Search Results for author: Haoyang Liu

Found 23 papers, 6 papers with code

Distinguished Quantized Guidance for Diffusion-based Sequence Recommendation

no code implementations29 Jan 2025 Wenyu Mao, Shuchang Liu, Haoyang Liu, Haozhe Liu, Xiang Li, Lanatao Hu

To address these issues, we propose Distinguished Quantized Guidance for Diffusion-based Sequence Recommendation (DiQDiff), which aims to extract robust guidance to understand user interests and generate distinguished items for personalized user interests within DMs.

Denoising Quantization +1

MILP-StuDio: MILP Instance Generation via Block Structure Decomposition

no code implementations30 Oct 2024 Haoyang Liu, Jie Wang, Wanbo Zhang, Zijie Geng, Yufei Kuang, Xijun Li, Bin Li, Yongdong Zhang, Feng Wu

However, existing approaches do not take into account specific block structures -- which are closely related to the problem formulations -- in the constraint coefficient matrices (CCMs) of MILPs.

Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization

1 code implementation3 Aug 2024 Wenyu Mao, Jiancan Wu, Haoyang Liu, Yongduo Sui, Xiang Wang

In this work, we propose a novel framework, called Invariant Graph Learning based on Information bottleneck theory (InfoIGL), to extract the invariant features of graphs and enhance models' generalization ability to unseen distributions.

Contrastive Learning Data Augmentation +3

Emotion Detection through Body Gesture and Face

no code implementations13 Jul 2024 Haoyang Liu

The project leverages advanced machine and deep learning techniques to address the challenge of emotion recognition by focusing on non-facial cues, specifically hands, body gestures, and gestures.

Emotion Classification Emotion Recognition +1

GenoTEX: A Benchmark for Evaluating LLM-Based Exploration of Gene Expression Data in Alignment with Bioinformaticians

1 code implementation21 Jun 2024 Haoyang Liu, Haohan Wang

We propose GenoTEX as a promising resource for benchmarking and enhancing AI-driven methods for genomics data analysis.

Benchmarking Language Modelling +1

Deep Symbolic Optimization for Combinatorial Optimization: Accelerating Node Selection by Discovering Potential Heuristics

1 code implementation14 Jun 2024 Hongyu Liu, Haoyang Liu, Yufei Kuang, Jie Wang, Bin Li

With data-driven approaches, Dso4NS guides the search for mathematical expressions within the high-dimensional discrete symbolic space and then incorporates the highest-performing mathematical expressions into a solver.

Combinatorial Optimization

Approximate Nullspace Augmented Finetuning for Robust Vision Transformers

no code implementations15 Mar 2024 Haoyang Liu, Aditya Singh, Yijiang Li, Haohan Wang

In this work, we provide a finetuning approach to enhance the robustness of vision transformers inspired by the concept of nullspace from linear algebra.

Towards Adversarially Robust Dataset Distillation by Curvature Regularization

no code implementations15 Mar 2024 Eric Xue, Yijiang Li, Haoyang Liu, Peiran Wang, Yifan Shen, Haohan Wang

Extensive empirical experiments suggest that our method not only outperforms standard adversarial training on both accuracy and robustness with less computation overhead but is also capable of generating robust distilled datasets that can withstand various adversarial attacks.

Adversarial Robustness Dataset Distillation

Accelerating PDE Data Generation via Differential Operator Action in Solution Space

no code implementations4 Feb 2024 Huanshuo Dong, Hong Wang, Haoyang Liu, Jian Luo, Jie Wang

It applies differential operators on these solutions, a process we call 'operator action', to efficiently generate precise PDE data points.

Dataset Generation

Machine Learning Insides OptVerse AI Solver: Design Principles and Applications

no code implementations11 Jan 2024 Xijun Li, Fangzhou Zhu, Hui-Ling Zhen, Weilin Luo, Meng Lu, Yimin Huang, Zhenan Fan, Zirui Zhou, Yufei Kuang, Zhihai Wang, Zijie Geng, Yang Li, Haoyang Liu, Zhiwu An, Muming Yang, Jianshu Li, Jie Wang, Junchi Yan, Defeng Sun, Tao Zhong, Yong Zhang, Jia Zeng, Mingxuan Yuan, Jianye Hao, Jun Yao, Kun Mao

To this end, we present a comprehensive study on the integration of machine learning (ML) techniques into Huawei Cloud's OptVerse AI Solver, which aims to mitigate the scarcity of real-world mathematical programming instances, and to surpass the capabilities of traditional optimization techniques.

