Search Results for author: Ying Zhang

Found 112 papers, 47 papers with code

Improving Zero-Shot Entity Linking Candidate Generation with Ultra-Fine Entity Type Information

1 code implementation COLING 2022 Xuhui Sui, Ying Zhang, Kehui Song, Baohang Zhou, Guoqing Zhao, Xin Wei, Xiaojie Yuan

Recently, zero-shot entity linking task has become a research hotspot, which links mentions to unseen entities to challenge the generalization ability.

Entity Linking Entity Typing +1

On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates

no code implementations22 Nov 2023 Stefano Bruno, Ying Zhang, Dong-Young Lim, Ömer Deniz Akyildiz, Sotirios Sabanis

As a result, we obtain the best known upper bound estimates in terms of key quantities of interest, such as the dimension and rates of convergence, for the Wasserstein-2 distance between the data distribution (Gaussian with unknown mean) and our sampling algorithm.

Modelling the Formation of Peer-to-Peer Trading Coalitions and Prosumer Participation Incentives in Transactive Energy Communities

no code implementations19 Nov 2023 Ying Zhang, Valentin Robu, Sho Cremers, Sonam Norbu, Benoit Couraud, Merlinda Andoni, David Flynn, H. Vincent Poor

Our experimental study shows that, for both market models, only a small number of P2P contracts, and only a fraction of total prosumers in the community are required to achieve the majority of the maximal potential Gains from Trade.

energy trading

Cooperative Multi-Agent Deep Reinforcement Learning for Adaptive Decentralized Emergency Voltage Control

no code implementations20 Oct 2023 Ying Zhang, Meng Yue

Under voltage load shedding (UVLS) for power grid emergency control builds the last defensive perimeter to prevent cascade outages and blackouts in case of contingencies.


A hybrid quantum-classical conditional generative adversarial network algorithm for human-centered paradigm in cloud

no code implementations30 Sep 2023 Wenjie Liu, Ying Zhang, Zhiliang Deng, Jiaojiao Zhao, Lian Tong

In order to solve these problems, a hybrid quantum-classical conditional generative adversarial network (QCGAN) algorithm is proposed, which is a knowledge-driven human-computer interaction computing mode that can be implemented in cloud.

Cloud Computing Quantum Machine Learning

High-Fidelity Speech Synthesis with Minimal Supervision: All Using Diffusion Models

no code implementations27 Sep 2023 Chunyu Qiang, Hao Li, Yixin Tian, Yi Zhao, Ying Zhang, Longbiao Wang, Jianwu Dang

To address these issues, we propose a minimally-supervised high-fidelity speech synthesis method, where all modules are constructed based on the diffusion models.

Speech Synthesis Voice Cloning

pLMFPPred: a novel approach for accurate prediction of functional peptides integrating embedding from pre-trained protein language model and imbalanced learning

1 code implementation25 Sep 2023 Zebin Ma, Yonglin Zou, Xiaobin Huang, Wenjin Yan, Hao Xu, Jiexin Yang, Ying Zhang, Jinqi Huang

Comparative experiments show that pLMFPPred outperforms current methods for predicting functional peptides. The experimental results suggest that the proposed method (pLMFPPred) can provide better performance in terms of Accuracy, Area under the curve - Receiver Operating Characteristics, and F1-Score than existing methods.

feature selection Protein Language Model

UniPT: Universal Parallel Tuning for Transfer Learning with Efficient Parameter and Memory

1 code implementation28 Aug 2023 Haiwen Diao, Bo Wan, Ying Zhang, Xu Jia, Huchuan Lu, Long Chen

Fine-tuning pre-trained models has emerged as a powerful technique in numerous domains, owing to its ability to leverage enormous pre-existing knowledge and achieve remarkable performance on downstream tasks.

Question Answering Retrieval +5

A Robust ADMM-Based Optimization Algorithm For Underwater Acoustic Channel Estimation

no code implementations23 Aug 2023 Tian Tian, Agastya Raj, Bruno Missi Xavier, Ying Zhang, Feiyun Wu, Kunde Yang

Accurate estimation of the Underwater acoustic (UWA) is a key part of underwater communications, especially for coherent systems.

Dark-Skin Individuals Are at More Risk on the Street: Unmasking Fairness Issues of Autonomous Driving Systems

1 code implementation5 Aug 2023 Xinyue Li, Zhenpeng Chen, Jie M. Zhang, Federica Sarro, Ying Zhang, Xuanzhe Liu

This paper conducts fairness testing on automated pedestrian detection, a crucial but under-explored issue in autonomous driving systems.

