activity
20212024
most citedInstanT: Semi-supervised Learning with Instance-dependent Thresholds

5 citations · 11 across the 9 of their papers we have counts for

collaborators

9 papers

cs.DS20241 cited

An Efficient and Exact Algorithm for Locally h-Clique Densest Subgraph Discovery

Xiaojia Xu, Haoyu Liu, Xiaowei Lv +2

Detecting locally, non-overlapping, near-clique densest subgraphs is a crucial problem for community search in social networks. As a vertex may be involved in multiple overlapped l…

cs.CV20241 cited

Intention-aware Denoising Diffusion Model for Trajectory Prediction

Chen Liu, Shibo He, Haoyu Liu +1

Trajectory prediction is an essential component in autonomous driving, particularly for collision avoidance systems. Considering the inherent uncertainty of the task, numerous stud…

cs.LG2024

TreeMIL: A Multi-instance Learning Framework for Time Series Anomaly Detection with Inexact Supervision

Chen Liu, Shibo He, Haoyu Liu +1

Time series anomaly detection (TSAD) plays a vital role in various domains such as healthcare, networks, and industry. Considering labels are crucial for detection but difficult to…

cs.HC2023

Towards Long-term Annotators: A Supervised Label Aggregation Baseline

Haoyu Liu, Fei Wang, Minmin Lin +6

Relying on crowdsourced workers, data crowdsourcing platforms are able to efficiently provide vast amounts of labeled data. Due to the variability in the annotation quality of crow…

cs.CR20232 cited

Amoeba: Circumventing ML-supported Network Censorship via Adversarial Reinforcement Learning

Haoyu Liu, Alec F. Diallo, Paul Patras

Embedding covert streams into a cover channel is a common approach to circumventing Internet censorship, due to censors' inability to examine encrypted information in otherwise per…

cs.LG20235 cited

InstanT: Semi-supervised Learning with Instance-dependent Thresholds

Muyang Li, Runze Wu, Haoyu Liu +4

Semi-supervised learning (SSL) has been a fundamental challenge in machine learning for decades. The primary family of SSL algorithms, known as pseudo-labeling, involves assigning…