Search Results for author: Hao Sun

Found 155 papers, 64 papers with code

Enhancing Self-Attention with Knowledge-Assisted Attention Maps

no code implementations NAACL 2022 Jiangang Bai, Yujing Wang, Hong Sun, Ruonan Wu, Tianmeng Yang, Pengfei Tang, Defu Cao, Mingliang Zhang1, Yunhai Tong, Yaming Yang, Jing Bai, Ruofei Zhang, Hao Sun, Wei Shen

Large-scale pre-trained language models have attracted extensive attentions in the research community and shown promising results on various tasks of natural language processing.

Multi-Task Learning Natural Language Understanding

Retrieved In-Context Principles from Previous Mistakes

no code implementations8 Jul 2024 Hao Sun, Yong Jiang, Bo wang, Yingyan Hou, Yan Zhang, Pengjun Xie, Fei Huang

In RICP, the teacher model analyzes mistakes from the student model to generate reasons and insights for preventing similar mistakes.

In-Context Learning

Discovering symbolic expressions with parallelized tree search

1 code implementation5 Jul 2024 Kai Ruan, Ze-Feng Gao, Yike Guo, Hao Sun, Ji-Rong Wen, Yang Liu

Symbolic regression plays a crucial role in modern scientific research thanks to its capability of discovering concise and interpretable mathematical expressions from data.

Equation Discovery regression

Unraveling the Mechanics of Learning-Based Demonstration Selection for In-Context Learning

no code implementations14 Jun 2024 Hui Liu, Wenya Wang, Hao Sun, Chris Xing Tian, Chenqi Kong, Xin Dong, Haoliang Li

Large Language Models (LLMs) have demonstrated impressive in-context learning (ICL) capabilities from few-shot demonstration exemplars.

In-Context Learning

Robust Latent Representation Tuning for Image-text Classification

no code implementations10 Jun 2024 Hao Sun, Yu Song

Specifically, our approach introduces a modality latent translation module to maximize the correlation between modalities, resulting in a robust representation.

Image-text Classification text-classification +1

Assessing the Performance of Chinese Open Source Large Language Models in Information Extraction Tasks

no code implementations4 Jun 2024 Yida Cai, Hao Sun, Hsiu-Yuan Huang, Yunfang Wu

Through meticulous experimentation and analysis, we aim to provide insights into the strengths, limitations, and potential enhancements of existing Chinese open-source LLMs in the domain of Information Extraction within the context of NLP.

Language Modelling named-entity-recognition +2

Unsupervised Distractor Generation via Large Language Model Distilling and Counterfactual Contrastive Decoding

no code implementations3 Jun 2024 Fanyi Qu, Hao Sun, Yunfang Wu

Our proposed unsupervised DG method offers a cost-effective framework for practical reading comprehension applications, without the need of laborious distractor annotation and costly large-size models

counterfactual Distractor Generation +3

Promoting AI Equity in Science: Generalized Domain Prompt Learning for Accessible VLM Research

1 code implementation14 May 2024 Qinglong Cao, Yuntian Chen, Lu Lu, Hao Sun, Zhenzhong Zeng, Xiaokang Yang, Dongxiao Zhang

Our framework paves the way for sustainable and inclusive VLM research, transcending the barriers between academia and industry.

Domain Adaptation

Vision-based Discovery of Nonlinear Dynamics for 3D Moving Target

no code implementations27 Apr 2024 Zitong Zhang, Yang Liu, Hao Sun

To this end, we propose a vision-based approach to automatically uncover governing equations of nonlinear dynamics for 3D moving targets via raw videos recorded by a set of cameras.

EEG-Deformer: A Dense Convolutional Transformer for Brain-computer Interfaces

1 code implementation25 Apr 2024 Yi Ding, Yong Li, Hao Sun, Rui Liu, Chengxuan Tong, Cuntai Guan

Effectively learning the temporal dynamics in electroencephalogram (EEG) signals is challenging yet essential for decoding brain activities using brain-computer interfaces (BCIs).

EEG

OneActor: Consistent Character Generation via Cluster-Conditioned Guidance

no code implementations16 Apr 2024 Jiahao Wang, Caixia Yan, Haonan Lin, Weizhan Zhang, Mengmeng Wang, Tieliang Gong, Guang Dai, Hao Sun

To mitigate the overfitting challenge shared by one-shot tuning pipelines, we augment the tuning with auxiliary samples and devise two inference strategies: semantic interpolation and cluster guidance.

Consistent Character Generation Denoising +1

Energy-modified Leverage Sampling for Radio Map Construction via Matrix Completion

no code implementations12 Apr 2024 Hao Sun, Junting Chen

This paper explores an energy-modified leverage sampling strategy for matrix completion in radio map construction.

Matrix Completion

Reasoning-Enhanced Object-Centric Learning for Videos

no code implementations22 Mar 2024 Jian Li, Pu Ren, Yang Liu, Hao Sun

Object-centric learning aims to break down complex visual scenes into more manageable object representations, enhancing the understanding and reasoning abilities of machine learning systems toward the physical world.

Object Object Tracking

Learning Novel View Synthesis from Heterogeneous Low-light Captures

no code implementations20 Mar 2024 Quan Zheng, Hao Sun, Huiyao Xu, Fanjiang Xu

Unfortunately, synthesizing novel views remains to be a challenge for input views with heterogeneous brightness level captured under low-light condition.

Novel View Synthesis

Supervised Fine-Tuning as Inverse Reinforcement Learning

no code implementations18 Mar 2024 Hao Sun

The prevailing approach to aligning Large Language Models (LLMs) typically relies on human or AI feedback and assumes access to specific types of preference datasets.

Imitation Learning reinforcement-learning

Rich Semantic Knowledge Enhanced Large Language Models for Few-shot Chinese Spell Checking

no code implementations13 Mar 2024 Ming Dong, Yujing Chen, Miao Zhang, Hao Sun, Tingting He

We found that by introducing a small number of specific Chinese rich semantic structures, LLMs achieve better performance than the BERT-based model on few-shot CSC task.

Chinese Spell Checking In-Context Learning +2

Boosting Disfluency Detection with Large Language Model as Disfluency Generator

no code implementations13 Mar 2024 Zhenrong Cheng, Jiayan Guo, Hao Sun, Yan Zhang

In this study, we propose a lightweight data augmentation approach for disfluency detection, utilizing the superior generative and semantic understanding capabilities of large language model (LLM) to generate disfluent sentences as augmentation data.

Data Augmentation Language Modelling +1

Physics-Informed Machine Learning for Seismic Response Prediction OF Nonlinear Steel Moment Resisting Frame Structures

no code implementations28 Feb 2024 R. Bailey Bond, Pu Ren, Jerome F. Hajjar, Hao Sun

There is growing interest in using machine learning (ML) methods for structural metamodeling due to the substantial computational cost of traditional simulations.

