Search Results for author: Zhen Wang

Found 153 papers, 59 papers with code

Deep Streaming Label Learning

1 code implementation ICML 2020 Zhen Wang, Liu Liu, DaCheng Tao

In order to fill in these research gaps, we propose a novel deep neural network (DNN) based framework, Deep Streaming Label Learning (DSLL), to classify instances with newly emerged labels effectively.

Multi-Label Learning

Towards Efficient LLM Grounding for Embodied Multi-Agent Collaboration

no code implementations23 May 2024 Yang Zhang, Shixin Yang, Chenjia Bai, Fei Wu, Xiu Li, Zhen Wang, Xuelong Li

In this paper, we propose a novel framework for multi-agent collaboration that introduces Reinforced Advantage feedback (ReAd) for efficient self-refinement of plans.


FreeTuner: Any Subject in Any Style with Training-free Diffusion

no code implementations23 May 2024 Youcan Xu, Zhen Wang, Jun Xiao, Wei Liu, Long Chen

With the advance of diffusion models, various personalized image generation methods have been proposed.

Disentanglement Image Generation

Ensemble Successor Representations for Task Generalization in Offline-to-Online Reinforcement Learning

no code implementations12 May 2024 Changhong Wang, Xudong Yu, Chenjia Bai, Qiaosheng Zhang, Zhen Wang

To address this problem, our work builds upon the investigation of successor representations for task generalization in online RL and extends the framework to incorporate offline-to-online learning.

Offline RL Reinforcement Learning (RL) +1

Contrastive Representation for Data Filtering in Cross-Domain Offline Reinforcement Learning

1 code implementation10 May 2024 Xiaoyu Wen, Chenjia Bai, Kang Xu, Xudong Yu, Yang Zhang, Xuelong Li, Zhen Wang

In this paper, we propose a novel representation-based approach to measure the domain gap, where the representation is learned through a contrastive objective by sampling transitions from different domains.


Pessimistic Value Iteration for Multi-Task Data Sharing in Offline Reinforcement Learning

1 code implementation30 Apr 2024 Chenjia Bai, Lingxiao Wang, Jianye Hao, Zhuoran Yang, Bin Zhao, Zhen Wang, Xuelong Li

We further provide theoretical analysis, which shows that the optimality gap of our method is only related to the expected data coverage of the shared dataset, thus resolving the distribution shift issue in data sharing.

Offline RL Reinforcement Learning (RL) +1

Provably Efficient Information-Directed Sampling Algorithms for Multi-Agent Reinforcement Learning

no code implementations30 Apr 2024 Qiaosheng Zhang, Chenjia Bai, Shuyue Hu, Zhen Wang, Xuelong Li

Finally, we extend Reg-MAIDS to multi-player general-sum MGs and prove that it can learn either the Nash equilibrium or coarse correlated equilibrium in a sample efficient manner.

Multi-agent Reinforcement Learning

A General Black-box Adversarial Attack on Graph-based Fake News Detectors

no code implementations24 Apr 2024 Peican Zhu, Zechen Pan, Yang Liu, Jiwei Tian, Keke Tang, Zhen Wang

Specifically, as sharing is an important social interaction for GNN-based fake news detectors to construct the graph, we simulate sharing behaviors to fool the detectors.

Adversarial Attack Graph Neural Network

Diverse Randomized Value Functions: A Provably Pessimistic Approach for Offline Reinforcement Learning

no code implementations9 Apr 2024 Xudong Yu, Chenjia Bai, Hongyi Guo, Changhong Wang, Zhen Wang

Offline Reinforcement Learning (RL) faces distributional shift and unreliable value estimation, especially for out-of-distribution (OOD) actions.

Reinforcement Learning (RL) Uncertainty Quantification

LLM Reasoners: New Evaluation, Library, and Analysis of Step-by-Step Reasoning with Large Language Models

1 code implementation8 Apr 2024 Shibo Hao, Yi Gu, Haotian Luo, Tianyang Liu, Xiyan Shao, Xinyuan Wang, Shuhua Xie, Haodi Ma, Adithya Samavedhi, Qiyue Gao, Zhen Wang, Zhiting Hu

(2) We develop LLM Reasoners, a library for standardized modular implementation of existing and new reasoning algorithms, under a unified formulation of the search, reward, and world model components.

AUEditNet: Dual-Branch Facial Action Unit Intensity Manipulation with Implicit Disentanglement

no code implementations CVPR 2024 Shiwei Jin, Zhen Wang, Lei Wang, Peng Liu, Ning Bi, Truong Nguyen

Our experiments demonstrate AUEditNet's superior accuracy in editing AU intensities, affirming its capability in disentangling facial attributes and identity within a limited subject pool.

Attribute Disentanglement

Graph Regularized NMF with L20-norm for Unsupervised Feature Learning

no code implementations16 Mar 2024 Zhen Wang, Wenwen Min

Nonnegative Matrix Factorization (NMF) is a widely applied technique in the fields of machine learning and data mining.

Dimensionality Reduction feature selection

Emergence of Social Norms in Generative Agent Societies: Principles and Architecture

1 code implementation13 Mar 2024 Siyue Ren, Zhiyao Cui, Ruiqi Song, Zhen Wang, Shuyue Hu

Our experiments deployed in the Smallville sandbox game environment demonstrate the capability of our architecture to establish social norms and reduce social conflicts within generative MASs.

Language Modelling Large Language Model

GIN-SD: Source Detection in Graphs with Incomplete Nodes via Positional Encoding and Attentive Fusion

no code implementations27 Feb 2024 Le Cheng, Peican Zhu, Keke Tang, Chao GAO, Zhen Wang

In this paper, we address a more challenging task, rumor source detection with incomplete user data, and propose a novel framework, i. e., Source Detection in Graphs with Incomplete Nodes via Positional Encoding and Attentive Fusion (GIN-SD), to tackle this challenge.

Multi-Agent, Human-Agent and Beyond: A Survey on Cooperation in Social Dilemmas

no code implementations27 Feb 2024 Hao Guo, Chunjiang Mu, Yang Chen, Chen Shen, Shuyue Hu, Zhen Wang

Third, we review the emergent field of leveraging AI agents to enhance cooperation among humans.

Improving Data Augmentation for Robust Visual Question Answering with Effective Curriculum Learning

no code implementations28 Jan 2024 Yuhang Zheng, Zhen Wang, Long Chen

Compared to training on the entire augmented dataset, our ECL strategy can further enhance VQA models' performance with fewer training samples.

