Search Results for author: Yichi Zhang

Found 40 papers, 22 papers with code

Perturbation Analysis of Randomized SVD and its Applications to High-dimensional Statistics

no code implementations19 Mar 2022 Yichi Zhang, Minh Tang

We first derive upper bounds for the $\ell_2$ (spectral norm) and $\ell_{2\to\infty}$ (maximum row-wise $\ell_2$ norm) distances between the approximate singular vectors of $\hat{\mathbf{M}}$ and the true singular vectors of the signal matrix $\mathbf{M}$.

Community Detection Matrix Completion

Understanding Hyperdimensional Computing for Parallel Single-Pass Learning

no code implementations10 Feb 2022 Tao Yu, Yichi Zhang, Zhiru Zhang, Christopher De Sa

Using representation theory, we characterize which similarity matrices can be "expressed" by finite group VSA hypervectors, and we show how these VSAs can be constructed.

Uncertainty-Guided Mutual Consistency Learning for Semi-Supervised Medical Image Segmentation

no code implementations5 Dec 2021 Yichi Zhang, Qingcheng Liao, Rushi Jiao, Jicong Zhang

In this paper, we propose a novel uncertainty-guided mutual consistency learning framework to effectively exploit unlabeled data by integrating intra-task consistency learning from up-to-date predictions for self-ensembling and cross-task consistency learning from task-level regularization to exploit geometric shape information.

Brain Tumor Segmentation Left Atrium Segmentation +2

PokeBNN: A Binary Pursuit of Lightweight Accuracy

1 code implementation30 Nov 2021 Yichi Zhang, Zhiru Zhang, Lukasz Lew

In order to enable joint optimization of the cost together with accuracy, we define arithmetic computation effort (ACE), a hardware- and energy-inspired cost metric for quantized and binarized networks.

Binarization

Bridge the Gap Between CV and NLP! A Gradient-based Textual Adversarial Attack Framework

no code implementations28 Oct 2021 Lifan Yuan, Yichi Zhang, Yangyi Chen, Wei Wei

Despite great success on many machine learning tasks, deep neural networks are still vulnerable to adversarial samples.

Adversarial Attack Language Modelling

Adversarial Semantic Contour for Object Detection

no code implementations ICML Workshop AML 2021 Yichi Zhang, Zijian Zhu, Xiao Yang, Jun Zhu

To address this issue, we propose a novel method of Adversarial Semantic Contour (ASC) guided by object contour as prior.

Object Detection

Tiered Reasoning for Intuitive Physics: Toward Verifiable Commonsense Language Understanding

1 code implementation Findings (EMNLP) 2021 Shane Storks, Qiaozi Gao, Yichi Zhang, Joyce Chai

However, evaluations only based on end task performance shed little light on machines' true ability in language understanding and reasoning.

U-Net-and-a-half: Convolutional network for biomedical image segmentation using multiple expert-driven annotations

1 code implementation10 Aug 2021 Yichi Zhang, Jesper Kers, Clarissa A. Cassol, Joris J. Roelofs, Najia Idrees, Alik Farber, Samir Haroon, Kevin P. Daly, Suvranu Ganguli, Vipul C. Chitalia, Vijaya B. Kolachalama

If more than a single expert is involved in the annotation of the same images, then the inter-expert agreement is not necessarily perfect, and no single expert annotation can precisely capture the so-called ground truth of the regions of interest on all images.

Semantic Segmentation whole slide images

Product1M: Towards Weakly Supervised Instance-Level Product Retrieval via Cross-modal Pretraining

1 code implementation ICCV 2021 Xunlin Zhan, Yangxin Wu, Xiao Dong, Yunchao Wei, Minlong Lu, Yichi Zhang, Hang Xu, Xiaodan Liang

In this paper, we investigate a more realistic setting that aims to perform weakly-supervised multi-modal instance-level product retrieval among fine-grained product categories.

Interpretable and Low-Resource Entity Matching via Decoupling Feature Learning from Decision Making

1 code implementation ACL 2021 Zijun Yao, Chengjiang Li, Tiansi Dong, Xin Lv, Jifan Yu, Lei Hou, Juanzi Li, Yichi Zhang, Zelin Dai

Using a set of comparison features and a limited amount of annotated data, KAT Induction learns an efficient decision tree that can be interpreted by generating entity matching rules whose structure is advocated by domain experts.

Decision Making Language Modelling +1

Hierarchical Task Learning from Language Instructions with Unified Transformers and Self-Monitoring

1 code implementation Findings (ACL) 2021 Yichi Zhang, Joyce Chai

On the ALFRED benchmark for task learning, the published state-of-the-art system only achieves a task success rate of less than 10% in an unseen environment, compared to the human performance of over 90%.

Improving Conversational Recommendation System by Pretraining on Billions Scale of Knowledge Graph

no code implementations30 Apr 2021 Chi-Man Wong, Fan Feng, Wen Zhang, Chi-Man Vong, Hui Chen, Yichi Zhang, Peng He, Huan Chen, Kun Zhao, Huajun Chen

We first construct a billion-scale conversation knowledge graph (CKG) from information about users, items and conversations, and then pretrain CKG by introducing knowledge graph embedding method and graph convolution network to encode semantic and structural information respectively. To make the CTR prediction model sensible of current state of users and the relationship between dialogues and items, we introduce user-state and dialogue-interaction representations based on pre-trained CKG and propose K-DCN. In K-DCN, we fuse the user-state representation, dialogue-interaction representation and other normal feature representations via deep cross network, which will give the rank of candidate items to be recommended. We experimentally prove that our proposal significantly outperforms baselines and show it's real application in Alime.

