Search Results for author: Yang Jiao

Found 35 papers, 10 papers with code

Eyes Can Deceive: Benchmarking Counterfactual Reasoning Abilities of Multi-modal Large Language Models

no code implementations19 Apr 2024 Yian Li, Wentao Tian, Yang Jiao, Jingjing Chen, Yu-Gang Jiang

Counterfactual reasoning, as a crucial manifestation of human intelligence, refers to making presuppositions based on established facts and extrapolating potential outcomes.

Benchmarking counterfactual +3

Detection of Problem Gambling with Less Features Using Machine Learning Methods

no code implementations23 Mar 2024 Yang Jiao, Gloria Wong-Padoongpatt, Mei Yang

Analytic features in gambling study are performed based on the amount of data monitoring on user daily actions.

From Canteen Food to Daily Meals: Generalizing Food Recognition to More Practical Scenarios

no code implementations12 Mar 2024 Guoshan Liu, Yang Jiao, Jingjing Chen, Bin Zhu, Yu-Gang Jiang

These two datasets are used to evaluate the transferability of approaches from the well-curated food image domain to the everyday-life food image domain.

Food Recognition

Lumen: Unleashing Versatile Vision-Centric Capabilities of Large Multimodal Models

1 code implementation12 Mar 2024 Yang Jiao, Shaoxiang Chen, Zequn Jie, Jingjing Chen, Lin Ma, Yu-Gang Jiang

To address this issue, we propose a novel LMM architecture named Lumen, a Large multimodal model with versatile vision-centric capability enhancement.

Concept Alignment Instruction Following +2

Federated Learning While Providing Model as a Service: Joint Training and Inference Optimization

no code implementations20 Dec 2023 Pengchao Han, Shiqiang Wang, Yang Jiao, Jianwei Huang

Toward the challenges, we propose an online problem approximation to reduce the problem complexity and optimize the resources to balance the needs of model training and inference.

Federated Learning Inference Optimization

Provably Convergent Federated Trilevel Learning

no code implementations19 Dec 2023 Yang Jiao, Kai Yang, Tiancheng Wu, Chengtao Jian, Jianwei Huang

To address the aforementioned challenges, this paper proposes an asynchronous federated trilevel optimization method to solve TLO problems.

Decision Making Domain Adaptation +2

Bandit Learning to Rank with Position-Based Click Models: Personalized and Equal Treatments

no code implementations8 Nov 2023 Tianchen Zhou, Jia Liu, Yang Jiao, Chaosheng Dong, Yetian Chen, Yan Gao, Yi Sun

Online learning to rank (ONL2R) is a foundational problem for recommender systems and has received increasing attention in recent years.

Learning-To-Rank Position +1

Federated Distributionally Robust Optimization with Non-Convex Objectives: Algorithm and Analysis

no code implementations25 Jul 2023 Yang Jiao, Kai Yang, Dongjin Song

Distributionally Robust Optimization (DRO), which aims to find an optimal decision that minimizes the worst case cost over the ambiguity set of probability distribution, has been widely applied in diverse applications, e. g., network behavior analysis, risk management, etc.

Management

NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario

2 code implementations24 May 2023 Tianwen Qian, Jingjing Chen, Linhai Zhuo, Yang Jiao, Yu-Gang Jiang

We introduce a novel visual question answering (VQA) task in the context of autonomous driving, aiming to answer natural language questions based on street-view clues.

Autonomous Driving Question Answering +1

Learning Attribute and Class-Specific Representation Duet for Fine-Grained Fashion Analysis

no code implementations CVPR 2023 Yang Jiao, Yan Gao, Jingjing Meng, Jin Shang, Yi Sun

Fashion representation learning involves the analysis and understanding of various visual elements at different granularities and the interactions among them.

Attribute Inductive Bias +2

Stock Market Prediction via Deep Learning Techniques: A Survey

no code implementations24 Dec 2022 Jinan Zou, Qingying Zhao, Yang Jiao, Haiyao Cao, Yanxi Liu, Qingsen Yan, Ehsan Abbasnejad, Lingqiao Liu, Javen Qinfeng Shi

Existing surveys on stock market prediction often focus on traditional machine learning methods instead of deep learning methods.

Stock Market Prediction

Asynchronous Distributed Bilevel Optimization

1 code implementation20 Dec 2022 Yang Jiao, Kai Yang, Tiancheng Wu, Dongjin Song, Chengtao Jian

Bilevel optimization plays an essential role in many machine learning tasks, ranging from hyperparameter optimization to meta-learning.