Dimensionality Reduction Physics-informed machine learning

Integrated Interpolation and Block-term Tensor Decomposition for Spectrum Map Construction

no code implementations27 Feb 2024 Hao Sun, Junting Chen

This approach leverages an interpolation model with the BTD structure to exploit the spatial correlation of power spectrum maps.

Tensor Decomposition

ShieldLM: Empowering LLMs as Aligned, Customizable and Explainable Safety Detectors

1 code implementation26 Feb 2024 Zhexin Zhang, Yida Lu, Jingyuan Ma, Di Zhang, Rui Li, Pei Ke, Hao Sun, Lei Sha, Zhifang Sui, Hongning Wang, Minlie Huang

The safety of Large Language Models (LLMs) has gained increasing attention in recent years, but there still lacks a comprehensive approach for detecting safety issues within LLMs' responses in an aligned, customizable and explainable manner.

$Se^2$: Sequential Example Selection for In-Context Learning

1 code implementation21 Feb 2024 Haoyu Liu, Jianfeng Liu, Shaohan Huang, Yuefeng Zhan, Hao Sun, Weiwei Deng, Furu Wei, Qi Zhang

The remarkable capability of large language models (LLMs) for in-context learning (ICL) needs to be activated by demonstration examples.

Diversity In-Context Learning

PhaseEvo: Towards Unified In-Context Prompt Optimization for Large Language Models

no code implementations17 Feb 2024 Wendi Cui, Jiaxin Zhang, Zhuohang Li, Hao Sun, Damien Lopez, Kamalika Das, Bradley Malin, Sricharan Kumar

Crafting an ideal prompt for Large Language Models (LLMs) is a challenging task that demands significant resources and expert human input.

Computational Efficiency In-Context Learning

Retrieval-Augmented Thought Process as Sequential Decision Making

no code implementations12 Feb 2024 Thomas Pouplin, Hao Sun, Samuel Holt, Mihaela van der Schaar

Large Language Models (LLMs) have demonstrated their strong ability to assist people and show "sparks of intelligence".

Decision Making Question Answering +1

Dense Reward for Free in Reinforcement Learning from Human Feedback

1 code implementation1 Feb 2024 Alex J. Chan, Hao Sun, Samuel Holt, Mihaela van der Schaar

Reinforcement Learning from Human Feedback (RLHF) has been credited as the key advance that has allowed Large Language Models (LLMs) to effectively follow instructions and produce useful assistance.

reinforcement-learning

Memory-Inspired Temporal Prompt Interaction for Text-Image Classification

no code implementations26 Jan 2024 Xinyao Yu, Hao Sun, Ziwei Niu, Rui Qin, Zhenjia Bai, Yen-Wei Chen, Lanfen Lin

We utilize temporal prompts on intermediate layers to imitate the acquiring stage, leverage similarity-based prompt interaction to imitate memory consolidation, and employ prompt generation strategy to imitate memory activation.

Classification Image Classification

TR-DETR: Task-Reciprocal Transformer for Joint Moment Retrieval and Highlight Detection

1 code implementation4 Jan 2024 Hao Sun, Mingyao Zhou, Wenjing Chen, Wei Xie

Finally, a task cooperation module is constructed to refine the retrieval pipeline and the highlight score prediction process by utilizing the reciprocity between MR and HD.

Highlight Detection Moment Retrieval +2

LiDAR-Net: A Real-scanned 3D Point Cloud Dataset for Indoor Scenes

no code implementations CVPR 2024 Yanwen Guo, Yuanqi Li, Dayong Ren, Xiaohong Zhang, Jiawei Li, Liang Pu, Changfeng Ma, Xiaoyu Zhan, Jie Guo, Mingqiang Wei, Yan Zhang, Piaopiao Yu, Shuangyu Yang, Donghao Ji, Huisheng Ye, Hao Sun, Yansong Liu, Yinuo Chen, Jiaqi Zhu, Hongyu Liu

In this paper we present LiDAR-Net a new real-scanned indoor point cloud dataset containing nearly 3. 6 billion precisely point-level annotated points covering an expansive area of 30000m^2.

Towards Verifiable Text Generation with Evolving Memory and Self-Reflection

no code implementations14 Dec 2023 Hao Sun, Hengyi Cai, Bo wang, Yingyan Hou, Xiaochi Wei, Shuaiqiang Wang, Yan Zhang, Dawei Yin

Despite the remarkable ability of large language models (LLMs) in language comprehension and generation, they often suffer from producing factually incorrect information, also known as hallucination.

Hallucination Retrieval +1

Unveiling the Implicit Toxicity in Large Language Models

1 code implementation29 Nov 2023 Jiaxin Wen, Pei Ke, Hao Sun, Zhexin Zhang, Chengfei Li, Jinfeng Bai, Minlie Huang

While recent studies primarily focus on probing toxic outputs that can be easily detected with existing toxicity classifiers, we show that LLMs can generate diverse implicit toxic outputs that are exceptionally difficult to detect via simply zero-shot prompting.

Language Modelling Reinforcement Learning (RL)

Robust Domain Misinformation Detection via Multi-modal Feature Alignment

1 code implementation24 Nov 2023 Hui Liu, Wenya Wang, Hao Sun, Anderson Rocha, Haoliang Li

We also propose a framework that simultaneously considers application scenarios of domain generalization (in which the target domain data is unavailable) and domain adaptation (in which unlabeled target domain data is available).

Domain Generalization Misinformation

When is Off-Policy Evaluation Useful? A Data-Centric Perspective

no code implementations23 Nov 2023 Hao Sun, Alex J. Chan, Nabeel Seedat, Alihan Hüyük, Mihaela van der Schaar

On the one hand, it brings opportunities for safe policy improvement under high-stakes scenarios like clinical guidelines.

Off-policy evaluation

AI-accelerated Discovery of Altermagnetic Materials

1 code implementation8 Nov 2023 Ze-Feng Gao, Shuai Qu, Bocheng Zeng, Yang Liu, Ji-Rong Wen, Hao Sun, Peng-Jie Guo, Zhong-Yi Lu

Altermagnetism, a new magnetic phase, has been theoretically proposed and experimentally verified to be distinct from ferromagnetism and antiferromagnetism.

Graph Neural Network

GOPlan: Goal-conditioned Offline Reinforcement Learning by Planning with Learned Models

no code implementations30 Oct 2023 Mianchu Wang, Rui Yang, Xi Chen, Hao Sun, Meng Fang, Giovanni Montana

In this work, we propose Goal-conditioned Offline Planning (GOPlan), a novel model-based framework that contains two key phases: (1) pretraining a prior policy capable of capturing multi-modal action distribution within the multi-goal dataset; (2) employing the reanalysis method with planning to generate imagined trajectories for funetuning policies.