Data Augmentation Question Answering +1

Diffusion-based Data Augmentation for Object Counting Problems

no code implementations25 Jan 2024 Zhen Wang, Yuelei Li, Jia Wan, Nuno Vasconcelos

Our proposed smoothed density map input for ControlNet significantly improves ControlNet's performance in generating crowds in the correct locations.

Crowd Counting Data Augmentation +2

Community Detection in the Multi-View Stochastic Block Model

no code implementations17 Jan 2024 Yexin Zhang, Zhongtian Ma, Qiaosheng Zhang, Zhen Wang, Xuelong Li

This paper considers the problem of community detection on multiple potentially correlated graphs from an information-theoretical perspective.

Community Detection Stochastic Block Model

Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling

1 code implementation17 Jan 2024 Hong Wang, Zhongkai Hao, Jie Wang, Zijie Geng, Zhen Wang, Bin Li, Feng Wu

To the best of our knowledge, SKR is the first attempt to address the time-consuming nature of data generation for learning neural operators.

Matrix Completion with Hypergraphs:Sharp Thresholds and Efficient Algorithms

no code implementations16 Jan 2024 Zhongtian Ma, Qiaosheng Zhang, Zhen Wang

Theoretical analyses show that our algorithm succeeds with high probability as long as the sample probability exceeds the aforementioned threshold, and this theoretical result is further validated by synthetic experiments.

Matrix Completion

Improving Graph Contrastive Learning via Adaptive Positive Sampling

no code implementations CVPR 2024 Jiaming Zhuo, Feiyang Qin, Can Cui, Kun fu, bingxin niu, Mengzhu Wang, Yuanfang Guo, Chuan Wang, Zhen Wang, Xiaochun Cao, Liang Yang

Graph Contrastive Learning (GCL) a Self-Supervised Learning (SSL) architecture tailored for graphs has shown notable potential for mitigating label scarcity.

Contrastive Learning Self-Supervised Learning

OVD-Explorer: Optimism Should Not Be the Sole Pursuit of Exploration in Noisy Environments

no code implementations19 Dec 2023 Jinyi Liu, Zhi Wang, Yan Zheng, Jianye Hao, Chenjia Bai, Junjie Ye, Zhen Wang, Haiyin Piao, Yang Sun

In reinforcement learning, the optimism in the face of uncertainty (OFU) is a mainstream principle for directing exploration towards less explored areas, characterized by higher uncertainty.

Continuous Control

Transferring CLIP's Knowledge into Zero-Shot Point Cloud Semantic Segmentation

no code implementations12 Dec 2023 Yuanbin Wang, Shaofei Huang, Yulu Gao, Zhen Wang, Rui Wang, Kehua Sheng, Bo Zhang, Si Liu

In this work, we focus on zero-shot point cloud semantic segmentation and propose a simple yet effective baseline to transfer the visual-linguistic knowledge implied in CLIP to point cloud encoder at both feature and output levels.

3D Semantic Segmentation Point Cloud Segmentation +2

GAMC: An Unsupervised Method for Fake News Detection using Graph Autoencoder with Masking

no code implementations10 Dec 2023 Shu Yin, Chao GAO, Zhen Wang

With the rise of social media, the spread of fake news has become a significant concern, potentially misleading public perceptions and impacting social stability.

Contrastive Learning Decoder +2

MVDD: Multi-View Depth Diffusion Models

no code implementations8 Dec 2023 Zhen Wang, Qiangeng Xu, Feitong Tan, Menglei Chai, Shichen Liu, Rohit Pandey, Sean Fanello, Achuta Kadambi, yinda zhang

State-of-the-art results from extensive experiments demonstrate MVDD's excellent ability in 3D shape generation, depth completion, and its potential as a 3D prior for downstream tasks.

3D Shape Generation Denoising +3

Control of the Power Flows of a Stochastic Power System

no code implementations27 Nov 2023 Zhen Wang, Kaihua Xi, Aijie Cheng, Hai Xiang Lin, Jan H. van Schuppen

The critical subset is related to the power flows of all power lines of a power system and to transient stability.

DECap: Towards Generalized Explicit Caption Editing via Diffusion Mechanism

no code implementations25 Nov 2023 Zhen Wang, Xinyun Jiang, Jun Xiao, Tao Chen, Long Chen

The denoising process involves the explicit predictions of edit operations and corresponding content words, refining reference captions through iterative step-wise editing.

Caption Generation Denoising +1

Octavius: Mitigating Task Interference in MLLMs via LoRA-MoE

1 code implementation5 Nov 2023 Zeren Chen, Ziqin Wang, Zhen Wang, Huayang Liu, Zhenfei Yin, Si Liu, Lu Sheng, Wanli Ouyang, Yu Qiao, Jing Shao

While this phenomenon has been overlooked in previous work, we propose a novel and extensible framework, called Octavius, for comprehensive studies and experimentation on multimodal learning with Multimodal Large Language Models (MLLMs).

Decoder Zero-shot Generalization

PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization

1 code implementation25 Oct 2023 Xinyuan Wang, Chenxi Li, Zhen Wang, Fan Bai, Haotian Luo, Jiayou Zhang, Nebojsa Jojic, Eric P. Xing, Zhiting Hu

Highly effective, task-specific prompts are often heavily engineered by experts to integrate detailed instructions and domain insights based on a deep understanding of both instincts of large language models (LLMs) and the intricacies of the target task.


Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages

1 code implementation11 Oct 2023 Guozheng Ma, Lu Li, Sen Zhang, Zixuan Liu, Zhen Wang, Yixin Chen, Li Shen, Xueqian Wang, DaCheng Tao

Plasticity, the ability of a neural network to evolve with new data, is crucial for high-performance and sample-efficient visual reinforcement learning (VRL).

Data Augmentation reinforcement-learning

Towards Robust Offline-to-Online Reinforcement Learning via Uncertainty and Smoothness

no code implementations29 Sep 2023 Xiaoyu Wen, Xudong Yu, Rui Yang, Chenjia Bai, Zhen Wang

Experimental results illustrate the superiority of RO2O in facilitating stable offline-to-online learning and achieving significant improvement with limited online interactions.