Bilevel Optimization Hyperparameter Optimization +1

CPMLHO:Hyperparameter Tuning via Cutting Plane and Mixed-Level Optimization

no code implementations11 Dec 2022 Shuo Yang, Yang Jiao, Shaoyu Dou, Mana Zheng, Chen Zhu

The bilevel optimization is used to automatically update the hyperparameter, and the gradient of the hyperparameter is the approximate gradient based on the best response function.

Bilevel Optimization Hyperparameter Optimization

Distributed Distributionally Robust Optimization with Non-Convex Objectives

no code implementations14 Oct 2022 Yang Jiao, Kai Yang, Dongjin Song

Distributionally Robust Optimization (DRO), which aims to find an optimal decision that minimizes the worst case cost over the ambiguity set of probability distribution, has been widely applied in diverse applications, e. g., network behavior analysis, risk management, etc.

Management

MSMDFusion: Fusing LiDAR and Camera at Multiple Scales with Multi-Depth Seeds for 3D Object Detection

1 code implementation CVPR 2023 Yang Jiao, Zequn Jie, Shaoxiang Chen, Jingjing Chen, Lin Ma, Yu-Gang Jiang

Recent approaches aim at exploring the semantic densities of camera features through lifting points in 2D camera images (referred to as seeds) into 3D space, and then incorporate 2D semantics via cross-modal interaction or fusion techniques.

3D Object Detection Autonomous Driving +1

Task-aware Similarity Learning for Event-triggered Time Series

no code implementations17 Jul 2022 Shaoyu Dou, Kai Yang, Yang Jiao, Chengbo Qiu, Kui Ren

The proposed framework aspires to offer a stepping stone that gives rise to a systematic approach to model and learn similarities among a multitude of event-triggered time series.

Anomaly Detection Time Series +1

Suspected Object Matters: Rethinking Model's Prediction for One-stage Visual Grounding

no code implementations10 Mar 2022 Yang Jiao, Zequn Jie, Jingjing Chen, Lin Ma, Yu-Gang Jiang

Recently, one-stage visual grounders attract high attention due to their comparable accuracy but significantly higher efficiency than two-stage grounders.

Object Visual Grounding

MORE: Multi-Order RElation Mining for Dense Captioning in 3D Scenes

1 code implementation10 Mar 2022 Yang Jiao, Shaoxiang Chen, Zequn Jie, Jingjing Chen, Lin Ma, Yu-Gang Jiang

3D dense captioning is a recently-proposed novel task, where point clouds contain more geometric information than the 2D counterpart.

3D dense captioning Dense Captioning +3

PATO: Producibility-Aware Topology Optimization using Deep Learning for Metal Additive Manufacturing

no code implementations8 Dec 2021 Naresh S. Iyer, Amir M. Mirzendehdel, Sathyanarayanan Raghavan, Yang Jiao, Erva Ulu, Morad Behandish, Saigopal Nelaturi, Dean M. Robinson

In this paper, we propose PATO-a producibility-aware topology optimization (TO) framework to help efficiently explore the design space of components fabricated using metal additive manufacturing (AM), while ensuring manufacturability with respect to cracking.

Two-stage Visual Cues Enhancement Network for Referring Image Segmentation

1 code implementation9 Oct 2021 Yang Jiao, Zequn Jie, Weixin Luo, Jingjing Chen, Yu-Gang Jiang, Xiaolin Wei, Lin Ma

Referring Image Segmentation (RIS) aims at segmenting the target object from an image referred by one given natural language expression.

Image Segmentation Retrieval +2

Data-Driven Learning of 3-Point Correlation Functions as Microstructure Representations

1 code implementation6 Sep 2021 Sheng Cheng, Yang Jiao, Yi Ren

This paper considers the open challenge of identifying complete, concise, and explainable quantitative microstructure representations for disordered heterogeneous material systems.

Bayesian Optimization

Optical Flow Estimation via Motion Feature Recovery

no code implementations16 Jan 2021 Yang Jiao, Guangming Shi, Trac D. Tran

In this paper, we discover that the lost information is related to a large quantity of motion features (more than 40%) computed from the popular discriminative cost-volume feature would completely vanish due to invalid sampling, leading to the low efficiency of optical flow learning.