Generative Adversarial Network reinforcement-learning

Character-level Chinese Backpack Language Models

1 code implementation19 Oct 2023 Hao Sun, John Hewitt

The Backpack is a Transformer alternative shown to improve interpretability in English language modeling by decomposing predictions into a weighted sum of token sense components.

Language Modelling

Model-enhanced Vector Index

1 code implementation NeurIPS 2023 Hailin Zhang, Yujing Wang, Qi Chen, Ruiheng Chang, Ting Zhang, Ziming Miao, Yingyan Hou, Yang Ding, Xupeng Miao, Haonan Wang, Bochen Pang, Yuefeng Zhan, Hao Sun, Weiwei Deng, Qi Zhang, Fan Yang, Xing Xie, Mao Yang, Bin Cui

We empirically show that our model achieves better performance on the commonly used academic benchmarks MSMARCO Passage and Natural Questions, with comparable serving latency to dense retrieval solutions.

Natural Questions Quantization +1

FedLALR: Client-Specific Adaptive Learning Rates Achieve Linear Speedup for Non-IID Data

no code implementations18 Sep 2023 Hao Sun, Li Shen, Shixiang Chen, Jingwei Sun, Jing Li, Guangzhong Sun, DaCheng Tao

Federated learning is an emerging distributed machine learning method, enables a large number of clients to train a model without exchanging their local data.

Federated Learning Scheduling

Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL

2 code implementations13 Sep 2023 Hao Sun, Alihan Hüyük, Mihaela van der Schaar

We identify a previously overlooked objective of query dependency in such optimization and elucidate two ensuing challenges that impede the successful and economical design of prompt optimization techniques.

Arithmetic Reasoning Navigate +2

Efficient Federated Learning via Local Adaptive Amended Optimizer with Linear Speedup

no code implementations30 Jul 2023 Yan Sun, Li Shen, Hao Sun, Liang Ding, DaCheng Tao

Adaptive optimization has achieved notable success for distributed learning while extending adaptive optimizer to federated Learning (FL) suffers from severe inefficiency, including (i) rugged convergence due to inaccurate gradient estimation in global adaptive optimizer; (ii) client drifts exacerbated by local over-fitting with the local adaptive optimizer.

Federated Learning

Constraint-aware and Ranking-distilled Token Pruning for Efficient Transformer Inference

1 code implementation26 Jun 2023 Junyan Li, Li Lyna Zhang, Jiahang Xu, Yujing Wang, Shaoguang Yan, Yunqing Xia, Yuqing Yang, Ting Cao, Hao Sun, Weiwei Deng, Qi Zhang, Mao Yang

Deploying pre-trained transformer models like BERT on downstream tasks in resource-constrained scenarios is challenging due to their high inference cost, which grows rapidly with input sequence length.

Model Compression

TLNets: Transformation Learning Networks for long-range time-series prediction

1 code implementation25 May 2023 Wei Wang, Yang Liu, Hao Sun

Note that the FT and SVD blocks are capable of learning global information, while the Conv blocks focus on learning local information.

Time Series Time Series Forecasting +1

Allies: Prompting Large Language Model with Beam Search

1 code implementation24 May 2023 Hao Sun, Xiao Liu, Yeyun Gong, Yan Zhang, Daxin Jiang, Linjun Yang, Nan Duan

With the advance of large language models (LLMs), the research field of LLM applications becomes more and more popular and the idea of constructing pipelines to accomplish complex tasks by stacking LLM API calls come true.

Language Modelling Large Language Model +3

RSRM: Reinforcement Symbolic Regression Machine

no code implementations24 May 2023 Yilong Xu, Yang Liu, Hao Sun

Biding of these modules yields the state-of-the-art performance of RSRM in symbolic regression as demonstrated by multiple sets of benchmark examples.

Math Q-Learning +2

Mask to reconstruct: Cooperative Semantics Completion for Video-text Retrieval

no code implementations13 May 2023 Han Fang, Zhifei Yang, Xianghao Zang, Chao Ban, Hao Sun

Specifically, after applying attention-based video masking to generate high-informed and low-informed masks, we propose Informed Semantics Completion to recover masked semantics information.

Text Retrieval Video-Text Retrieval

Physics-informed neural network for seismic wave inversion in layered semi-infinite domain

no code implementations9 May 2023 Pu Ren, Chengping Rao, Hao Sun, Yang Liu

In this paper, we present a PINN framework for seismic wave inversion in layered (1D) semi-infinite domain.

Seismic Inversion

Attention-guided Multi-step Fusion: A Hierarchical Fusion Network for Multimodal Recommendation

no code implementations24 Apr 2023 Yan Zhou, Jie Guo, Hao Sun, Bin Song, Fei Richard Yu

The main idea of multimodal recommendation is the rational utilization of the item's multimodal information to improve the recommendation performance.

Contrastive Learning Multimodal Recommendation

Safety Assessment of Chinese Large Language Models

2 code implementations20 Apr 2023 Hao Sun, Zhexin Zhang, Jiawen Deng, Jiale Cheng, Minlie Huang

To further promote the safe deployment of LLMs, we develop a Chinese LLM safety assessment benchmark.

Latent Semantic Diffusion-based Channel Adaptive De-Noising SemCom for Future 6G Systems

no code implementations19 Apr 2023 Bingxuan Xu, Rui Meng, Yue Chen, Xiaodong Xu, Chen Dong, Hao Sun

Upon the designed DNSC architecture, we further combine adversarial learning, variational autoencoder, and diffusion model to propose the Latent Diffusion DNSC (Latent-Diff DNSC) scheme to realize intelligent online de-noising.

Semantic Communication SSIM

IRGen: Generative Modeling for Image Retrieval

1 code implementation17 Mar 2023 Yidan Zhang, Ting Zhang, Dong Chen, Yujing Wang, Qi Chen, Xing Xie, Hao Sun, Weiwei Deng, Qi Zhang, Fan Yang, Mao Yang, Qingmin Liao, Baining Guo

While generative modeling has been ubiquitous in natural language processing and computer vision, its application to image retrieval remains unexplored.

Image Retrieval Retrieval

UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation

1 code implementation15 Mar 2023 Daixuan Cheng, Shaohan Huang, Junyu Bi, Yuefeng Zhan, Jianfeng Liu, Yujing Wang, Hao Sun, Furu Wei, Denvy Deng, Qi Zhang

Large Language Models (LLMs) are popular for their impressive abilities, but the need for model-specific fine-tuning or task-specific prompt engineering can hinder their generalization.