Decision Making Management

Dataset Distillation via the Wasserstein Metric

no code implementations30 Nov 2023 Haoyang Liu, Yijiang Li, Tiancheng Xing, Vibhu Dalal, Luwei Li, Jingrui He, Haohan Wang

Dataset Distillation (DD) emerges as a powerful strategy to encapsulate the expansive information of large datasets into significantly smaller, synthetic equivalents, thereby preserving model performance with reduced computational overhead.

Dataset Distillation

Beyond Pixels: Exploring Human-Readable SVG Generation for Simple Images with Vision Language Models

no code implementations27 Nov 2023 Tong Zhang, Haoyang Liu, Peiyan Zhang, Yuxuan Cheng, Haohan Wang

Our method focuses on producing SVGs that are both accurate and simple, aligning with human readability and understanding.

Vector Graphics

Promoting Generalization for Exact Solvers via Adversarial Instance Augmentation

no code implementations22 Oct 2023 Haoyang Liu, Yufei Kuang, Jie Wang, Xijun Li, Yongdong Zhang, Feng Wu

To tackle this problem, we propose a novel approach, which is called Adversarial Instance Augmentation and does not require to know the problem type for new instance generation, to promote data diversity for learning-based branching modules in the branch-and-bound (B&B) Solvers (AdaSolver).

Diversity Imitation Learning

Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models

no code implementations21 Aug 2023 Peiyan Zhang, Haoyang Liu, Chaozhuo Li, Xing Xie, Sunghun Kim, Haohan Wang

Machine learning has demonstrated remarkable performance over finite datasets, yet whether the scores over the fixed benchmarks can sufficiently indicate the model's performance in the real world is still in discussion.

Image Classification model

Towards Trustworthy and Aligned Machine Learning: A Data-centric Survey with Causality Perspectives

no code implementations31 Jul 2023 Haoyang Liu, Maheep Chaudhary, Haohan Wang

Accordingly, this survey presents the background of trustworthy machine learning development using a unified set of concepts, connects this language to Pearl's causal hierarchy, and finally discusses methods explicitly inspired by causality literature.

Adversarial Robustness Fairness +2

Augmented Lagrangian Methods for Time-varying Constrained Online Convex Optimization

no code implementations19 May 2022 Haoyang Liu, Xiantao Xiao, Liwei Zhang

Furthermore, we extend MALM to deal with time-varying functional constrained OCO with delayed feedback, in which the feedback information of loss and constraint functions is revealed to decision maker with delays.

UIUC\_BioNLP at SemEval-2021 Task 11: A Cascade of Neural Models for Structuring Scholarly NLP Contributions

1 code implementation SEMEVAL 2021 Haoyang Liu, M. Janina Sarol, Halil Kilicoglu

We propose a cascade of neural models that performs sentence classification, phrase recognition, and triple extraction to automatically structure the scholarly contributions of NLP publications.

Sentence Sentence Classification

UIUC_BioNLP at SemEval-2021 Task 11: A Cascade of Neural Models for Structuring Scholarly NLP Contributions

1 code implementation12 May 2021 Haoyang Liu, M. Janina Sarol, Halil Kilicoglu

We propose a cascade of neural models that performs sentence classification, phrase recognition, and triple extraction to automatically structure the scholarly contributions of NLP publications.

Keyphrase Extraction Relation Extraction +2

Exact high-dimensional asymptotics for Support Vector Machine

no code implementations13 May 2019 Haoyang Liu

In this paper, we consider the soft-margin SVM used on data points with independent features, where the sample size $n$ and the feature dimension $p$ grows to $\infty$ in a fixed ratio $p/n\rightarrow \delta$.

Vocal Bursts Intensity Prediction

An equivalence between critical points for rank constraints versus low-rank factorizations

no code implementations2 Dec 2018 Wooseok Ha, Haoyang Liu, Rina Foygel Barber

Two common approaches in low-rank optimization problems are either working directly with a rank constraint on the matrix variable, or optimizing over a low-rank factorization so that the rank constraint is implicitly ensured.

Optimization and Control

Between hard and soft thresholding: optimal iterative thresholding algorithms

no code implementations24 Apr 2018 Haoyang Liu, Rina Foygel Barber

Instead, a general class of thresholding operators, lying between hard thresholding and soft thresholding, is shown to be optimal with the strongest possible convergence guarantee among all thresholding operators.

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