Offline RL reinforcement-learning +1

Node-Aligned Graph-to-Graph (NAG2G): Elevating Template-Free Deep Learning Approaches in Single-Step Retrosynthesis

1 code implementation27 Sep 2023 Lin Yao, Wentao Guo, Zhen Wang, Shang Xiang, Wentan Liu, Guolin Ke

Single-step retrosynthesis (SSR) in organic chemistry is increasingly benefiting from deep learning (DL) techniques in computer-aided synthesis design.

Benchmarking Graph Generation +2

Learning Point-wise Abstaining Penalty for Point Cloud Anomaly Detection

1 code implementation19 Sep 2023 Shaocong Xu, Pengfei Li, Xinyu Liu, Qianpu Sun, Yang Li, Shihui Guo, Zhen Wang, Bo Jiang, Rui Wang, Kehua Sheng, Bo Zhang, Hao Zhao

We demonstrate that learning different abstaining penalties, apart from point-wise penalty, for different types of (synthesized) outliers can further improve the performance.

Anomaly Detection Autonomous Driving +1

Least Squares Maximum and Weighted Generalization-Memorization Machines

no code implementations31 Aug 2023 Shuai Wang, Zhen Wang, Yuan-Hai Shao

Furthermore, we propose some different memory impact functions for the MIMM and WIMM.


IOB: Integrating Optimization Transfer and Behavior Transfer for Multi-Policy Reuse

no code implementations14 Aug 2023 Siyuan Li, Hao Li, Jin Zhang, Zhen Wang, Peng Liu, Chongjie Zhang

Humans have the ability to reuse previously learned policies to solve new tasks quickly, and reinforcement learning (RL) agents can do the same by transferring knowledge from source policies to a related target task.

Continual Learning Reinforcement Learning (RL)

Unstoppable Attack: Label-Only Model Inversion via Conditional Diffusion Model

no code implementations17 Jul 2023 Rongke Liu, Dong Wang, Yizhi Ren, Zhen Wang, Kaitian Guo, Qianqian Qin, Xiaolei Liu

Therefore, the attack models in existing MIAs are difficult to effectively train with the knowledge of the target model, resulting in sub-optimal attacks.

Sequential Attention Source Identification Based on Feature Representation

no code implementations28 Jun 2023 Dongpeng Hou, Zhen Wang, Chao GAO, Xuelong Li

Snapshot observation based source localization has been widely studied due to its accessibility and low cost.

Decoder Graph Attention

MAT: Mixed-Strategy Game of Adversarial Training in Fine-tuning

no code implementations27 Jun 2023 Zhehua Zhong, Tianyi Chen, Zhen Wang

Fine-tuning large-scale pre-trained language models has been demonstrated effective for various natural language processing (NLP) tasks.

On the Value of Myopic Behavior in Policy Reuse

no code implementations28 May 2023 Kang Xu, Chenjia Bai, Shuang Qiu, Haoran He, Bin Zhao, Zhen Wang, Wei Li, Xuelong Li

Leveraging learned strategies in unfamiliar scenarios is fundamental to human intelligence.

Reasoning with Language Model is Planning with World Model

3 code implementations24 May 2023 Shibo Hao, Yi Gu, Haodi Ma, Joshua Jiahua Hong, Zhen Wang, Daisy Zhe Wang, Zhiting Hu

RAP on LLAMA-33B surpasses CoT on GPT-4 with 33% relative improvement in a plan generation setting.

Language Modelling Math

Efficient Bilateral Cross-Modality Cluster Matching for Unsupervised Visible-Infrared Person ReID

no code implementations22 May 2023 De Cheng, Lingfeng He, Nannan Wang, Shizhou Zhang, Zhen Wang, Xinbo Gao

To this end, we propose a novel bilateral cluster matching-based learning framework to reduce the modality gap by matching cross-modality clusters.

Contrastive Learning Person Re-Identification

ReDirTrans: Latent-to-Latent Translation for Gaze and Head Redirection

no code implementations CVPR 2023 Shiwei Jin, Zhen Wang, Lei Wang, Ning Bi, Truong Nguyen

Then both the initial and edited embeddings are projected back (deprojected) to the initial latent space as residuals to modify the input latent vectors by subtraction and addition, representing old status removal and new status addition.

Attribute Gaze Estimation +2

Behavior Contrastive Learning for Unsupervised Skill Discovery

1 code implementation8 May 2023 Rushuai Yang, Chenjia Bai, Hongyi Guo, Siyuan Li, Bin Zhao, Zhen Wang, Peng Liu, Xuelong Li

Under mild assumptions, our objective maximizes the MI between different behaviors based on the same skill, which serves as an upper bound of the previous MI objective.

Continuous Control Contrastive Learning

Single Node Injection Label Specificity Attack on Graph Neural Networks via Reinforcement Learning

no code implementations4 May 2023 Dayuan Chen, Jian Zhang, Yuqian Lv, Jinhuan Wang, Hongjie Ni, Shanqing Yu, Zhen Wang, Qi Xuan

Furthermore, most methods concentrate on a single attack goal and lack a generalizable adversary to develop distinct attack strategies for diverse goals, thus limiting precise control over victim model behavior in real-world scenarios.


Delving into Shape-aware Zero-shot Semantic Segmentation

1 code implementation CVPR 2023 Xinyu Liu, Beiwen Tian, Zhen Wang, Rui Wang, Kehua Sheng, Bo Zhang, Hao Zhao, Guyue Zhou

Thanks to the impressive progress of large-scale vision-language pretraining, recent recognition models can classify arbitrary objects in a zero-shot and open-set manner, with a surprisingly high accuracy.

Image Segmentation Segmentation +2

HPN: Personalized Federated Hyperparameter Optimization

no code implementations11 Apr 2023 Anda Cheng, Zhen Wang, Yaliang Li, Jian Cheng

The client encoding is calculated with a random projection-based procedure to protect each client's privacy.

Federated Learning Hyperparameter Optimization

GPT is becoming a Turing machine: Here are some ways to program it

no code implementations25 Mar 2023 Ana Jojic, Zhen Wang, Nebojsa Jojic

We demonstrate that, through appropriate prompting, GPT-3 family of models can be triggered to perform iterative behaviours necessary to execute (rather than just write or recall) programs that involve loops, including several popular algorithms found in computer science curricula or software developer interviews.