Hallucination Prompt Engineering +1

AdaSAM: Boosting Sharpness-Aware Minimization with Adaptive Learning Rate and Momentum for Training Deep Neural Networks

no code implementations1 Mar 2023 Hao Sun, Li Shen, Qihuang Zhong, Liang Ding, Shixiang Chen, Jingwei Sun, Jing Li, Guangzhong Sun, DaCheng Tao

Integrating SAM with adaptive learning rate and momentum acceleration, dubbed AdaSAM, has already been explored empirically to train large-scale deep neural networks without theoretical guarantee due to the triple difficulties in analyzing the coupled perturbation step, adaptive learning rate and momentum step.

Membership Inference Attacks against Synthetic Data through Overfitting Detection

1 code implementation24 Feb 2023 Boris van Breugel, Hao Sun, Zhaozhi Qian, Mihaela van der Schaar

In this work we argue for a realistic MIA setting that assumes the attacker has some knowledge of the underlying data distribution.

Neural Laplace Control for Continuous-time Delayed Systems

2 code implementations24 Feb 2023 Samuel Holt, Alihan Hüyük, Zhaozhi Qian, Hao Sun, Mihaela van der Schaar

Many real-world offline reinforcement learning (RL) problems involve continuous-time environments with delays.

Model Predictive Control Offline RL +1

Towards Safer Generative Language Models: A Survey on Safety Risks, Evaluations, and Improvements

no code implementations18 Feb 2023 Jiawen Deng, Jiale Cheng, Hao Sun, Zhexin Zhang, Minlie Huang

This survey presents a framework for safety research pertaining to large models, delineating the landscape of safety risks as well as safety evaluation and improvement methods.

Adversarial Attack Ethics

Laplacian ICP for Progressive Registration of 3D Human Head Meshes

no code implementations4 Feb 2023 Nick Pears, Hang Dai, Will Smith, Hao Sun

We present a progressive 3D registration framework that is a highly-efficient variant of classical non-rigid Iterative Closest Points (N-ICP).

Accurate Gaze Estimation using an Active-gaze Morphable Model

no code implementations30 Jan 2023 Hao Sun, Nick Pears

Rather than regressing gaze direction directly from images, we show that adding a 3D shape model can: i) improve gaze estimation accuracy, ii) perform well with lower resolution inputs and iii) provide a richer understanding of the eye-region and its constituent gaze system.

Gaze Estimation

PAL: Persona-Augmented Emotional Support Conversation Generation

1 code implementation19 Dec 2022 Jiale Cheng, Sahand Sabour, Hao Sun, Zhuang Chen, Minlie Huang

As previous studies have demonstrated that seekers' persona is an important factor for effective support, we investigate whether there are benefits to modeling such information in dialogue models for support.

LEAD: Liberal Feature-based Distillation for Dense Retrieval

1 code implementation10 Dec 2022 Hao Sun, Xiao Liu, Yeyun Gong, Anlei Dong, Jingwen Lu, Yan Zhang, Linjun Yang, Rangan Majumder, Nan Duan

Knowledge distillation is often used to transfer knowledge from a strong teacher model to a relatively weak student model.

Document Ranking Knowledge Distillation +2

An Unsupervised Machine Learning Approach for Ground-Motion Spectra Clustering and Selection

no code implementations6 Dec 2022 R. Bailey Bond, Pu Ren, Jerome F. Hajjar, Hao Sun

Clustering analysis of sequence data continues to address many applications in engineering design, aided with the rapid growth of machine learning in applied science.

Clustering

Constructing Highly Inductive Contexts for Dialogue Safety through Controllable Reverse Generation

1 code implementation4 Dec 2022 Zhexin Zhang, Jiale Cheng, Hao Sun, Jiawen Deng, Fei Mi, Yasheng Wang, Lifeng Shang, Minlie Huang

In order to detect such toxic generations, existing methods rely on templates, real-world data extraction, crowdsourcing workers, or automatic generation to construct adversarial contexts that are likely to induce toxic generations.

Response Generation

Stare at What You See: Masked Image Modeling without Reconstruction

no code implementations CVPR 2023 Hongwei Xue, Peng Gao, Hongyang Li, Yu Qiao, Hao Sun, Houqiang Li, Jiebo Luo

However, unlike the low-level features such as pixel values, we argue the features extracted by powerful teacher models already encode rich semantic correlation across regions in an intact image. This raises one question: is reconstruction necessary in Masked Image Modeling (MIM) with a teacher model?

SeismicNet: Physics-informed neural networks for seismic wave modeling in semi-infinite domain

no code implementations25 Oct 2022 Pu Ren, Chengping Rao, Su Chen, Jian-Xun Wang, Hao Sun, Yang Liu

In this paper, we present a novel physics-informed neural network (PINN) model for seismic wave modeling in semi-infinite domain without the nedd of labeled data.

Computational Efficiency

Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics with Quantified Uncertainty

1 code implementation14 Oct 2022 Luning Sun, Daniel Zhengyu Huang, Hao Sun, Jian-Xun Wang

The equation residuals are used to inform the spline learning in a Bayesian manner, where approximate Bayesian uncertainty calibration techniques are employed to approximate posterior distributions of the trainable parameters.

Equation Discovery

Optimistic Curiosity Exploration and Conservative Exploitation with Linear Reward Shaping

1 code implementation15 Sep 2022 Hao Sun, Lei Han, Rui Yang, Xiaoteng Ma, Jian Guo, Bolei Zhou

We validate our insight on a range of RL tasks and show its improvement over baselines: (1) In offline RL, the conservative exploitation leads to improved performance based on off-the-shelf algorithms; (2) In online continuous control, multiple value functions with different shifting constants can be used to tackle the exploration-exploitation dilemma for better sample efficiency; (3) In discrete control tasks, a negative reward shifting yields an improvement over the curiosity-based exploration method.

Continuous Control Offline RL

A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural Language

4 code implementations12 Sep 2022 Bing Su, Dazhao Du, Zhao Yang, Yujie Zhou, Jiangmeng Li, Anyi Rao, Hao Sun, Zhiwu Lu, Ji-Rong Wen

Although artificial intelligence (AI) has made significant progress in understanding molecules in a wide range of fields, existing models generally acquire the single cognitive ability from the single molecular modality.

Contrastive Learning Cross-Modal Retrieval +4

Pasture Intake Protects Against Commercial Diet-induced Lipopolysaccharide Production Facilitated by Gut Microbiota through Activating Intestinal Alkaline Phosphatase Enzyme in Meat Geese

no code implementations29 Aug 2022 Qasim Ali, Sen Ma, Umar Farooq, Jiakuan Niu, Fen Li, Muhammad Abaidullah, Boshuai Liu, Shaokai La, Defeng Li, Zhichang Wang, Hao Sun, Yalei Cui, Yinghua Shi

In the gut microbiota analysis, meat geese supplemented with pasture demonstrated a significant reduction in microbial richness and diversity compared to IHF meat geese demonstrating antimicrobial, antioxidation, and anti-inflammatory ability of AGF system.

