Search Results for author: Yao Xiao

Found 37 papers, 10 papers with code

1-HKUST: Object Detection in ILSVRC 2014

no code implementations22 Sep 2014 Cewu Lu, Hao Chen, Qifeng Chen, Hei Law, Yao Xiao, Chi-Keung Tang

We participated in the object detection track of ILSVRC 2014 and received the fourth place among the 38 teams.

Object object-detection +3

A Supervised STDP-based Training Algorithm for Living Neural Networks

no code implementations30 Oct 2017 Yuan Zeng, Kevin Devincentis, Yao Xiao, Zubayer Ibne Ferdous, Xiaochen Guo, Zhiyuan Yan, Yevgeny Berdichevsky

Neural networks have shown great potential in many applications like speech recognition, drug discovery, image classification, and object detection.

BIG-bench Machine Learning Drug Discovery +7

Vehicle Detection in Deep Learning

no code implementations29 May 2019 Yao Xiao

Computer vision is developing rapidly with the support of deep learning techniques.

Region Proposal

Template-Instance Loss for Offline Handwritten Chinese Character Recognition

no code implementations12 Oct 2019 Yao Xiao, Dan Meng, Cewu Lu, Chi-Keung Tang

The long-standing challenges for offline handwritten Chinese character recognition (HCCR) are twofold: Chinese characters can be very diverse and complicated while similarly looking, and cursive handwriting (due to increased writing speed and infrequent pen lifting) makes strokes and even characters connected together in a flowing manner.

Offline Handwritten Chinese Character Recognition

A Vertex Cut based Framework for Load Balancing and Parallelism Optimization in Multi-core Systems

no code implementations9 Oct 2020 Guixiang Ma, Yao Xiao, Theodore L. Willke, Nesreen K. Ahmed, Shahin Nazarian, Paul Bogdan

High-level applications, such as machine learning, are evolving from simple models based on multilayer perceptrons for simple image recognition to much deeper and more complex neural networks for self-driving vehicle control systems. The rapid increase in the consumption of memory and computational resources by these models demands the use of multi-core parallel systems to scale the execution of the complex emerging applications that depend on them.

Batch Sequential Adaptive Designs for Global Optimization

no code implementations21 Oct 2020 Jianhui Ning, Yao Xiao, Zikang Xiong

The computation burden of the new method is much lighter, and the points clustering is also avoided.

Clustering

Enhance Gender and Identity Preservation in Face Aging Simulation for Infants and Toddlers

no code implementations15 Nov 2020 Yao Xiao, Yijun Zhao

We trained our model using the publicly available UTKFace dataset and evaluated our model by simulating up to 100 years of aging on 1, 156 male and 1, 207 female infant and toddler face photos.

Robust Autonomous Landing of UAV in Non-Cooperative Environments based on Dynamic Time Camera-LiDAR Fusion

no code implementations27 Nov 2020 Lyujie Chen, Xiaming Yuan, Yao Xiao, Yiding Zhang, Jihong Zhu

We have conducted extensive autonomous landing experiments in a variety of familiar or completely unknown environments, verifying that our model can adaptively balance the accuracy and speed, and the UAV can robustly select a safe landing site.

Depth Completion

Generative Auto-Encoder: Non-adversarial Controllable Synthesis with Disentangled Exploration

no code implementations1 Jan 2021 Yunhao Ge, Gan Xin, Zhi Xu, Yao Xiao, Yunkui Pang, Yining HE, Laurent Itti

DEAE can become a generative model and synthesis semantic controllable samples by interpolating latent code, which can even synthesis novel attribute value never is shown in the original dataset.

Attribute Data Augmentation +2

EMface: Detecting Hard Faces by Exploring Receptive Field Pyraminds

no code implementations21 May 2021 Leilei Cao, Yao Xiao, Lin Xu

Modern face detectors employ feature pyramids to deal with scale variation.

Face Detection

Interventional Video Grounding with Dual Contrastive Learning

1 code implementation CVPR 2021 Guoshun Nan, Rui Qiao, Yao Xiao, Jun Liu, Sicong Leng, Hao Zhang, Wei Lu

2) Meanwhile, we introduce a dual contrastive learning approach (DCL) to better align the text and video by maximizing the mutual information (MI) between query and video clips, and the MI between start/end frames of a target moment and the others within a video to learn more informative visual representations.