In-Context Learning

LON-GNN: Spectral GNNs with Learnable Orthonormal Basis

1 code implementation24 Mar 2023 Qian Tao, Zhen Wang, Wenyuan Yu, Yaliang Li, Zhewei Wei

In recent years, a plethora of spectral graph neural networks (GNN) methods have utilized polynomial basis with learnable coefficients to achieve top-tier performances on many node-level tasks.

Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning

no code implementations6 Mar 2023 Zhen Wang, Rameswar Panda, Leonid Karlinsky, Rogerio Feris, Huan Sun, Yoon Kim

Prompt tuning, in which a base pretrained model is adapted to each task via conditioning on learned prompt vectors, has emerged as a promising approach for efficiently adapting large language models to multiple downstream tasks.

Transfer Learning

Exit options sustain altruistic punishment and decrease the second-order free-riders, but it is not a panacea

no code implementations12 Jan 2023 Chen Shen, Zhao Song, Lei Shi, Jun Tanimoto, Zhen Wang

Altruistic punishment, where individuals incur personal costs to punish others who have harmed third parties, presents an evolutionary conundrum as it undermines individual fitness.

Open-Ended Question Answering

Hard Sample Aware Network for Contrastive Deep Graph Clustering

2 code implementations16 Dec 2022 Yue Liu, Xihong Yang, Sihang Zhou, Xinwang Liu, Zhen Wang, Ke Liang, Wenxuan Tu, Liang Li, Jingcan Duan, Cancan Chen

Moreover, under the guidance of the carefully collected high-confidence clustering information, our proposed weight modulating function will first recognize the positive and negative samples and then dynamically up-weight the hard sample pairs while down-weighting the easy ones.

Attribute Clustering +1

Neighbour Consistency Guided Pseudo-Label Refinement for Unsupervised Person Re-Identification

no code implementations30 Nov 2022 De Cheng, Haichun Tai, Nannan Wang, Zhen Wang, Xinbo Gao

In this paper, we propose a Neighbour Consistency guided Pseudo Label Refinement (NCPLR) framework, which can be regarded as a transductive form of label propagation under the assumption that the prediction of each example should be similar to its nearest neighbours'.

Clustering Person Retrieval +3

BatmanNet: Bi-branch Masked Graph Transformer Autoencoder for Molecular Representation

1 code implementation25 Nov 2022 Zhen Wang, Zheng Feng, Yanjun Li, Bowen Li, Yongrui Wang, Chulin Sha, Min He, Xiaolin Li

Although substantial efforts have been made using graph neural networks (GNNs) for AI-driven drug discovery (AIDD), effective molecular representation learning remains an open challenge, especially in the case of insufficient labeled molecules.

Drug Discovery Molecular Property Prediction +4

Search to Pass Messages for Temporal Knowledge Graph Completion

1 code implementation30 Oct 2022 Zhen Wang, Haotong Du, Quanming Yao, Xuelong Li

In particular, we develop a generalized framework to explore topological and temporal information in TKGs.

Graph Neural Network Link Prediction +3

Entity Tracking via Effective Use of Multi-Task Learning Model and Mention-guided Decoding

2 code implementations12 Oct 2022 Janvijay Singh, Fan Bai, Zhen Wang

Cross-task knowledge transfer via multi-task learning has recently made remarkable progress in general NLP tasks.

Multi-Task Learning

A Comprehensive Survey of Data Augmentation in Visual Reinforcement Learning

1 code implementation10 Oct 2022 Guozheng Ma, Zhen Wang, Zhecheng Yuan, Xueqian Wang, Bo Yuan, DaCheng Tao

Visual reinforcement learning (RL), which makes decisions directly from high-dimensional visual inputs, has demonstrated significant potential in various domains.

Data Augmentation reinforcement-learning +1

ThinkSum: Probabilistic reasoning over sets using large language models

no code implementations4 Oct 2022 Batu Ozturkler, Nikolay Malkin, Zhen Wang, Nebojsa Jojic

Our results suggest that because the probabilistic inference in ThinkSum is performed outside of calls to the LLM, ThinkSum is less sensitive to prompt design, yields more interpretable predictions, and can be flexibly combined with latent variable models to extract structured knowledge from LLMs.

In-Context Learning Retrieval

Cross Task Neural Architecture Search for EEG Signal Classifications

1 code implementation1 Oct 2022 Yiqun Duan, Zhen Wang, Yi Li, Jianhang Tang, Yu-Kai Wang, Chin-Teng Lin

Recently, various neural network approaches have been proposed to improve the accuracy of EEG signal recognition.

EEG Emotion Recognition +2

Hiding Visual Information via Obfuscating Adversarial Perturbations

1 code implementation ICCV 2023 Zhigang Su, Dawei Zhou, Nannan Wangu, Decheng Li, Zhen Wang, Xinbo Gao

Growing leakage and misuse of visual information raise security and privacy concerns, which promotes the development of information protection.

Adversarial Attack De-identification +1

Compressed Sensing Based RFI Mitigation and Restoration for Pulsar Signals

no code implementations The Astrophysical Journal 2022 Hao Shan, Jianping Yuan, Na Wang, Zhen Wang

In pulsar signal processing, two primary difficulties are (1) radio-frequency interference (RFI) mitigation and (2) information loss due to preprocessing and mitigation itself.

A Game-Theoretic Perspective of Generalization in Reinforcement Learning

no code implementations7 Aug 2022 Chang Yang, Ruiyu Wang, Xinrun Wang, Zhen Wang

However, there is not a unified formulation of the various schemes, as well as the comprehensive comparisons of methods across different schemes.

Few-Shot Learning Multi-Task Learning +2

Balancing Stability and Plasticity through Advanced Null Space in Continual Learning

no code implementations25 Jul 2022 Yajing Kong, Liu Liu, Zhen Wang, DaCheng Tao

Continual learning is a learning paradigm that learns tasks sequentially with resources constraints, in which the key challenge is stability-plasticity dilemma, i. e., it is uneasy to simultaneously have the stability to prevent catastrophic forgetting of old tasks and the plasticity to learn new tasks well.

Continual Learning

Online Continual Learning with Contrastive Vision Transformer

no code implementations24 Jul 2022 Zhen Wang, Liu Liu, Yajing Kong, Jiaxian Guo, DaCheng Tao

Based on the learnable focuses, we design a focal contrastive loss to rebalance contrastive learning between new and past classes and consolidate previously learned representations.