Multimodal foundation models are better simulators of the human brain

1 code implementation17 Aug 2022 Haoyu Lu, Qiongyi Zhou, Nanyi Fei, Zhiwu Lu, Mingyu Ding, Jingyuan Wen, Changde Du, Xin Zhao, Hao Sun, Huiguang He, Ji-Rong Wen

Further, from the perspective of neural encoding (based on our foundation model), we find that both visual and lingual encoders trained multimodally are more brain-like compared with unimodal ones.

Physics-informed Deep Super-resolution for Spatiotemporal Data

1 code implementation2 Aug 2022 Pu Ren, Chengping Rao, Yang Liu, Zihan Ma, Qi Wang, Jian-Xun Wang, Hao Sun

High-fidelity simulation of complex physical systems is exorbitantly expensive and inaccessible across spatiotemporal scales.

Super-Resolution

CubeMLP: An MLP-based Model for Multimodal Sentiment Analysis and Depression Estimation

1 code implementation28 Jul 2022 Hao Sun, Hongyi Wang, Jiaqing Liu, Yen-Wei Chen, Lanfen Lin

Multimodal sentiment analysis and depression estimation are two important research topics that aim to predict human mental states using multimodal data.

Multimodal Sentiment Analysis

Propagation Map Reconstruction via Interpolation Assisted Matrix Completion

no code implementations27 Jul 2022 Hao Sun, Junting Chen

This paper proposes to integrate interpolation with matrix completion to exploit both the spatial correlation and the potential low rank structure of the propagation map.

Management Matrix Completion

A Survey on Collaborative DNN Inference for Edge Intelligence

no code implementations16 Jul 2022 Weiqing Ren, Yuben Qu, Chao Dong, Yuqian Jing, Hao Sun, Qihui Wu, Song Guo

With the vigorous development of artificial intelligence (AI), the intelligent applications based on deep neural network (DNN) change people's lifestyles and the production efficiency.

A Neural Corpus Indexer for Document Retrieval

1 code implementation6 Jun 2022 Yujing Wang, Yingyan Hou, Haonan Wang, Ziming Miao, Shibin Wu, Hao Sun, Qi Chen, Yuqing Xia, Chengmin Chi, Guoshuai Zhao, Zheng Liu, Xing Xie, Hao Allen Sun, Weiwei Deng, Qi Zhang, Mao Yang

To this end, we propose Neural Corpus Indexer (NCI), a sequence-to-sequence network that generates relevant document identifiers directly for a designated query.

Decoder Retrieval +1

Symbolic Physics Learner: Discovering governing equations via Monte Carlo tree search

no code implementations26 May 2022 Fangzheng Sun, Yang Liu, Jian-Xun Wang, Hao Sun

The key concept is to interpret mathematical operations and system state variables by computational rules and symbols, establish symbolic reasoning of mathematical formulas via expression trees, and employ a Monte Carlo tree search (MCTS) agent to explore optimal expression trees based on measurement data.

Multi-resolution partial differential equations preserved learning framework for spatiotemporal dynamics

1 code implementation9 May 2022 Xin-Yang Liu, Min Zhu, Lu Lu, Hao Sun, Jian-Xun Wang

Traditional data-driven deep learning models often struggle with high training costs, error accumulation, and poor generalizability in complex physical processes.

Distilling Governing Laws and Source Input for Dynamical Systems from Videos

1 code implementation3 May 2022 Lele Luan, Yang Liu, Hao Sun

Distilling interpretable physical laws from videos has led to expanded interest in the computer vision community recently thanks to the advances in deep learning, but still remains a great challenge.

regression

HousE: Knowledge Graph Embedding with Householder Parameterization

1 code implementation16 Feb 2022 Rui Li, Jianan Zhao, Chaozhuo Li, Di He, Yiqi Wang, Yuming Liu, Hao Sun, Senzhang Wang, Weiwei Deng, Yanming Shen, Xing Xie, Qi Zhang

The effectiveness of knowledge graph embedding (KGE) largely depends on the ability to model intrinsic relation patterns and mapping properties.

Knowledge Graph Embedding Relation +1

Rethinking Goal-conditioned Supervised Learning and Its Connection to Offline RL

1 code implementation ICLR 2022 Rui Yang, Yiming Lu, Wenzhe Li, Hao Sun, Meng Fang, Yali Du, Xiu Li, Lei Han, Chongjie Zhang

In this paper, we revisit the theoretical property of GCSL -- optimizing a lower bound of the goal reaching objective, and extend GCSL as a novel offline goal-conditioned RL algorithm.

Offline RL Reinforcement Learning (RL) +1

Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning

no code implementations ICLR 2022 Chengping Rao, Pu Ren, Yang Liu, Hao Sun

There have been growing interests in leveraging experimental measurements to discover the underlying partial differential equations (PDEs) that govern complex physical phenomena.

COLD: A Benchmark for Chinese Offensive Language Detection

1 code implementation16 Jan 2022 Jiawen Deng, Jingyan Zhou, Hao Sun, Chujie Zheng, Fei Mi, Helen Meng, Minlie Huang

To this end, we propose a benchmark --COLD for Chinese offensive language analysis, including a Chinese Offensive Language Dataset --COLDATASET and a baseline detector --COLDETECTOR which is trained on the dataset.

Progressively Optimized Bi-Granular Document Representation for Scalable Embedding Based Retrieval

2 code implementations14 Jan 2022 Shitao Xiao, Zheng Liu, Weihao Han, Jianjin Zhang, Yingxia Shao, Defu Lian, Chaozhuo Li, Hao Sun, Denvy Deng, Liangjie Zhang, Qi Zhang, Xing Xie

In this work, we tackle this problem with Bi-Granular Document Representation, where the lightweight sparse embeddings are indexed and standby in memory for coarse-grained candidate search, and the heavyweight dense embeddings are hosted in disk for fine-grained post verification.

Quantization Retrieval

Toward Causal-Aware RL: State-Wise Action-Refined Temporal Difference

1 code implementation2 Jan 2022 Hao Sun, Taiyi Wang

Although it is well known that exploration plays a key role in Reinforcement Learning (RL), prevailing exploration strategies for continuous control tasks in RL are mainly based on naive isotropic Gaussian noise regardless of the causality relationship between action space and the task and consider all dimensions of actions equally important.

Continuous Control Reinforcement Learning (RL)

Towards artificial general intelligence via a multimodal foundation model

1 code implementation27 Oct 2021 Nanyi Fei, Zhiwu Lu, Yizhao Gao, Guoxing Yang, Yuqi Huo, Jingyuan Wen, Haoyu Lu, Ruihua Song, Xin Gao, Tao Xiang, Hao Sun, Ji-Rong Wen

To overcome this limitation and take a solid step towards artificial general intelligence (AGI), we develop a foundation model pre-trained with huge multimodal data, which can be quickly adapted for various downstream cognitive tasks.