Autonomous Driving Fairness +1

Bootstrapping Contrastive Learning Enhanced Music Cold-Start Matching

no code implementations5 Aug 2023 Xinping Zhao, Ying Zhang, Qiang Xiao, Yuming Ren, Yingchun Yang

In short, given a cold-start song request, we expect to retrieve songs with similar audiences and then fastly push the cold-start song to the audiences of the retrieved songs to warm up it.

Contrastive Learning Representation Learning

How to Build Low-cost Networks for Large Language Models (without Sacrificing Performance)?

no code implementations22 Jul 2023 Weiyang Wang, Manya Ghobadi, Kayvon Shakeri, Ying Zhang, Naader Hasani

We show that LLMs exhibit a unique communication pattern where only small groups of GPUs require high-bandwidth communication to achieve near-optimal training performance.

Blocking Language Modelling +1

Where Did the President Visit Last Week? Detecting Celebrity Trips from News Articles

1 code implementation17 Jul 2023 Kai Peng, Ying Zhang, Shuai Ling, Zhaoru Ke, Haipeng Zhang

Although news articles contain travel information of celebrities, it is not possible to perform large-scale and network-wise analysis due to the lack of automatic itinerary detection tools.

Query2GMM: Learning Representation with Gaussian Mixture Model for Reasoning over Knowledge Graphs

no code implementations17 Jun 2023 Yuhan Wu, Yuanyuan Xu, Wenjie Zhang, Ying Zhang

Research along this line suggests that using multi-modal distribution to represent answer entities is more suitable than uni-modal distribution, as a single query may contain multiple disjoint answer subsets due to the compositional nature of multi-hop queries and the varying latent semantics of relations.

Knowledge Graphs

AoM: Detecting Aspect-oriented Information for Multimodal Aspect-Based Sentiment Analysis

1 code implementation31 May 2023 Ru Zhou, Wenya Guo, Xumeng Liu, Shenglong Yu, Ying Zhang, Xiaojie Yuan

Multimodal aspect-based sentiment analysis (MABSA) aims to extract aspects from text-image pairs and recognize their sentiments.

Aspect-Based Sentiment Analysis Sentiment Analysis

Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study

no code implementations23 May 2023 Yi Liu, Gelei Deng, Zhengzi Xu, Yuekang Li, Yaowen Zheng, Ying Zhang, Lida Zhao, Tianwei Zhang, Yang Liu

Our study investigates three key research questions: (1) the number of different prompt types that can jailbreak LLMs, (2) the effectiveness of jailbreak prompts in circumventing LLM constraints, and (3) the resilience of ChatGPT against these jailbreak prompts.

Prompt Engineering

Bidirectional Transformer Reranker for Grammatical Error Correction

1 code implementation22 May 2023 Ying Zhang, Hidetaka Kamigaito, Manabu Okumura

Pre-trained seq2seq models have achieved state-of-the-art results in the grammatical error correction task.

Grammatical Error Correction Language Modelling +1

From Alignment to Entailment: A Unified Textual Entailment Framework for Entity Alignment

1 code implementation19 May 2023 Yu Zhao, Yike Wu, Xiangrui Cai, Ying Zhang, Haiwei Zhang, Xiaojie Yuan

Our approach captures the unified correlation pattern of two kinds of information between entities, and explicitly models the fine-grained interaction between original entity information.

Entity Alignment Knowledge Graphs +2

Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction

2 code implementations9 May 2023 Sheng Xiang, Dawei Cheng, Chencheng Shang, Ying Zhang, Yuqi Liang

The price movement prediction of stock market has been a classical yet challenging problem, with the attention of both economists and computer scientists.

Graph Attention Time Series +1

A Mountain-Shaped Single-Stage Network for Accurate Image Restoration

1 code implementation9 May 2023 Hu Gao, Jing Yang, Ying Zhang, Ning Wang, Jingfan Yang, Depeng Dang

Image restoration is the task of aiming to obtain a high-quality image from a corrupt input image, such as deblurring and deraining.

Deblurring Image Deblurring +2

Plug-and-Play Regulators for Image-Text Matching

1 code implementation23 Mar 2023 Haiwen Diao, Ying Zhang, Wei Liu, Xiang Ruan, Huchuan Lu

Exploiting fine-grained correspondence and visual-semantic alignments has shown great potential in image-text matching.