Continual Learning Contrastive Learning

Explicit Image Caption Editing

1 code implementation20 Jul 2022 Zhen Wang, Long Chen, Wenbo Ma, Guangxing Han, Yulei Niu, Jian Shao, Jun Xiao

Given an image and a reference caption, the image caption editing task aims to correct the misalignment errors and generate a refined caption.


Bootstrapping a User-Centered Task-Oriented Dialogue System

no code implementations11 Jul 2022 Shijie Chen, Ziru Chen, Xiang Deng, Ashley Lewis, Lingbo Mo, Samuel Stevens, Zhen Wang, Xiang Yue, Tianshu Zhang, Yu Su, Huan Sun

We present TacoBot, a task-oriented dialogue system built for the inaugural Alexa Prize TaskBot Challenge, which assists users in completing multi-step cooking and home improvement tasks.

Data Augmentation Dialogue Management +2

Generalization-Memorization Machines

1 code implementation8 Jul 2022 Zhen Wang, Yuan-Hai Shao

Under this mechanism, error-based learning machines improve their memorization abilities of training data without over-fitting.


Modern Question Answering Datasets and Benchmarks: A Survey

no code implementations30 Jun 2022 Zhen Wang

Question Answering (QA) is one of the most important natural language processing (NLP) tasks.

Question Answering Visual Question Answering

FedHPO-B: A Benchmark Suite for Federated Hyperparameter Optimization

1 code implementation8 Jun 2022 Zhen Wang, Weirui Kuang, Ce Zhang, Bolin Ding, Yaliang Li

Due to this uniqueness, existing HPO benchmarks no longer satisfy the need to compare HPO methods in the FL setting.

Benchmarking Federated Learning +1

A Benchmark for Federated Hetero-Task Learning

1 code implementation7 Jun 2022 Liuyi Yao, Dawei Gao, Zhen Wang, Yuexiang Xie, Weirui Kuang, Daoyuan Chen, Haohui Wang, Chenhe Dong, Bolin Ding, Yaliang Li

To investigate the heterogeneity in federated learning in real-world scenarios, we generalize the classic federated learning to federated hetero-task learning, which emphasizes the inconsistency across the participants in federated learning in terms of both data distribution and learning tasks.

Federated Learning Meta-Learning +2

EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks

1 code implementation27 May 2022 Runlin Lei, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei

Despite their extraordinary predictive accuracy, existing approaches, such as GCN and GPRGNN, are not robust in the face of homophily changes on test graphs, rendering these models vulnerable to graph structural attacks and with limited capacity in generalizing to graphs of varied homophily levels.

Node Classification

D4: a Chinese Dialogue Dataset for Depression-Diagnosis-Oriented Chat

no code implementations24 May 2022 Binwei Yao, Chao Shi, Likai Zou, Lingfeng Dai, Mengyue Wu, Lu Chen, Zhen Wang, Kai Yu

In a depression-diagnosis-directed clinical session, doctors initiate a conversation with ample emotional support that guides the patients to expose their symptoms based on clinical diagnosis criteria.

Response Generation

PrEF: Percolation-based Evolutionary Framework for the diffusion-source-localization problem in large networks

no code implementations16 May 2022 Yang Liu, Xiaoqi Wang, Xi Wang, Zhen Wang, Jürgen Kurths

We assume that the state of a number of nodes in a network could be investigated if necessary, and study what configuration of those nodes could facilitate a better solution for the diffusion-source-localization (DSL) problem.

Towards Fine-grained Causal Reasoning and QA

1 code implementation15 Apr 2022 Linyi Yang, Zhen Wang, Yuxiang Wu, Jie Yang, Yue Zhang

Understanding causality is key to the success of NLP applications, especially in high-stakes domains.

Question Answering Sentence

FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning

1 code implementation12 Apr 2022 Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou

The incredible development of federated learning (FL) has benefited various tasks in the domains of computer vision and natural language processing, and the existing frameworks such as TFF and FATE has made the deployment easy in real-world applications.

Federated Learning Graph Learning

FederatedScope: A Flexible Federated Learning Platform for Heterogeneity

1 code implementation11 Apr 2022 Yuexiang Xie, Zhen Wang, Dawei Gao, Daoyuan Chen, Liuyi Yao, Weirui Kuang, Yaliang Li, Bolin Ding, Jingren Zhou

Although remarkable progress has been made by existing federated learning (FL) platforms to provide infrastructures for development, these platforms may not well tackle the challenges brought by various types of heterogeneity, including the heterogeneity in participants' local data, resources, behaviors and learning goals.

Federated Learning Hyperparameter Optimization

PAnDR: Fast Adaptation to New Environments from Offline Experiences via Decoupling Policy and Environment Representations

1 code implementation6 Apr 2022 Tong Sang, Hongyao Tang, Yi Ma, Jianye Hao, Yan Zheng, Zhaopeng Meng, Boyan Li, Zhen Wang

In online adaptation phase, with the environment context inferred from few experiences collected in new environments, the policy is optimized by gradient ascent with respect to the PDVF.

Contrastive Learning Decision Making

Experimental quantum adversarial learning with programmable superconducting qubits

no code implementations4 Apr 2022 Wenhui Ren, Weikang Li, Shibo Xu, Ke Wang, Wenjie Jiang, Feitong Jin, Xuhao Zhu, Jiachen Chen, Zixuan Song, Pengfei Zhang, Hang Dong, Xu Zhang, Jinfeng Deng, Yu Gao, Chuanyu Zhang, Yaozu Wu, Bing Zhang, Qiujiang Guo, Hekang Li, Zhen Wang, Jacob Biamonte, Chao Song, Dong-Ling Deng, H. Wang

Our results reveal experimentally a crucial vulnerability aspect of quantum learning systems under adversarial scenarios and demonstrate an effective defense strategy against adversarial attacks, which provide a valuable guide for quantum artificial intelligence applications with both near-term and future quantum devices.

BIG-bench Machine Learning Quantum Machine Learning

PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration

1 code implementation16 Mar 2022 Pengyi Li, Hongyao Tang, Tianpei Yang, Xiaotian Hao, Tong Sang, Yan Zheng, Jianye Hao, Matthew E. Taylor, Wenyuan Tao, Zhen Wang, Fazl Barez

However, we reveal sub-optimal collaborative behaviors also emerge with strong correlations, and simply maximizing the MI can, surprisingly, hinder the learning towards better collaboration.