Image Classification Reading Comprehension +2

Gophormer: Ego-Graph Transformer for Node Classification

no code implementations25 Oct 2021 Jianan Zhao, Chaozhuo Li, Qianlong Wen, Yiqi Wang, Yuming Liu, Hao Sun, Xing Xie, Yanfang Ye

Existing graph transformer models typically adopt fully-connected attention mechanism on the whole input graph and thus suffer from severe scalability issues and are intractable to train in data insufficient cases.

Classification Data Augmentation +4

On the Safety of Conversational Models: Taxonomy, Dataset, and Benchmark

1 code implementation Findings (ACL) 2022 Hao Sun, Guangxuan Xu, Jiawen Deng, Jiale Cheng, Chujie Zheng, Hao Zhou, Nanyun Peng, Xiaoyan Zhu, Minlie Huang

We propose a taxonomy for dialogue safety specifically designed to capture unsafe behaviors in human-bot dialogue settings, with focuses on context-sensitive unsafety, which is under-explored in prior works.

Reward Shifting for Optimistic Exploration and Conservative Exploitation

no code implementations29 Sep 2021 Hao Sun, Lei Han, Jian Guo, Bolei Zhou

We verify our insight on a range of tasks: (1) In offline RL, the conservative exploitation leads to improved learning performance based on off-the-shelf algorithms; (2) In online continuous control, multiple value functions with different shifting constants can be used to trade-off between exploration and exploitation thus improving learning efficiency; (3) In online RL with discrete action space, a negative reward shifting brings an improvement over the previous curiosity-based exploration method.

Continuous Control Offline RL

SPLID: Self-Imitation Policy Learning through Iterative Distillation

no code implementations29 Sep 2021 Zhihan Liu, Hao Sun, Bolei Zhou

To this end, we propose a novel meta-algorithm Self-Imitation Policy Learning through Iterative Distillation (SPLID) which relies on the concept of $\delta$-distilled policy to iteratively level up the quality of the target data and agent mimics from the relabeled target data.

Continuous Control

EVA: An Open-Domain Chinese Dialogue System with Large-Scale Generative Pre-Training

2 code implementations3 Aug 2021 Hao Zhou, Pei Ke, Zheng Zhang, Yuxian Gu, Yinhe Zheng, Chujie Zheng, Yida Wang, Chen Henry Wu, Hao Sun, Xiaocong Yang, Bosi Wen, Xiaoyan Zhu, Minlie Huang, Jie Tang

Although pre-trained language models have remarkably enhanced the generation ability of dialogue systems, open-domain Chinese dialogue systems are still limited by the dialogue data and the model size compared with English ones.

PhyCRNet: Physics-informed Convolutional-Recurrent Network for Solving Spatiotemporal PDEs

2 code implementations26 Jun 2021 Pu Ren, Chengping Rao, Yang Liu, JianXun Wang, Hao Sun

Partial differential equations (PDEs) play a fundamental role in modeling and simulating problems across a wide range of disciplines.

Uncovering Closed-form Governing Equations of Nonlinear Dynamics from Videos

no code implementations9 Jun 2021 Lele Luan, Yang Liu, Hao Sun

Distilling analytical models from data has the potential to advance our understanding and prediction of nonlinear dynamics.

Decoder Time Series +1

Encoding physics to learn reaction-diffusion processes

2 code implementations9 Jun 2021 Chengping Rao, Pu Ren, Qi Wang, Oral Buyukozturk, Hao Sun, Yang Liu

Modeling complex spatiotemporal dynamical systems, such as the reaction-diffusion processes, have largely relied on partial differential equations (PDEs).

Epidemiology

PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Support

2 code implementations Findings (ACL) 2021 Hao Sun, Zhenru Lin, Chujie Zheng, Siyang Liu, Minlie Huang

In this paper, we propose PsyQA, a Chinese dataset of psychological health support in the form of question and answer pair.

Physics-informed Spline Learning for Nonlinear Dynamics Discovery

1 code implementation5 May 2021 Fangzheng Sun, Yang Liu, Hao Sun

Dynamical systems are typically governed by a set of linear/nonlinear differential equations.

Hard Encoding of Physics for Learning Spatiotemporal Dynamics

no code implementations2 May 2021 Chengping Rao, Hao Sun, Yang Liu

Modeling nonlinear spatiotemporal dynamical systems has primarily relied on partial differential equations (PDEs).

Epidemiology

AdsGNN: Behavior-Graph Augmented Relevance Modeling in Sponsored Search

1 code implementation25 Apr 2021 Chaozhuo Li, Bochen Pang, Yuming Liu, Hao Sun, Zheng Liu, Xing Xie, Tianqi Yang, Yanling Cui, Liangjie Zhang, Qi Zhang

Our motivation lies in incorporating the tremendous amount of unsupervised user behavior data from the historical search logs as the complementary graph to facilitate relevance modeling.

Marketing

Structure-Preserving Progressive Low-rank Image Completion for Defending Adversarial Attacks

no code implementations4 Mar 2021 Zhiqun Zhao, Hengyou Wang, Hao Sun, Zhihai He

In this work, we propose to develop a structure-preserving progressive low-rank image completion (SPLIC) method to remove unneeded texture details from the input images and shift the bias of deep neural networks towards global object structures and semantic cues.

Adversarial Robustness Low-Rank Matrix Completion

A Supervised Segmentation Network for Hyperspectral Image Classification

no code implementations IEEE Transactions on Image Processing 2021 Hao Sun, Xiangtao Zheng, Xiaoqiang Lu

To explore the spatial information for HSI classification, pixels with its adjacent pixels are usually directly cropped from hyperspectral data to form HSI cubes in CNN-based methods.

Classification Diversity +1

Relic density of dark matter in the inert doublet model beyond leading order for the low mass region: 3. Annihilation in 3-body final state

no code implementations6 Jan 2021 Shankha Banerjee, Fawzi Boudjema, Nabarun Chakrabarty, Hao Sun

These are the dominant processes that enter the computation of the relic density for the low mass region of the inert doublet model (IDM) when annihilations to two on-shell vector bosons are closed.

High Energy Physics - Phenomenology High Energy Physics - Experiment

Relic density of dark matter in the inert doublet model beyond leading order for the low mass region: 1. Renormalisation and constraints

no code implementations6 Jan 2021 Shankha Banerjee, Fawzi Boudjema, Nabarun Chakrabarty, Hao Sun

The theoretical uncertainty brought by the scale dependence leads us to introduce a new criterion on the perturbativity of the IDM.

High Energy Physics - Phenomenology High Energy Physics - Experiment

Relic density of dark matter in the inert doublet model beyond leading order for the low mass region: 2. Co-annihilation

no code implementations6 Jan 2021 Shankha Banerjee, Fawzi Boudjema, Nabarun Chakrabarty, Hao Sun

We examine the relic density of the light mass dark matter region in the inert doublet model (IDM) when the dominant process is due to co-annihilation between the lightest neutral scalars of the model.