Image Retrieval Image-text matching +1

Limits of Predictability in Top-N Recommendation

no code implementations23 Mar 2023 En Xu, Zhiwen Yu, Ying Zhang, Bin Guo, Lina Yao

This work investigates such predictability by studying the degree of regularity from a specific set of user behavior data.

SF-SGL: Solver-Free Spectral Graph Learning from Linear Measurements

no code implementations9 Feb 2023 Ying Zhang, Zhiqiang Zhao, Zhuo Feng

This work introduces a highly-scalable spectral graph densification framework (SGL) for learning resistor networks with linear measurements, such as node voltages and currents.

Graph Learning

Disco Intelligent Reflecting Surfaces: Active Channel Aging for Fully-Passive Jamming Attacks

no code implementations1 Feb 2023 Huan Huang, Ying Zhang, Hongliang Zhang, Yi Cai, A. Lee Swindlehurst, Zhu Han

A theoretical analysis of the proposed DIRS-based FPJ that provides an evaluation of the DIRS-based jamming attacks is derived.


Audio2Gestures: Generating Diverse Gestures from Audio

no code implementations17 Jan 2023 Jing Li, Di Kang, Wenjie Pei, Xuefei Zhe, Ying Zhang, Linchao Bao, Zhenyu He

Finally, we demonstrate that our method can be readily used to generate motion sequences with user-specified motion clips on the timeline.

Gesture Generation

BadPrompt: Backdoor Attacks on Continuous Prompts

1 code implementation27 Nov 2022 Xiangrui Cai, Haidong Xu, Sihan Xu, Ying Zhang, Xiaojie Yuan

To address this challenge, we propose BadPrompt, a lightweight and task-adaptive algorithm, to backdoor attack continuous prompts.

Backdoor Attack

Joint Secure Communication and Radar Beamforming: A Secrecy-Estimation Rate-Based Design

no code implementations23 Nov 2022 Rong Wen, Ying Zhang, Qiang Li, Youxi Tang

For the AN-aided SRM, by leveraging alternating optimization similar closed-form solution is obtained for the beamformer and the AN covariance matrix.

Langevin dynamics based algorithm e-TH$\varepsilon$O POULA for stochastic optimization problems with discontinuous stochastic gradient

1 code implementation24 Oct 2022 Dong-Young Lim, Ariel Neufeld, Sotirios Sabanis, Ying Zhang

We introduce a new Langevin dynamics based algorithm, called e-TH$\varepsilon$O POULA, to solve optimization problems with discontinuous stochastic gradients which naturally appear in real-world applications such as quantile estimation, vector quantization, CVaR minimization, and regularized optimization problems involving ReLU neural networks.

Portfolio Optimization Quantization +2

MoSE: Modality Split and Ensemble for Multimodal Knowledge Graph Completion

1 code implementation17 Oct 2022 Yu Zhao, Xiangrui Cai, Yike Wu, Haiwei Zhang, Ying Zhang, Guoqing Zhao, Ning Jiang

Based on these embeddings, in the inference phase, we first make modality-split predictions and then exploit various ensemble methods to combine the predictions with different weights, which models the modality importance dynamically.

Knowledge Graph Completion Representation Learning

Overcoming Language Priors in Visual Question Answering via Distinguishing Superficially Similar Instances

1 code implementation COLING 2022 Yike Wu, Yu Zhao, Shiwan Zhao, Ying Zhang, Xiaojie Yuan, Guoqing Zhao, Ning Jiang

In this work, we define the training instances with the same question type but different answers as \textit{superficially similar instances}, and attribute the language priors to the confusion of VQA model on such instances.

Question Answering Visual Question Answering

Multi-grained Label Refinement Network with Dependency Structures for Joint Intent Detection and Slot Filling

1 code implementation9 Sep 2022 Baohang Zhou, Ying Zhang, Xuhui Sui, Kehui Song, Xiaojie Yuan

To capture the semantic dependency between the syntactic information and task labels, we combine the task specific features with corresponding label embeddings by attention mechanism.

Graph Attention Intent Detection +4

Towards Higher-order Topological Consistency for Unsupervised Network Alignment

no code implementations26 Aug 2022 Qingqiang Sun, Xuemin Lin, Ying Zhang, Wenjie Zhang, Chaoqi Chen

Network alignment task, which aims to identify corresponding nodes in different networks, is of great significance for many subsequent applications.