Multi-agent Reinforcement Learning reinforcement-learning +1

Breaking the Curse of Dimensionality in Multiagent State Space: A Unified Agent Permutation Framework

no code implementations10 Mar 2022 Xiaotian Hao, Hangyu Mao, Weixun Wang, Yaodong Yang, Dong Li, Yan Zheng, Zhen Wang, Jianye Hao

To break this curse, we propose a unified agent permutation framework that exploits the permutation invariance (PI) and permutation equivariance (PE) inductive biases to reduce the multiagent state space.

Data Augmentation Reinforcement Learning (RL) +1

Regularized Bilinear Discriminant Analysis for Multivariate Time Series Data

no code implementations26 Feb 2022 Jianhua Zhao, Haiye Liang, Shulan Li, Zhiji Yang, Zhen Wang

To address the two problems, we propose RBLDA for MTS data classification, where each of the two within-class matrices is regularized via one parameter.

Model Selection Time Series +1

Adversarial Attacks and Defense Methods for Power Quality Recognition

1 code implementation11 Feb 2022 Jiwei Tian, Buhong Wang, Jing Li, Zhen Wang, Mete Ozay

To this end, we first propose a signal-specific method and a universal signal-agnostic method to attack power systems using generated adversarial examples.

Compactness Score: A Fast Filter Method for Unsupervised Feature Selection

no code implementations31 Jan 2022 Peican Zhu, Xin Hou, Keke Tang, Zhen Wang, Feiping Nie

For feature engineering, feature selection seems to be an important research content in which is anticipated to select "excellent" features from candidate ones.

Decision Making Dimensionality Reduction +2

MR-SVS: Singing Voice Synthesis with Multi-Reference Encoder

no code implementations11 Jan 2022 Shoutong Wang, Jinglin Liu, Yi Ren, Zhen Wang, Changliang Xu, Zhou Zhao

However, they face several challenges: 1) the fixed-size speaker embedding is not powerful enough to capture full details of the target timbre; 2) single reference audio does not contain sufficient timbre information of the target speaker; 3) the pitch inconsistency between different speakers also leads to a degradation in the generated voice.

Singing Voice Synthesis

Continual Learning With Lifelong Vision Transformer

no code implementations CVPR 2022 Zhen Wang, Liu Liu, Yiqun Duan, Yajing Kong, DaCheng Tao

Continual learning methods aim at training a neural network from sequential data with streaming labels, relieving catastrophic forgetting.

Continual Learning

Synthetic Generation of Face Videos With Plethysmograph Physiology

no code implementations CVPR 2022 Zhen Wang, Yunhao Ba, Pradyumna Chari, Oyku Deniz Bozkurt, Gianna Brown, Parth Patwa, Niranjan Vaddi, Laleh Jalilian, Achuta Kadambi

Accelerated by telemedicine, advances in Remote Photoplethysmography (rPPG) are beginning to offer a viable path toward non-contact physiological measurement.

ED2: Environment Dynamics Decomposition World Models for Continuous Control

1 code implementation6 Dec 2021 Jianye Hao, Yifu Yuan, Cong Wang, Zhen Wang

Model-based reinforcement learning (MBRL) achieves significant sample efficiency in practice in comparison to model-free RL, but its performance is often limited by the existence of model prediction error.

Continuous Control Model-based Reinforcement Learning

Understanding the Dynamics of DNNs Using Graph Modularity

1 code implementation24 Nov 2021 Yao Lu, Wen Yang, Yunzhe Zhang, Zuohui Chen, Jinyin Chen, Qi Xuan, Zhen Wang, Xiaoniu Yang

Specifically, we model the process of class separation of intermediate representations in pre-trained DNNs as the evolution of communities in dynamic graphs.

Feature Engineering

Graph-Based Similarity of Neural Network Representations

1 code implementation22 Nov 2021 Zuohui Chen, Yao Lu, Jinxuan Hu, Wen Yang, Qi Xuan, Zhen Wang, Xiaoniu Yang

Understanding the black-box representations in Deep Neural Networks (DNN) is an essential problem in deep learning.

Coarformer: Transformer for large graph via graph coarsening

no code implementations29 Sep 2021 Weirui Kuang, Zhen Wang, Yaliang Li, Zhewei Wei, Bolin Ding

We get rid of these obstacles by exploiting the complementary natures of GNN and Transformer, and trade the fine-grained long-range information for the efficiency of Transformer.

iFlood: A Stable and Effective Regularizer

no code implementations ICLR 2022 Yuexiang Xie, Zhen Wang, Yaliang Li, Ce Zhang, Jingren Zhou, Bolin Ding

However, our further studies uncover that the design of the loss function of Flooding can lead to a discrepancy between its objective and implementation, and cause the instability issue.

Image Classification

Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain

no code implementations14 Sep 2021 Jianye Hao, Tianpei Yang, Hongyao Tang, Chenjia Bai, Jinyi Liu, Zhaopeng Meng, Peng Liu, Zhen Wang

In addition to algorithmic analysis, we provide a comprehensive and unified empirical comparison of different exploration methods for DRL on a set of commonly used benchmarks.

Autonomous Vehicles Efficient Exploration +3

N24News: A New Dataset for Multimodal News Classification

1 code implementation LREC 2022 Zhen Wang, Xu Shan, Xiangxie Zhang, Jie Yang

Current news datasets merely focus on text features on the news and rarely leverage the feature of images, excluding numerous essential features for news classification.

Classification News Classification

Synchronization of Power Systems under Stochastic Disturbances

no code implementations9 Aug 2021 Zhen Wang, Kaihua Xi, Aijie Cheng, Hai Xiang Lin, André C. M. Ran, Jan H. van Schuppen, Chenghui Zhang

The synchronization of power generators is an important condition for the proper functioning of a power system, in which the fluctuations in frequency and the phase angle differences between the generators are sufficiently small when subjected to stochastic disturbances.

Overcoming Difficulty in Obtaining Dark-skinned Subjects for Remote-PPG by Synthetic Augmentation

no code implementations10 Jun 2021 Yunhao Ba, Zhen Wang, Kerim Doruk Karinca, Oyku Deniz Bozkurt, Achuta Kadambi

Camera-based remote photoplethysmography (rPPG) provides a non-contact way to measure physiological signals (e. g., heart rate) using facial videos.

Chinese Sentences Similarity via Cross-Attention Based Siamese Network

no code implementations18 Apr 2021 Zhen Wang, Xiangxie Zhang, Yicong Tan

Measuring sentence similarity is a key research area nowadays as it allows machines to better understand human languages.