Causal Inference Contrastive Learning +2

Speaker-Oriented Latent Structures for Dialogue-Based Relation Extraction

1 code implementation11 Sep 2021 Guoshun Nan, Guoqing Luo, Sicong Leng, Yao Xiao, Wei Lu

Dialogue-based relation extraction (DiaRE) aims to detect the structural information from unstructured utterances in dialogues.

Dialog Relation Extraction Relation

Towards Generic Interface for Human-Neural Network Knowledge Exchange

no code implementations29 Sep 2021 Yunhao Ge, Yao Xiao, Zhi Xu, Linwei Li, Ziyan Wu, Laurent Itti

Take image classification as an example, HNI visualizes the reasoning logic of a NN with class-specific Structural Concept Graphs (c-SCG), which are human-interpretable.

Image Classification Zero-Shot Learning

Encouraging Disentangled and Convex Representation with Controllable Interpolation Regularization

no code implementations6 Dec 2021 Yunhao Ge, Zhi Xu, Yao Xiao, Gan Xin, Yunkui Pang, Laurent Itti

(2) They lack convexity constraints, which is important for meaningfully manipulating specific attributes for downstream tasks.

Data Augmentation Disentanglement +2

End-to-end Mapping in Heterogeneous Systems Using Graph Representation Learning

no code implementations25 Apr 2022 Yao Xiao, Guixiang Ma, Nesreen K. Ahmed, Mihai Capota, Theodore Willke, Shahin Nazarian, Paul Bogdan

To enable heterogeneous computing systems with autonomous programming and optimization capabilities, we propose a unified, end-to-end, programmable graph representation learning (PGL) framework that is capable of mining the complexity of high-level programs down to the universal intermediate representation, extracting the specific computational patterns and predicting which code segments would run best on a specific core in heterogeneous hardware platforms.

Graph Representation Learning

AutoFAS: Automatic Feature and Architecture Selection for Pre-Ranking System

no code implementations19 May 2022 Xiang Li, Xiaojiang Zhou, Yao Xiao, Peihao Huang, Dayao Chen, Sheng Chen, Yunsen Xian

Industrial search and recommendation systems mostly follow the classic multi-stage information retrieval paradigm: matching, pre-ranking, ranking, and re-ranking stages.

Information Retrieval Neural Architecture Search +3

Sampling Is All You Need on Modeling Long-Term User Behaviors for CTR Prediction

1 code implementation20 May 2022 Yue Cao, Xiaojiang Zhou, Jiaqi Feng, Peihao Huang, Yao Xiao, Dayao Chen, Sheng Chen

However, the retrieval-based methods are sub-optimal and would cause more or less information losses, and it's difficult to balance the effectiveness and efficiency of the retrieval algorithm.

Click-Through Rate Prediction Retrieval

Automated WBRT Treatment Planning via Deep Learning Auto-Contouring and Customizable Landmark-Based Field Aperture Design

no code implementations24 May 2022 Yao Xiao, Carlos Cardenas, Dong Joo Rhee, Tucker Netherton, Lifei Zhang, Callistus Nguyen, Raphael Douglas, Raymond Mumme, Stephen Skett, Tina Patel, Chris Trauernicht, Caroline Chung, Hannah Simonds, Ajay Aggarwal, Laurence Court

In this work, we developed and evaluated a novel pipeline consisting of two landmark-based field aperture generation approaches for WBRT treatment planning; they are fully automated and customizable.

Sequential image recovery using joint hierarchical Bayesian learning

no code implementations25 Jun 2022 Yao Xiao, Jan Glaubitz

We specifically consider the case where each data set is missing vital information, which prevents the accurate recovery of the individual images.

Deblurring Uncertainty Quantification

PatchZero: Defending against Adversarial Patch Attacks by Detecting and Zeroing the Patch

no code implementations5 Jul 2022 Ke Xu, Yao Xiao, Zhaoheng Zheng, Kaijie Cai, Ram Nevatia

Despite the diversity in attack patterns, adversarial patches tend to be highly textured and different in appearance from natural images.