Semi-supervised segmentation of tooth from 3D Scanned Dental Arches

1 code implementation10 Aug 2022 Ammar Alsheghri, Farnoosh Ghadiri, Ying Zhang, Olivier Lessard, Julia Keren, Farida Cheriet, Francois Guibault

In the dental field, the variability of input data is high and there are no publicly available 3D dental arch datasets.


Enabling Harmonious Human-Machine Interaction with Visual-Context Augmented Dialogue System: A Review

no code implementations2 Jul 2022 Hao Wang, Bin Guo, Yating Zeng, Yasan Ding, Chen Qiu, Ying Zhang, Lina Yao, Zhiwen Yu

The intelligent dialogue system, aiming at communicating with humans harmoniously with natural language, is brilliant for promoting the advancement of human-machine interaction in the era of artificial intelligence.

Multi-scale Attentive Image De-raining Networks via Neural Architecture Search

1 code implementation2 Jul 2022 Lei Cai, Yuli Fu, Wanliang Huo, Youjun Xiang, Tao Zhu, Ying Zhang, Huanqiang Zeng, Delu Zeng

The proposed method formulates a new multi-scale attention search space with multiple flexible modules that are favorite to the image de-raining task.

Neural Architecture Search Rain Removal

Traffic Context Aware Data Augmentation for Rare Object Detection in Autonomous Driving

no code implementations1 May 2022 Naifan Li, Fan Song, Ying Zhang, Pengpeng Liang, Erkang Cheng

In this work, we propose a systematic study on simple Copy-Paste data augmentation for rare object detection in autonomous driving.

Autonomous Driving Data Augmentation +2

Probabilistic Models for Manufacturing Lead Times

no code implementations28 Apr 2022 Recep Yusuf Bekci, Yacine Mahdid, Jinling Xing, Nikita Letov, Ying Zhang, Zahid Pasha

In this study, we utilize Gaussian processes, probabilistic neural network, natural gradient boosting, and quantile regression augmented gradient boosting to model lead times of laser manufacturing processes.

Gaussian Processes regression

Influence of the vessel wall geometry on the wall-induced migration of red blood cells

1 code implementation23 Mar 2022 Ying Zhang, Thomas G. Fai

The geometry of the blood vessel wall plays a regulatory role on the motion of red blood cells (RBCs).

GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records

no code implementations2 Feb 2022 Xi Yang, Aokun Chen, Nima PourNejatian, Hoo Chang Shin, Kaleb E Smith, Christopher Parisien, Colin Compas, Cheryl Martin, Mona G Flores, Ying Zhang, Tanja Magoc, Christopher A Harle, Gloria Lipori, Duane A Mitchell, William R Hogan, Elizabeth A Shenkman, Jiang Bian, Yonghui Wu

GatorTron models scale up the clinical language model from 110 million to 8. 9 billion parameters and improve 5 clinical NLP tasks (e. g., 9. 6% and 9. 5% improvement in accuracy for NLI and MQA), which can be applied to medical AI systems to improve healthcare delivery.

Clinical Concept Extraction Language Modelling +5

Reinforcement Learning Based Query Vertex Ordering Model for Subgraph Matching

no code implementations25 Jan 2022 Hanchen Wang, Ying Zhang, Lu Qin, Wei Wang, Wenjie Zhang, Xuemin Lin

In recent years, many advanced techniques for query vertex ordering (i. e., matching order generation) have been proposed to reduce the unpromising intermediate results according to the preset heuristic rules.

reinforcement-learning Reinforcement Learning (RL)

Detailed Balance for Particle Models of Reversible Reactions in Bounded Domains

no code implementations11 Jan 2022 Ying Zhang, Samuel A. Isaacson

In bounded domains with no-flux boundary conditions, when choosing unbinding kernels consistent with several commonly used binding kernels, we show that preserving detailed balance of spatial reaction-fluxes at all points requires spatially varying unbinding rate functions near the domain boundary.

Distribution Consistent Neural Architecture Search

no code implementations CVPR 2022 Junyi Pan, Chong Sun, Yizhou Zhou, Ying Zhang, Chen Li

We first theoretically investigate how the weight coupling problem affects the network searching performance from a parameter distribution perspective, and then propose a novel supernet training strategy with a Distribution Consistent Constraint that can provide a good measurement for the extent to which two architectures can share weights.