Sentence Sentence Similarity

Fuzzy Discriminant Clustering with Fuzzy Pairwise Constraints

1 code implementation17 Apr 2021 Zhen Wang, Shan-Shan Wang, Lan Bai, Wen-Si Wang, Yuan-Hai Shao

In semi-supervised fuzzy clustering, this paper extends the traditional pairwise constraint (i. e., must-link or cannot-link) to fuzzy pairwise constraint.


Equilibrium and Socially optimal of a double-sided queueing system with two-mass point matching time

no code implementations28 Jan 2021 Zhen Wang, Cheryl Yang, Liwei Liu, Yiqiang Q. Zhao

The numerical scenarios illustrate the influence of parameters on the equilibrium strategy and socially optimal strategy under two information levels.

Probability 60K25, 91B50, 91A35

Ensemble and Random Collaborative Representation-Based Anomaly Detector for Hyperspectral Imagery

no code implementations6 Jan 2021 Rong Wang, Yihang Lu, Qianrong Zhang, Feiping Nie, Zhen Wang, Xuelong Li

To alleviate this problem, we proposed a novel ensemble and random collaborative representation-based detector (ERCRD) for HAD, which comprises two closely related stages.

Anomaly Detection Ensemble Learning

Semantic Inference Network for Few-shot Streaming Label Learning

no code implementations1 Jan 2021 Zhen Wang, Liu Liu, Yiqun Duan, DaCheng Tao

In this work, we formulate and study few-shot streaming label learning (FSLL), which models emerging new labels with only a few annotated examples by utilizing the knowledge learned from past labels.

Meta-Learning Multi-Label Classification

ROBY: Evaluating the Robustness of a Deep Model by its Decision Boundaries

no code implementations18 Dec 2020 Jinyin Chen, Zhen Wang, Haibin Zheng, Jun Xiao, Zhaoyan Ming

This work proposes a generic evaluation metric ROBY, a novel attack-independent robustness measure based on the model's decision boundaries.

EvaLDA: Efficient Evasion Attacks Towards Latent Dirichlet Allocation

1 code implementation9 Dec 2020 Qi Zhou, Haipeng Chen, Yitao Zheng, Zhen Wang

As one of the most powerful topic models, Latent Dirichlet Allocation (LDA) has been used in a vast range of tasks, including document understanding, information retrieval and peer-reviewer assignment.

document understanding Information Retrieval +3

Method and Dataset Entity Mining in Scientific Literature: A CNN + Bi-LSTM Model with Self-attention

no code implementations26 Oct 2020 Linlin Hou, Ji Zhang, Ou wu, Ting Yu, Zhen Wang, Zhao Li, Jianliang Gao, Yingchun Ye, Rujing Yao

We finally apply our model on PAKDD papers published from 2009-2019 to mine insightful results from scientific papers published in a longer time span.

Data Augmentation

Exploring Common and Individual Characteristics of Students via Matrix Recovering

no code implementations23 Oct 2020 Zhen Wang, Ben Teng, Yun Zhou, Hanshuang Tong, Guangtong Liu

We assume that the characteristics matrix of students' is composed of two parts: one is a low-rank matrix representing the common characteristics of students; the other is a sparse matrix representing individual characteristics of students.

Exercise Hierarchical Feature Enhanced Knowledge Tracing

no code implementations23 Oct 2020 Hanshuang Tong, Yun Zhou, Zhen Wang

Knowledge tracing is a fundamental task in the computer-aid educational system.

Knowledge Tracing

Unseen Target Stance Detection with Adversarial Domain Generalization

1 code implementation12 Oct 2020 Zhen Wang, Qiansheng Wang, Chengguo Lv, Xue Cao, Guohong Fu

Although stance detection has made great progress in the past few years, it is still facing the problem of unseen targets.

Domain Generalization Stance Detection

Cue-word Driven Neural Response Generation with a Shrinking Vocabulary

1 code implementation10 Oct 2020 Qiansheng Wang, Yuxin Liu, Chengguo Lv, Zhen Wang, Guohong Fu

Open-domain response generation is the task of generating sensible and informative re-sponses to the source sentence.

Response Generation Sentence

FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data

no code implementations29 Jul 2020 Yuexiang Xie, Zhen Wang, Yaliang Li, Bolin Ding, Nezihe Merve Gürel, Ce Zhang, Minlie Huang, Wei. Lin, Jingren Zhou

Then we instantiate this search strategy by optimizing both a dedicated graph neural network (GNN) and the adjacency tensor associated with the defined feature graph.

Graph Neural Network Recommendation Systems

HGKT: Introducing Hierarchical Exercise Graph for Knowledge Tracing

no code implementations13 Jun 2020 Hanshuang Tong, Zhen Wang, Yun Zhou, Shiwei Tong, Wenyuan Han, Qi Liu

To solve the above problems, we propose a hierarchical graph knowledge tracing model called HGKT to explore the latent hierarchical relations between exercises.

Knowledge Tracing

Rationalizing Medical Relation Prediction from Corpus-level Statistics

1 code implementation ACL 2020 Zhen Wang, Jennifer Lee, Simon Lin, Huan Sun

Nowadays, the interpretability of machine learning models is becoming increasingly important, especially in the medical domain.

Decision Making Relation

A Semi-supervised Graph Attentive Network for Financial Fraud Detection

1 code implementation28 Feb 2020 Daixin Wang, Jianbin Lin, Peng Cui, Quanhui Jia, Zhen Wang, Yanming Fang, Quan Yu, Jun Zhou, Shuang Yang, Yuan Qi

Additionally, among the network, only very few of the users are labelled, which also poses a great challenge for only utilizing labeled data to achieve a satisfied performance on fraud detection.

Fraud Detection Graph Neural Network

Tree++: Truncated Tree Based Graph Kernels

1 code implementation23 Feb 2020 Wei Ye, Zhen Wang, Rachel Redberg, Ambuj Singh

At the heart of Tree++ is a graph kernel called the path-pattern graph kernel.

Graph Similarity

Multiple Flat Projections for Cross-manifold Clustering

no code implementations17 Feb 2020 Lan Bai, Yuan-Hai Shao, Wei-Jie Chen, Zhen Wang, Nai-Yang Deng

In this paper, we propose a Multiple Flat Projections Clustering (MFPC) to deal with cross-manifold clustering problems.