Optical Flow Estimation

Topological Transformations in Pentagonal 2D Materials Induced by Stone-Wales Defects

no code implementations22 Dec 2020 Yu Zheng, Duyu Chen, Lei Liu, Houlong Zhuang, Yang Jiao

We discover two distinct topological pathways through which the pentagonal Cairo tiling (P5), a structural model for single-layer $AB_2$ pyrite materials, respectively transforms into a crystalline rhombus-hexagon (C46) tiling and random rhombus-pentagon-hexagon (R456) tilings, by continuously introducing the Stone-Wales (SW) topological defects.

Soft Condensed Matter Disordered Systems and Neural Networks Materials Science

EffiScene: Efficient Per-Pixel Rigidity Inference for Unsupervised Joint Learning of Optical Flow, Depth, Camera Pose and Motion Segmentation

no code implementations CVPR 2021 Yang Jiao, Trac D. Tran, Guangming Shi

This paper addresses the challenging unsupervised scene flow estimation problem by jointly learning four low-level vision sub-tasks: optical flow $\textbf{F}$, stereo-depth $\textbf{D}$, camera pose $\textbf{P}$ and motion segmentation $\textbf{S}$.

Depth Estimation Motion Segmentation +3

2D+3D Facial Expression Recognition via Discriminative Dynamic Range Enhancement and Multi-Scale Learning

no code implementations16 Nov 2020 Yang Jiao, Yi Niu, Trac D. Tran, Guangming Shi

In 2D+3D facial expression recognition (FER), existing methods generate multi-view geometry maps to enhance the depth feature representation.

3D Facial Expression Recognition Facial Expression Recognition

SeNsER: Learning Cross-Building Sensor Metadata Tagger

1 code implementation Findings of the Association for Computational Linguistics 2020 Yang Jiao, Jiacheng Li, Jiaman Wu, Dezhi Hong, Rajesh Gupta, Jingbo Shang

Sensor metadata tagging, akin to the named entity recognition task, provides key contextual information (e. g., measurement type and location) about sensors for running smart building applications.

named-entity-recognition Named Entity Recognition +1

BERT for Joint Multichannel Speech Dereverberation with Spatial-aware Tasks

no code implementations21 Oct 2020 Yang Jiao

The proposed method addresses involved tasks as a sequence to sequence mapping problem, which is general enough for a variety of front-end speech enhancement tasks.

Speech Dereverberation Speech Separation

TimeAutoML: Autonomous Representation Learning for Multivariate Irregularly Sampled Time Series

no code implementations4 Oct 2020 Yang Jiao, Kai Yang, Shaoyu Dou, Pan Luo, Sijia Liu, Dongjin Song

To this end, we propose an autonomous representation learning approach for multivariate time series (TimeAutoML) with irregular sampling rates and variable lengths.

Anomaly Detection Clustering +4

Multi-Object Portion Tracking in 4D Fluorescence Microscopy Imagery with Deep Feature Maps

no code implementations26 Nov 2019 Yang Jiao, Mo Weng, Mei Yang

In this paper, we first define the problem of multi-object portion tracking to model the protein object tracking process.

Multi-Object Tracking Object

Modeling cell migration regulated by cell-ECM micromechanical coupling

no code implementations16 May 2019 Yu Zheng, Hanqing Nan, Qihui Fan, Xiaochen Wang, LiYu Liu, Ruchuan Liu, Fangfu Ye, Bo Sun, Yang Jiao

During migration, individual cells can generate active pulling forces via actin filament contraction, which are transmitted to the ECM fibers through focal adhesion complexes, remodel the ECM, and eventually propagate to and can be sensed by other cells in the system.

Improving Direct Physical Properties Prediction of Heterogeneous Materials from Imaging Data via Convolutional Neural Network and a Morphology-Aware Generative Model

1 code implementation7 Dec 2017 Ruijin Cang, Hechao Li, Hope Yao, Yang Jiao, Yi Ren

Direct prediction of material properties from microstructures through statistical models has shown to be a potential approach to accelerating computational material design with large design spaces.

Computational Physics Materials Science

Microstructure Representation and Reconstruction of Heterogeneous Materials via Deep Belief Network for Computational Material Design

1 code implementation22 Dec 2016 Ruijin Cang, Yaopengxiao Xu, Shaohua Chen, Yongming Liu, Yang Jiao, Max Yi Ren

Integrated Computational Materials Engineering (ICME) aims to accelerate optimal design of complex material systems by integrating material science and design automation.

Dimensionality Reduction

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