Neural Architecture Search

Building an AI-ready RSE Workforce

no code implementations9 Nov 2021 Ying Zhang, Matthew A. Gitzendanner, Dan S. Maxwell, Justin W. Richardson, Kaleb E. Smith, Eric A. Stubbs, Brian J. Stucky, Jingchao Zhang, Erik Deumens

Artificial Intelligence has been transforming industries and academic research across the globe, and research software development is no exception.

Decentralized Coordinated State Estimation in Integrated Transmission and Distribution Systems

no code implementations8 Nov 2021 Ying Zhang, Yanbo Chen, Jianhui Wang, Yue Meng, Tianqiao Zhao

Current transmission and distribution system states are mostly unobservable to each other, and state estimation is separately conducted in the two systems owing to the differences in network structures and analytical models.

Decoupling Long- and Short-Term Patterns in Spatiotemporal Inference

no code implementations16 Sep 2021 Junfeng Hu, Yuxuan Liang, Zhencheng Fan, Yifang Yin, Ying Zhang, Roger Zimmermann

Sensors are the key to sensing the environment and imparting benefits to smart cities in many aspects, such as providing real-time air quality information throughout an urban area.

Graph Attention

Audio2Gestures: Generating Diverse Gestures from Speech Audio with Conditional Variational Autoencoders

no code implementations ICCV 2021 Jing Li, Di Kang, Wenjie Pei, Xuefei Zhe, Ying Zhang, Zhenyu He, Linchao Bao

In order to overcome this problem, we propose a novel conditional variational autoencoder (VAE) that explicitly models one-to-many audio-to-motion mapping by splitting the cross-modal latent code into shared code and motion-specific code.

Gesture Generation

Target-Oriented Fine-tuning for Zero-Resource Named Entity Recognition

1 code implementation Findings (ACL) 2021 Ying Zhang, Fandong Meng, Yufeng Chen, Jinan Xu, Jie zhou

In this paper, we tackle the problem by transferring knowledge from three aspects, i. e., domain, language and task, and strengthening connections among them.

named-entity-recognition Named Entity Recognition +2

Non-asymptotic estimates for TUSLA algorithm for non-convex learning with applications to neural networks with ReLU activation function

1 code implementation19 Jul 2021 Dong-Young Lim, Ariel Neufeld, Sotirios Sabanis, Ying Zhang

To illustrate the applicability of the main results, we consider an example from transfer learning with ReLU neural networks, which represents a key paradigm in machine learning.

Stochastic Optimization Transfer Learning

Animatable Neural Radiance Fields from Monocular RGB Videos

1 code implementation25 Jun 2021 Jianchuan Chen, Ying Zhang, Di Kang, Xuefei Zhe, Linchao Bao, Xu Jia, Huchuan Lu

We present animatable neural radiance fields (animatable NeRF) for detailed human avatar creation from monocular videos.

3D Human Reconstruction Neural Rendering +2

Model-based 3D Hand Reconstruction via Self-Supervised Learning

1 code implementation CVPR 2021 Yujin Chen, Zhigang Tu, Di Kang, Linchao Bao, Ying Zhang, Xuefei Zhe, Ruizhi Chen, Junsong Yuan

For the first time, we demonstrate the feasibility of training an accurate 3D hand reconstruction network without relying on manual annotations.

Self-Supervised Learning

Quantifying measurement-induced nonbilocal correlation

no code implementations9 Mar 2021 Ying Zhang, Kan He

In the paper, we devote to defining an available measure to quantify the nonbilocal correlation in the entanglement-swapping experiment.

Quantum Physics

Adaptive Load Shedding for Grid Emergency Control via Deep Reinforcement Learning

no code implementations25 Feb 2021 Ying Zhang, Meng Yue, Jianhui Wang

Emergency control, typically such as under-voltage load shedding (UVLS), is broadly used to grapple with low voltage and voltage instability issues in practical power systems under contingencies.

reinforcement-learning Reinforcement Learning (RL)

Similarity Reasoning and Filtration for Image-Text Matching

1 code implementation5 Jan 2021 Haiwen Diao, Ying Zhang, Lin Ma, Huchuan Lu

Image-text matching plays a critical role in bridging the vision and language, and great progress has been made by exploiting the global alignment between image and sentence, or local alignments between regions and words.

Image Retrieval Image-text matching +1

A Unified Spectral Sparsification Framework for Directed Graphs

no code implementations1 Jan 2021 Ying Zhang, Zhiqiang Zhao, Zhuo Feng

For the first time, we prove the existence of linear-sized spectral sparsifiers for general directed graphs and introduce a practically-efficient and unified spectral graph sparsification approach that allows sparsifying real-world, large-scale directed and undirected graphs with guaranteed preservation of the original graph spectra.

