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Hua Yu

7 accepted papers

2026

Bypassing the Transport Plan: Dynamic Reweighting for Out-of-Distribution Detection with Optimal Transport

CVPR 2026

Semi-supervised learning (SSL) has achieved remarkable progress by leveraging both limited labeled data and abundant unlabeled data. However, unlabeled datasets often contain out-of-distribution (OOD) samples from unknown classes, which can lead to performance degradation in open-set SSL scenarios.

Cited by 0SourceScholar
2025

Distinguish Then Exploit: Source-free Open Set Domain Adaptation via Weight Barcode Estimation and Sparse Label Assignment

CVPR 2025poster

Nowadays, domain adaptation techniques have been widely investigated for knowledge sharing from labeled source domain to unlabeled target domain. However, target domain may include some data samples that belong to unknown categories in real-world scenarios. Moreover, the target domain cannot access…

Cited by 0SourcePDFScholar
2025

Solving Discrete (Semi) Unbalanced Optimal Transport with Equivalent Transformation Mechanism and KKT-Multiplier Regularization

NeurIPS 2025poster

Semi-Unbalanced Optimal Transport (SemiUOT) shows great promise in matching two probability measures by relaxing one of the marginal constraints. Previous solvers often incorporate an entropy regularization term, which can result in inaccurate matching solutions. To address this issue, we focus on d…

Cited by 0SourceScholar
2024

TFGDA: Exploring Topology and Feature Alignment in Semi-supervised Graph Domain Adaptation through Robust Clustering

NeurIPS 2024poster

Semi-supervised graph domain adaptation, as a branch of graph transfer learning, aims to annotate unlabeled target graph nodes by utilizing transferable knowledge learned from a label-scarce source graph. However, most existing studies primarily concentrate on aligning feature distributions directly…

Cited by 3SourcePDFScholar
2023

Improving Domain Generalization for Prompt-Aware Essay Scoring via Disentangled Representation Learning

ACL 2023long

Automated Essay Scoring (AES) aims to score essays written in response to specific prompts. Many AES models have been proposed, but most of them are either prompt-specific or prompt-adaptive and cannot generalize well on “unseen” prompts. This work focuses on improving the generalization ability of…

Cited by 14SourcePDFScholar
2020

A Symmetric Local Search Network for Emotion-Cause Pair Extraction

COLING 2020main

Emotion-cause pair extraction (ECPE) is a new task which aims at extracting the potential clause pairs of emotions and corresponding causes in a document. To tackle this task, a two-step method was proposed by previous study which first extracted emotion clauses and cause clauses individually, then…

2015

Low-complexity minimum-SER channel equalization for OFDM underwater acoustic communications

ICASSP 2015accepted

Orthogonal frequency division multiplexing (OFDM) is promising for underwater acoustic (UWA) communications as it is robust against large delay spread. However, OFDM suffers from intercarrier interference (ICI) caused by the serious Doppler effect in UWA channels. Attentive to the property that the…

Cited by 0SourceScholar