Texture Classification using Block Intensity and Gradient Difference (BIGD) Descriptor

no code implementations4 Feb 2020 Yuting Hu, Zhen Wang, Ghassan AlRegib

In this paper, we present an efficient and distinctive local descriptor, namely block intensity and gradient difference (BIGD).

Classification General Classification +1

AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search

1 code implementation13 Jan 2020 Daoyuan Chen, Yaliang Li, Minghui Qiu, Zhen Wang, Bofang Li, Bolin Ding, Hongbo Deng, Jun Huang, Wei. Lin, Jingren Zhou

Motivated by the necessity and benefits of task-oriented BERT compression, we propose a novel compression method, AdaBERT, that leverages differentiable Neural Architecture Search to automatically compress BERT into task-adaptive small models for specific tasks.

Knowledge Distillation Neural Architecture Search

Learning to Answer Subjective, Specific Product-Related Queries using Customer Reviews by Adversarial Domain Adaptation

no code implementations18 Oct 2019 Manirupa Das, Zhen Wang, Evan Jaffe, Madhuja Chattopadhyay, Eric Fosler-Lussier, Rajiv Ramnath

Online customer reviews on large-scale e-commerce websites, represent a rich and varied source of opinion data, often providing subjective qualitative assessments of product usage that can help potential customers to discover features that meet their personal needs and preferences.

Domain Adaptation Sentence

A Distributed Fair Machine Learning Framework with Private Demographic Data Protection

1 code implementation17 Sep 2019 Hui Hu, Yijun Liu, Zhen Wang, Chao Lan

In this paper, we propose a distributed fair learning framework for protecting the privacy of demographic data.

BIG-bench Machine Learning Fairness

SurfCon: Synonym Discovery on Privacy-Aware Clinical Data

1 code implementation21 Jun 2019 Zhen Wang, Xiang Yue, Soheil Moosavinasab, Yungui Huang, Simon Lin, Huan Sun

To solve the problem, we propose a new framework SurfCon that leverages two important types of information in the privacy-aware clinical data, i. e., the surface form information, and the global context information for synonym discovery.

Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations

4 code implementations12 Jun 2019 Xiang Yue, Zhen Wang, Jingong Huang, Srinivasan Parthasarathy, Soheil Moosavinasab, Yungui Huang, Simon M. Lin, Wen Zhang, Ping Zhang, Huan Sun

Our experimental results demonstrate that the recent graph embedding methods achieve promising results and deserve more attention in the future biomedical graph analysis.

Graph Embedding Link Prediction +2

Fisher-Bures Adversary Graph Convolutional Networks

1 code implementation11 Mar 2019 Ke Sun, Piotr Koniusz, Zhen Wang

We try to minimize the loss wrt the perturbed $G+\Delta{G}$ while making $\Delta{G}$ to be effective in terms of the Fisher information of the neural network.

Graph Neural Network Node Classification

Characterization of migrated seismic volumes using texture attributes: a comparative study

no code implementations30 Jan 2019 Zhiling Long, Yazeed Alaudah, Muhammad Ali Qureshi, Motaz Al Farraj, Zhen Wang, Asjad Amin, Mohamed Deriche, Ghassan AlRegib

It is our hope that this comparative study will help acquaint the seismic interpretation community with the many available powerful image texture analysis techniques, providing more alternative attributes for their seismic exploration.

Image Retrieval Retrieval +2

Ramp-based Twin Support Vector Clustering

no code implementations10 Dec 2018 Zhen Wang, Xu Chen, Chun-Na Li, Yuan-Hai Shao

Traditional plane-based clustering methods measure the cost of within-cluster and between-cluster by quadratic, linear or some other unbounded functions, which may amplify the impact of cost.


Robust Bhattacharyya bound linear discriminant analysis through adaptive algorithm

no code implementations6 Nov 2018 Chun-Na Li, Yuan-Hai Shao, Zhen Wang, Nai-Yang Deng

In this paper, we propose a novel linear discriminant analysis criterion via the Bhattacharyya error bound estimation based on a novel L1-norm (L1BLDA) and L2-norm (L2BLDA).

Joint Training of Candidate Extraction and Answer Selection for Reading Comprehension

no code implementations ACL 2018 Zhen Wang, Jiachen Liu, Xinyan Xiao, Yajuan Lyu, Tian Wu

While sophisticated neural-based techniques have been developed in reading comprehension, most approaches model the answer in an independent manner, ignoring its relations with other answer candidates.

Answer Selection Reading Comprehension

A Many-Objective Evolutionary Algorithm With Two Interacting Processes: Cascade Clustering and Reference Point Incremental Learning

no code implementations3 Mar 2018 Hongwei Ge, Mingde Zhao, Liang Sun, Zhen Wang, Guozhen Tan, Qiang Zhang, C. L. Philip Chen

This paper proposes a many-objective optimization algorithm with two interacting processes: cascade clustering and reference point incremental learning (CLIA).

Clustering Incremental Learning

On the Effectiveness of Least Squares Generative Adversarial Networks

2 code implementations18 Dec 2017 Xudong Mao, Qing Li, Haoran Xie, Raymond Y. K. Lau, Zhen Wang, Stephen Paul Smolley

To overcome such a problem, we propose in this paper the Least Squares Generative Adversarial Networks (LSGANs) which adopt the least squares loss for both the discriminator and the generator.

Insensitive Stochastic Gradient Twin Support Vector Machine for Large Scale Problems

no code implementations19 Apr 2017 Zhen Wang, Yuan-Hai Shao, Lan Bai, Li-Ming Liu, Nai-Yang Deng

In this paper, stochastic gradient descent algorithm is investigated to twin support vector machines for classification.

General Classification

Least Squares Generative Adversarial Networks

23 code implementations ICCV 2017 Xudong Mao, Qing Li, Haoran Xie, Raymond Y. K. Lau, Zhen Wang, Stephen Paul Smolley

To overcome such a problem, we propose in this paper the Least Squares Generative Adversarial Networks (LSGANs) which adopt the least squares loss function for the discriminator.

Knowledge Graph Embedding by Translating on Hyperplanes

1 code implementation AAAI 2014 2014 Zhen Wang, Jianwen Zhang, Jianlin Feng, Zheng Chen

Utilizing the one-to-many/many-to-one mapping property of a relation, we propose a simple trick to reduce the possibility of false negative labeling.

Knowledge Graph Embedding Link Prediction

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