Existence and uniqueness of local weak solution of d-dimensional tropical climate model without thermal diffusion in inhomogeneous Besov space

no code implementations24 Dec 2020 Baoquan Yuan, Ying Zhang

This paper studies the existence and uniqueness of local weak solutions to the d-dimensional tropical climate model without thermal diffusion.

Analysis of PDEs

Emotional Conversation Generation with Heterogeneous Graph Neural Network

1 code implementation9 Dec 2020 Yunlong Liang, Fandong Meng, Ying Zhang, Jinan Xu, Yufeng Chen, Jie zhou

Firstly, we design a Heterogeneous Graph-Based Encoder to represent the conversation content (i. e., the dialogue history, its emotion flow, facial expressions, audio, and speakers' personalities) with a heterogeneous graph neural network, and then predict suitable emotions for feedback.

Graph Neural Network for Fraud Detection via Spatial-Temporal Attention

1 code implementation TKDE 2020 Dawei Cheng, Xiaoyang Wang, Ying Zhang, Liqing Zhang

But manually generating features needs domain knowledge and may lay behind the modus operandi of fraud, which means we need to automatically focus on the most relevant fraudulent behavior patterns in the online detection system.

Fraud Detection

SF-GRASS: Solver-Free Graph Spectral Sparsification

no code implementations17 Aug 2020 Ying Zhang, Zhiqiang Zhao, Zhuo Feng

Recent spectral graph sparsification techniques have shown promising performance in accelerating many numerical and graph algorithms, such as iterative methods for solving large sparse matrices, spectral partitioning of undirected graphs, vectorless verification of power/thermal grids, representation learning of large graphs, etc.

Representation Learning

Consensus-Aware Visual-Semantic Embedding for Image-Text Matching

1 code implementation ECCV 2020 Haoran Wang, Ying Zhang, Zhong Ji, Yanwei Pang, Lin Ma

In this paper, we propose a Consensus-aware Visual-Semantic Embedding (CVSE) model to incorporate the consensus information, namely the commonsense knowledge shared between both modalities, into image-text matching.

Image Captioning Image-text matching +3

A fully data-driven approach to minimizing CVaR for portfolio of assets via SGLD with discontinuous updating

no code implementations2 Jul 2020 Sotirios Sabanis, Ying Zhang

We are thus able to provide theoretical guarantees for the algorithm's convergence in (standard) Wasserstein distances for both convex and non-convex objective functions.

Stochastic Optimization

GoGNN: Graph of Graphs Neural Network for Predicting Structured Entity Interactions

1 code implementation12 May 2020 Hanchen Wang, Defu Lian, Ying Zhang, Lu Qin, Xuemin Lin

We observe that existing works on structured entity interaction prediction cannot properly exploit the unique graph of graphs model.

Binarized Graph Neural Network

no code implementations19 Apr 2020 Hanchen Wang, Defu Lian, Ying Zhang, Lu Qin, Xiangjian He, Yiguang Lin, Xuemin Lin

Our proposed method can be seamlessly integrated into the existing GNN-based embedding approaches to binarize the model parameters and learn the compact embedding.

Graph Embedding

Task-Oriented Conversation Generation Using Heterogeneous Memory Networks

no code implementations IJCNLP 2019 Zehao Lin, Xinjing Huang, Feng Ji, Haiqing Chen, Ying Zhang

How to incorporate external knowledge into a neural dialogue model is critically important for dialogue systems to behave like real humans.

Retrieving Signals in the Frequency Domain with Deep Complex Extractors

1 code implementation25 Sep 2019 Chiheb Trabelsi, Olexa Bilaniuk, Ousmane Dia, Ying Zhang, Mirco Ravanelli, Jonathan Binas, Negar Rostamzadeh, Christopher J Pal

Using the Wall Street Journal Dataset, we compare our phase-aware loss to several others that operate both in the time and frequency domains and demonstrate the effectiveness of our proposed signal extraction method and proposed loss.

Audio Source Separation

Improving Captioning for Low-Resource Languages by Cycle Consistency

no code implementations21 Aug 2019 Yike Wu, Shiwan Zhao, Jia Chen, Ying Zhang, Xiaojie Yuan, Zhong Su

Improving the captioning performance on low-resource languages by leveraging English caption datasets has received increasing research interest in recent years.


