports broad healthcare and behavior science applications. However, data heterogeneity and the scarcity of labeled data lim…

cs.RO2026

WM-DAgger: Enabling Efficient Data Aggregation for Imitation Learning with World Models

Anlan Yu, Zaishu Chen, Peili Song +6

Imitation learning is a powerful paradigm for training robotic policies, yet its performance is limited by compounding errors: minor policy inaccuracies could drive robots into uns…