High Energy Physics - Phenomenology High Energy Physics - Experiment

Relic density of dark matter in the inert doublet model beyond leading order for the low mass region: 4. The Higgs resonance region

no code implementations6 Jan 2021 Shankha Banerjee, Fawzi Boudjema, Nabarun Chakrabarty, Hao Sun

One-loop electroweak corrections to the annihilation cross-sections of dark matter in the Higgs resonance region of the inert doublet model (IDM) are investigated.

High Energy Physics - Phenomenology High Energy Physics - Experiment

Self-Supervised Continuous Control without Policy Gradient

no code implementations1 Jan 2021 Hao Sun, Ziping Xu, Meng Fang, Yuhang Song, Jiechao Xiong, Bo Dai, Zhengyou Zhang, Bolei Zhou

Despite the remarkable progress made by the policy gradient algorithms in reinforcement learning (RL), sub-optimal policies usually result from the local exploration property of the policy gradient update.

Continuous Control Policy Gradient Methods +3

On the Guaranteed Almost Equivalence between Imitation Learning from Observation and Demonstration

no code implementations16 Oct 2020 Zhihao Cheng, Liu Liu, Aishan Liu, Hao Sun, Meng Fang, DaCheng Tao

By contrast, this paper proves that LfO is almost equivalent to LfD in the deterministic robot environment, and more generally even in the robot environment with bounded randomness.

Imitation Learning

A Human Ear Reconstruction Autoencoder

no code implementations7 Oct 2020 Hao Sun, Nick Pears, Hang Dai

The ear, as an important part of the human head, has received much less attention compared to the human face in the area of computer vision.

3D Face Reconstruction Self-Supervised Learning

Extracting full-field subpixel structural displacements from videos via deep learning

no code implementations31 Aug 2020 Lele Luan, Jingwei Zheng, Yongchao Yang, Ming L. Wang, Hao Sun

This paper develops a deep learning framework based on convolutional neural networks (CNNs) that enable real-time extraction of full-field subpixel structural displacements from videos.

Incremental Bayesian tensor learning for structural monitoring data imputation and response forecasting

no code implementations1 Jul 2020 Pu Ren, Xinyu Chen, Lijun Sun, Hao Sun

To address this fundamental issue, this paper presents an incremental Bayesian tensor learning method for reconstruction of spatiotemporal missing data in SHM and forecasting of structural response.

Imputation Incremental Learning +1

Non-local Policy Optimization via Diversity-regularized Collaborative Exploration

no code implementations14 Jun 2020 Zhenghao Peng, Hao Sun, Bolei Zhou

Conventional Reinforcement Learning (RL) algorithms usually have one single agent learning to solve the task independently.

Diversity Reinforcement Learning (RL)

Zeroth-Order Supervised Policy Improvement

no code implementations11 Jun 2020 Hao Sun, Ziping Xu, Yuhang Song, Meng Fang, Jiechao Xiong, Bo Dai, Bolei Zhou

However, PG algorithms rely on exploiting the value function being learned with the first-order update locally, which results in limited sample efficiency.

Continuous Control Policy Gradient Methods +2

Physics informed deep learning for computational elastodynamics without labeled data

1 code implementation10 Jun 2020 Chengping Rao, Hao Sun, Yang Liu

In this paper, we present a physics-informed neural network (PINN) with mixed-variable output to model elastodynamics problems without resort to labeled data, in which the I/BCs are hardly imposed.

Philosophy

MultiSpeech: Multi-Speaker Text to Speech with Transformer

1 code implementation8 Jun 2020 Mingjian Chen, Xu Tan, Yi Ren, Jin Xu, Hao Sun, Sheng Zhao, Tao Qin, Tie-Yan Liu

Transformer-based text to speech (TTS) model (e. g., Transformer TTS~\cite{li2019neural}, FastSpeech~\cite{ren2019fastspeech}) has shown the advantages of training and inference efficiency over RNN-based model (e. g., Tacotron~\cite{shen2018natural}) due to its parallel computation in training and/or inference.

Decoder

Sparse representation for damage identification of structural systems

no code implementations6 Jun 2020 Zhao Chen, Hao Sun

Specifically, an $\ell_2$ Bayesian learning method is firstly developed for updating the intact model and uncertainty quantification so as to set forward a baseline for damage detection.

Bayesian Optimization Uncertainty Quantification

Novel Policy Seeking with Constrained Optimization

1 code implementation21 May 2020 Hao Sun, Zhenghao Peng, Bo Dai, Jian Guo, Dahua Lin, Bolei Zhou

In problem-solving, we humans can come up with multiple novel solutions to the same problem.

Diversity reinforcement-learning +1

Physics-informed learning of governing equations from scarce data

1 code implementation5 May 2020 Zhao Chen, Yang Liu, Hao Sun

Harnessing data to discover the underlying governing laws or equations that describe the behavior of complex physical systems can significantly advance our modeling, simulation and understanding of such systems in various science and engineering disciplines.

Model Discovery Representation Learning

LightPAFF: A Two-Stage Distillation Framework for Pre-training and Fine-tuning

no code implementations27 Apr 2020 Kaitao Song, Hao Sun, Xu Tan, Tao Qin, Jianfeng Lu, Hongzhi Liu, Tie-Yan Liu

While pre-training and fine-tuning, e. g., BERT~\citep{devlin2018bert}, GPT-2~\citep{radford2019language}, have achieved great success in language understanding and generation tasks, the pre-trained models are usually too big for online deployment in terms of both memory cost and inference speed, which hinders them from practical online usage.

Knowledge Distillation Language Modelling

Evolutionary Stochastic Policy Distillation

1 code implementation27 Apr 2020 Hao Sun, Xinyu Pan, Bo Dai, Dahua Lin, Bolei Zhou

Solving the Goal-Conditioned Reward Sparse (GCRS) task is a challenging reinforcement learning problem due to the sparsity of reward signals.

Reciprocal Learning Networks for Human Trajectory Prediction

no code implementations CVPR 2020 Hao Sun, Zhiqun Zhao, Zhihai He

Based on this unique property, we develop a new approach, called reciprocal learning, for human trajectory prediction.

Trajectory Prediction

Existence of an equilibrium for pure exchange economy with fuzzy preferences

no code implementations19 Mar 2020 Xia Zhang, Hao Sun, Xuanzhu Jin, Moses Olabhele Esangbedo

We set up a new fuzzy binary relation on the consumption set to evaluate the fuzzy preferences.

Computer Science and Game Theory

Physics-informed deep learning for incompressible laminar flows

1 code implementation24 Feb 2020 Chengping Rao, Hao Sun, Yang Liu

Physics-informed deep learning has drawn tremendous interest in recent years to solve computational physics problems, whose basic concept is to embed physical laws to constrain/inform neural networks, with the need of less data for training a reliable model.