A Survey and Experimental Analysis of Distributed Subgraph Matching

1 code implementation27 Jun 2019 Longbin Lai, Zhu Qing, Zhengyi Yang, Xin Jin, Zhengmin Lai, Ran Wang, Kongzhang Hao, Xuemin Lin, Lu Qin, Wenjie Zhang, Ying Zhang, Zhengping Qian, Jingren Zhou

We conduct extensive experiments for both unlabelled matching and labelled matching to analyze the performance of distributed subgraph matching under various settings, which is finally summarized as a practical guide.


On stochastic gradient Langevin dynamics with dependent data streams: the fully non-convex case

no code implementations30 May 2019 Ngoc Huy Chau, Éric Moulines, Miklos Rásonyi, Sotirios Sabanis, Ying Zhang

We consider the problem of sampling from a target distribution, which is \emph {not necessarily logconcave}, in the context of empirical risk minimization and stochastic optimization as presented in Raginsky et al. (2017).

Stochastic Optimization

Voiceprint recognition of Parkinson patients based on deep learning

no code implementations17 Dec 2018 Zhijing Xu, Juan Wang, Ying Zhang, Xiangjian He

In this paper, a method based on Deep Neural Network (DNN) recognition and classification combined with Mini-Batch Gradient Descent (MBGD) is proposed to distinguish PD patients from healthy people using voiceprint features.

General Classification

Fashion-Gen: The Generative Fashion Dataset and Challenge

3 code implementations21 Jun 2018 Negar Rostamzadeh, Seyedarian Hosseini, Thomas Boquet, Wojciech Stokowiec, Ying Zhang, Christian Jauvin, Chris Pal

We introduce a new dataset of 293, 008 high definition (1360 x 1360 pixels) fashion images paired with item descriptions provided by professional stylists.

Image Generation

Quaternion Convolutional Neural Networks for End-to-End Automatic Speech Recognition

1 code implementation20 Jun 2018 Titouan Parcollet, Ying Zhang, Mohamed Morchid, Chiheb Trabelsi, Georges Linarès, Renato De Mori, Yoshua Bengio

Quaternion numbers and quaternion neural networks have shown their efficiency to process multidimensional inputs as entities, to encode internal dependencies, and to solve many tasks with less learning parameters than real-valued models.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Medical Concept Embedding with Time-Aware Attention

1 code implementation6 Jun 2018 Xiangrui Cai, Jinyang Gao, Kee Yuan Ngiam, Beng Chin Ooi, Ying Zhang, Xiaojie Yuan

Embeddings of medical concepts such as medication, procedure and diagnosis codes in Electronic Medical Records (EMRs) are central to healthcare analytics.


IDEL: In-Database Entity Linking with Neural Embeddings

no code implementations13 Mar 2018 Torsten Kilias, Alexander Löser, Felix A. Gers, Richard Koopmanschap, Ying Zhang, Martin Kersten

We present a novel architecture, In-Database Entity Linking (IDEL), in which we integrate the analytics-optimized RDBMS MonetDB with neural text mining abilities.

Entity Linking Retrieval

Online Product Quantization

no code implementations29 Nov 2017 Donna Xu, Ivor W. Tsang, Ying Zhang

The experiments demonstrate that our online PQ model is both time-efficient and effective for ANN search in dynamic large scale databases compared with baseline methods and the idea of partial PQ codebook update further reduces the update cost.


Device-to-Device Load Balancing for Cellular Networks

1 code implementation7 Oct 2017 Lei Deng, Yinghui He, Ying Zhang, Minghua Chen, Zongpeng Li, Jack Y. B. Lee, Ying Jun Zhang, Lingyang Song

The idea is to shift traffic from a congested cell to its adjacent under-utilized cells by leveraging inter-cell D2D communication, so that the traffic can be served without using extra spectrum, effectively improving the spectrum temporal efficiency.

Networking and Internet Architecture

Deep Mutual Learning

8 code implementations CVPR 2018 Ying Zhang, Tao Xiang, Timothy M. Hospedales, Huchuan Lu

Model distillation is an effective and widely used technique to transfer knowledge from a teacher to a student network.

Person Re-Identification

Deep Complex Networks

9 code implementations ICLR 2018 Chiheb Trabelsi, Olexa Bilaniuk, Ying Zhang, Dmitriy Serdyuk, Sandeep Subramanian, João Felipe Santos, Soroush Mehri, Negar Rostamzadeh, Yoshua Bengio, Christopher J. Pal

Despite their attractive properties and potential for opening up entirely new neural architectures, complex-valued deep neural networks have been marginalized due to the absence of the building blocks required to design such models.