Image Classification object-detection +3

Contributions of Shape, Texture, and Color in Visual Recognition

1 code implementation19 Jul 2022 Yunhao Ge, Yao Xiao, Zhi Xu, Xingrui Wang, Laurent Itti

We use human experiments to confirm that both HVE and humans predominantly use some specific features to support the classification of specific classes (e. g., texture is the dominant feature to distinguish a zebra from other quadrupeds, both for humans and HVE).

Attribute General Classification +2

Semi-supervised Learning with Deterministic Labeling and Large Margin Projection

1 code implementation17 Aug 2022 Ji Xu, Gang Ren, Yao Xiao, Shaobo Li, Guoyin Wang

Optimal leading forest (OLF) has been observed to have the advantage of revealing the difference evolution along a path within a subtree.

Active Learning Attribute

Determinate Node Selection for Semi-supervised Classification Oriented Graph Convolutional Networks

no code implementations11 Jan 2023 Yao Xiao, Ji Xu, Jing Yang, Shaobo Li

Graph Convolutional Networks (GCNs) have been proved successful in the field of semi-supervised node classification by extracting structural information from graph data.

Node Classification

Sequential edge detection using joint hierarchical Bayesian learning

no code implementations28 Feb 2023 Yao Xiao, Anne Gelb, Guohui Song

This paper introduces a new sparse Bayesian learning (SBL) algorithm that jointly recovers a temporal sequence of edge maps from noisy and under-sampled Fourier data.

Edge Detection

Masked Images Are Counterfactual Samples for Robust Fine-tuning

1 code implementation CVPR 2023 Yao Xiao, Ziyi Tang, Pengxu Wei, Cong Liu, Liang Lin

In this paper, based on causal analysis of the aforementioned problems, we propose a novel fine-tuning method, which uses masked images as counterfactual samples that help improve the robustness of the fine-tuning model.

counterfactual

Continual Learning in Open-vocabulary Classification with Complementary Memory Systems

no code implementations4 Jul 2023 Zhen Zhu, Weijie Lyu, Yao Xiao, Derek Hoiem

We introduce a method for flexible and efficient continual learning in open-vocabulary image classification, drawing inspiration from the complementary learning systems observed in human cognition.

Continual Learning Image Classification

SPM: Structured Pretraining and Matching Architectures for Relevance Modeling in Meituan Search

no code implementations15 Aug 2023 Wen Zan, Yaopeng Han, Xiaotian Jiang, Yao Xiao, Yang Yang, Dayao Chen, Sheng Chen

At pretraining stage, we propose an effective pretraining method that employs both query and multiple fields of document as inputs, including an effective information compression method for lengthy fields.

Language Modelling

DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

2 code implementations20 Sep 2023 Shengbin Yue, Wei Chen, Siyuan Wang, Bingxuan Li, Chenchen Shen, Shujun Liu, Yuxuan Zhou, Yao Xiao, Song Yun, Xuanjing Huang, Zhongyu Wei

We propose DISC-LawLLM, an intelligent legal system utilizing large language models (LLMs) to provide a wide range of legal services.

Legal Reasoning Retrieval

Decomposed Prompt Tuning via Low-Rank Reparameterization

1 code implementation16 Oct 2023 Yao Xiao, Lu Xu, Jiaxi Li, Wei Lu, XiaoLi Li

While prompt tuning approaches have achieved competitive performance with high efficiency, we observe that they invariably employ the same initialization process, wherein the soft prompt is either randomly initialized or derived from an existing embedding vocabulary.

Efficiently Visualizing Large Graphs

1 code implementation17 Oct 2023 Xinyu Li, Yao Xiao, Yuchen Zhou

Performing SPLEE to obtain a high-dimensional embedding of the large-scale graph and then using t-SGNE to reduce its dimension for visualization, we are able to visualize graphs with up to 300K nodes and 1M edges within 5 minutes and achieve approximately 10% improvement in visualization quality.

Dimensionality Reduction Graph Embedding

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