Policy Continuation with Hindsight Inverse Dynamics

1 code implementation NeurIPS 2019 Hao Sun, Zhizhong Li, Xiaotong Liu, Dahua Lin, Bolei Zhou

This approach learns from Hindsight Inverse Dynamics based on Hindsight Experience Replay, enabling the learning process in a self-imitated manner and thus can be trained with supervised learning.

Reinforcement Learning (RL)

MixModule: Mixed CNN Kernel Module for Medical Image Segmentation

no code implementations19 Oct 2019 Henry H. Yu, Xue Feng, Hao Sun, Ziwen Wang

Convolutional neural networks (CNNs) have been successfully applied to medical image classification, segmentation, and related tasks.

Image Classification Image Segmentation +4

GetNet: Get Target Area for Image Pairing

no code implementations8 Oct 2019 Henry H. Yu, Jiang Liu, Hao Sun, Ziwen Wang, Haotian Zhang

Image pairing is an important research task in the field of computer vision.

Person Re-Identification

Learning with Social Influence through Interior Policy Differentiation

no code implementations25 Sep 2019 Hao Sun, Bo Dai, Jiankai Sun, Zhenghao Peng, Guodong Xu, Dahua Lin, Bolei Zhou

In this work we model the social influence into the scheme of reinforcement learning, enabling the agents to learn both from the environment and from their peers.

Reinforcement Learning (RL)

Snowball: Iterative Model Evolution and Confident Sample Discovery for Semi-Supervised Learning on Very Small Labeled Datasets

no code implementations4 Sep 2019 Yang Li, Jianhe Yuan, Zhiqun Zhao, Hao Sun, Zhihai He

In this work, we develop a joint sample discovery and iterative model evolution method for semi-supervised learning on very small labeled training sets.

Adaptive Regularization of Labels

no code implementations15 Aug 2019 Qianggang Ding, Sifan Wu, Hao Sun, Jiadong Guo, Shu-Tao Xia

In addition, label regularization techniques such as label smoothing and label disturbance have also been proposed with the motivation of adding a stochastic perturbation to labels.

Data Augmentation Knowledge Distillation +2

ResNet Can Be Pruned 60x: Introducing Network Purification and Unused Path Removal (P-RM) after Weight Pruning

no code implementations30 Apr 2019 Xiaolong Ma, Geng Yuan, Sheng Lin, Zhengang Li, Hao Sun, Yanzhi Wang

The state-of-art DNN structures involve high computation and great demand for memory storage which pose intensive challenge on DNN framework resources.

Computer-aided diagnosis in histopathological images of the endometrium using a convolutional neural network and attention mechanisms

1 code implementation24 Apr 2019 Hao Sun, Xianxu Zeng, Tao Xu, Gang Peng, Yutao Ma

In the ten-fold cross-validation process, the CADx approach, HIENet, achieved a 76. 91 $\pm$ 1. 17% (mean $\pm$ s. d.) classification accuracy for four classes of endometrial tissue, namely normal endometrium, endometrial polyp, endometrial hyperplasia, and endometrial adenocarcinoma.

Binary Classification Classification +2

Comparison Network for One-Shot Conditional Object Detection

no code implementations4 Apr 2019 Tengfei Zhang, Yue Zhang, Xian Sun, Hao Sun, Menglong Yan, Xue Yang, Kun fu

A two-stage detector for OSCD is introduced to compare the extracted query and target features with the learnable metric to approach the optimized non-linear conditional probability.

Object object-detection +1

Learning Fast Matching Models from Weak Annotations

no code implementations30 Jan 2019 Xue Li, Zhipeng Luo, Hao Sun, Jianjin Zhang, Weihao Han, Xianqi Chu, Liangjie Zhang, Qi Zhang

The proposed training framework targets on mitigating both issues, by treating the stronger but undeployable models as annotators, and learning a deployable model from both human provided relevance labels and weakly annotated search log data.

IntRepair: Informed Repairing of Integer Overflows

2 code implementations12 Jul 2018 Paul Muntean, Martin Monperrus, Hao Sun, Jens Grossklags, Claudia Eckert

Thus, in this paper, we propose a novel technique to provide automatic repairs of integer overflows in C source code.

Software Engineering

Position Detection and Direction Prediction for Arbitrary-Oriented Ships via Multitask Rotation Region Convolutional Neural Network

3 code implementations13 Jun 2018 Xue Yang, Hao Sun, Xian Sun, Menglong Yan, Zhi Guo, Kun fu

The complexity of application scenarios, the redundancy of detection region, and the difficulty of dense ship detection are all the main obstacles that limit the successful operation of traditional methods in ship detection.

Position

Automatic Ship Detection of Remote Sensing Images from Google Earth in Complex Scenes Based on Multi-Scale Rotation Dense Feature Pyramid Networks

4 code implementations12 Jun 2018 Xue Yang, Hao Sun, Kun fu, Jirui Yang, Xian Sun, Menglong Yan, Zhi Guo

Additionally, in the case of ship rotation and dense arrangement, we design a rotation anchor strategy to predict the minimum circumscribed rectangle of the object so as to reduce the redundant detection region and improve the recall.

object-detection Object Detection

Progressive Neural Networks for Image Classification

no code implementations25 Apr 2018 Zhi Zhang, Guanghan Ning, Yigang Cen, Yang Li, Zhiqun Zhao, Hao Sun, Zhihai He

The inference structures and computational complexity of existing deep neural networks, once trained, are fixed and remain the same for all test images.

Classification General Classification +1

Hyperspectral Unmixing with Endmember Variability using Semi-supervised Partial Membership Latent Dirichlet Allocation

no code implementations17 Mar 2017 Sheng Zou, Hao Sun, Alina Zare

A semi-supervised Partial Membership Latent Dirichlet Allocation approach is developed for hyperspectral unmixing and endmember estimation while accounting for spectral variability and spatial information.

Hyperspectral Unmixing

Spice up Your Chat: The Intentions and Sentiment Effects of Using Emoji

no code implementations8 Mar 2017 Tianran Hu, Han Guo, Hao Sun, Thuy-vy Thi Nguyen, Jiebo Luo

Second, from a perspective of message recipients, we further study the sentiment effects of emojis, as well as their duplications, on verbal messages.

Map-guided Hyperspectral Image Superpixel Segmentation Using Proportion Maps

no code implementations6 Jan 2017 Hao Sun, Alina Zare

A map-guided superpixel segmentation method for hyperspectral imagery is developed and introduced.

Segmentation

Degree of W-operator and Noncrossing Partition

no code implementations20 Oct 2016 Hao Sun

We prove that W([n]) can be written as the sum of n!

Combinatorics

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