Image Classification Music Transcription +2

Fully Distributed and Asynchronized Stochastic Gradient Descent for Networked Systems

no code implementations13 Apr 2017 Ying Zhang

This paper considers a general data-fitting problem over a networked system, in which many computing nodes are connected by an undirected graph.

Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks

1 code implementation10 Jan 2017 Ying Zhang, Mohammad Pezeshki, Philemon Brakel, Saizheng Zhang, Cesar Laurent Yoshua Bengio, Aaron Courville

Meanwhile, Connectionist Temporal Classification (CTC) with Recurrent Neural Networks (RNNs), which is proposed for labeling unsegmented sequences, makes it feasible to train an end-to-end speech recognition system instead of hybrid settings.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Recurrent Neural Networks With Limited Numerical Precision

1 code implementation21 Nov 2016 Joachim Ott, Zhouhan Lin, Ying Zhang, Shih-Chii Liu, Yoshua Bengio

Recurrent Neural Networks (RNNs) produce state-of-art performance on many machine learning tasks but their demand on resources in terms of memory and computational power are often high.


Professor Forcing: A New Algorithm for Training Recurrent Networks

1 code implementation NeurIPS 2016 Alex Lamb, Anirudh Goyal, Ying Zhang, Saizheng Zhang, Aaron Courville, Yoshua Bengio

We introduce the Professor Forcing algorithm, which uses adversarial domain adaptation to encourage the dynamics of the recurrent network to be the same when training the network and when sampling from the network over multiple time steps.

Domain Adaptation Handwriting generation +3

Approximate Nearest Neighbor Search on High Dimensional Data --- Experiments, Analyses, and Improvement (v1.0)

3 code implementations8 Oct 2016 Wen Li, Ying Zhang, Yifang Sun, Wei Wang, Wenjie Zhang, Xuemin Lin

Approximate Nearest neighbor search (ANNS) is fundamental and essential operation in applications from many domains, such as databases, machine learning, multimedia, and computer vision.


Recurrent Neural Networks With Limited Numerical Precision

1 code implementation24 Aug 2016 Joachim Ott, Zhouhan Lin, Ying Zhang, Shih-Chii Liu, Yoshua Bengio

We present results from the use of different stochastic and deterministic reduced precision training methods applied to three major RNN types which are then tested on several datasets.


On Multiplicative Integration with Recurrent Neural Networks

no code implementations NeurIPS 2016 Yuhuai Wu, Saizheng Zhang, Ying Zhang, Yoshua Bengio, Ruslan Salakhutdinov

We introduce a general and simple structural design called Multiplicative Integration (MI) to improve recurrent neural networks (RNNs).

Language Modelling

Sample-Specific SVM Learning for Person Re-Identification

no code implementations CVPR 2016 Ying Zhang, Baohua Li, Huchuan Lu, Atshushi Irie, Xiang Ruan

Person re-identification addresses the problem of matching people across disjoint camera views and extensive efforts have been made to seek either the robust feature representation or the discriminative matching metrics.

Dictionary Learning imbalanced classification +1

Theano: A Python framework for fast computation of mathematical expressions

1 code implementation9 May 2016 The Theano Development Team, Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermueller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre-Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Mélanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian Goodfellow, Matt Graham, Caglar Gulcehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrancois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert T. McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang

Since its introduction, it has been one of the most used CPU and GPU mathematical compilers - especially in the machine learning community - and has shown steady performance improvements.

BIG-bench Machine Learning Clustering +2

Batch Normalized Recurrent Neural Networks

no code implementations5 Oct 2015 César Laurent, Gabriel Pereyra, Philémon Brakel, Ying Zhang, Yoshua Bengio

Recurrent Neural Networks (RNNs) are powerful models for sequential data that have the potential to learn long-term dependencies.

Language Modelling speech-recognition +1

Subspace Clustering by Mixture of Gaussian Regression

no code implementations CVPR 2015 Baohua Li, Ying Zhang, Zhouchen Lin, Huchuan Lu

Therefore, we propose Mixture of Gaussian Regression (MoG Regression) for subspace clustering by modeling noise as a Mixture of Gaussians (MoG).

Clustering regression

Cannot find the paper you are looking for? You can Submit a new open access paper.