Click-Through Rate Prediction Knowledge Graph Embedding +1

Is Multi-Hop Reasoning Really Explainable? Towards Benchmarking Reasoning Interpretability

1 code implementation EMNLP 2021 Xin Lv, Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu, Yichi Zhang, Zelin Dai

However, we find in experiments that many paths given by these models are actually unreasonable, while little works have been done on interpretability evaluation for them.

Link Prediction

Adversarial and Contrastive Variational Autoencoder for Sequential Recommendation

1 code implementation19 Mar 2021 Zhe Xie, Chengxuan Liu, Yichi Zhang, Hongtao Lu, Dong Wang, Yue Ding

To solve the above problem, in this work, we propose a novel method called Adversarial and Contrastive Variational Autoencoder (ACVAE) for sequential recommendation.

Collaborative Filtering Sequential Recommendation

Dual-Task Mutual Learning for Semi-Supervised Medical Image Segmentation

1 code implementation8 Mar 2021 Yichi Zhang, Jicong Zhang

The success of deep learning methods in medical image segmentation tasks usually requires a large amount of labeled data.

Semantic Segmentation Semi-supervised Medical Image Segmentation

Consistency of random-walk based network embedding algorithms

no code implementations18 Jan 2021 Yichi Zhang, Minh Tang

More specifically, as the network becomes sparser, our results suggest using larger window sizes, or equivalently, taking longer random walks, in order to attain better convergence rate for the resulting embeddings.

Community Detection Network Embedding

Exploiting Shared Knowledge from Non-COVID Lesions for Annotation-Efficient COVID-19 CT Lung Infection Segmentation

no code implementations31 Dec 2020 Yichi Zhang, Qingcheng Liao, Lin Yuan, He Zhu, Jiezhen Xing, Jicong Zhang

In this paper, we propose a novel relation-driven collaborative learning model to exploit shared knowledge from non-COVID lesions for annotation-efficient COVID-19 CT lung infection segmentation.

Computed Tomography (CT) Lesion Segmentation

Cascaded Convolutional Neural Network for Automatic Myocardial Infarction Segmentation from Delayed-Enhancement Cardiac MRI

no code implementations28 Dec 2020 Yichi Zhang

Automatic segmentation of myocardial contours and relevant areas like infraction and no-reflow is an important step for the quantitative evaluation of myocardial infarction.

AbdomenCT-1K: Is Abdominal Organ Segmentation A Solved Problem?

1 code implementation28 Oct 2020 Jun Ma, Yao Zhang, Song Gu, Cheng Zhu, Cheng Ge, Yichi Zhang, Xingle An, Congcong Wang, Qiyuan Wang, Xin Liu, Shucheng Cao, Qi Zhang, Shangqing Liu, Yunpeng Wang, Yuhui Li, Jian He, Xiaoping Yang

With the unprecedented developments in deep learning, automatic segmentation of main abdominal organs seems to be a solved problem as state-of-the-art (SOTA) methods have achieved comparable results with inter-rater variability on many benchmark datasets.

Continual Learning Pancreas Segmentation

Bridging 2D and 3D Segmentation Networks for Computation Efficient Volumetric Medical Image Segmentation: An Empirical Study of 2.5D Solutions

no code implementations13 Oct 2020 Yichi Zhang, Qingcheng Liao, Le Ding, Jicong Zhang

Despite these works lead to improvements on a variety of segmentation tasks, to the best of our knowledge, there has not previously been a large-scale empirical comparison of these methods.

Semantic Segmentation Volumetric Medical Image Segmentation

Dynamic Anticipation and Completion for Multi-Hop Reasoning over Sparse Knowledge Graph

1 code implementation EMNLP 2020 Xin Lv, Xu Han, Lei Hou, Juanzi Li, Zhiyuan Liu, Wei zhang, Yichi Zhang, Hao Kong, Suhui Wu

On the one hand, sparse KGs contain less information, which makes it difficult for the model to choose correct paths.

A Probabilistic End-To-End Task-Oriented Dialog Model with Latent Belief States towards Semi-Supervised Learning

1 code implementation EMNLP 2020 Yichi Zhang, Zhijian Ou, Huixin Wang, Junlan Feng

In this paper we aim at alleviating the reliance on belief state labels in building end-to-end dialog systems, by leveraging unlabeled dialog data towards semi-supervised learning.

End-To-End Dialogue Modelling

Paraphrase Augmented Task-Oriented Dialog Generation

1 code implementation ACL 2020 Silin Gao, Yichi Zhang, Zhijian Ou, Zhou Yu

Neural generative models have achieved promising performance on dialog generation tasks if given a huge data set.

Data Augmentation Response Generation

Covariance Estimation for Matrix-valued Data

no code implementations11 Apr 2020 Yichi Zhang, Weining Shen, Dehan Kong

Covariance estimation for matrix-valued data has received an increasing interest in applications.

Precision Gating: Improving Neural Network Efficiency with Dynamic Dual-Precision Activations

1 code implementation ICLR 2020 Yichi Zhang, Ritchie Zhao, Weizhe Hua, Nayun Xu, G. Edward Suh, Zhiru Zhang

The proposed approach is applicable to a variety of DNN architectures and significantly reduces the computational cost of DNN execution with almost no accuracy loss.

Quantization

SAU-Net: Efficient 3D Spine MRI Segmentation Using Inter-Slice Attention

no code implementations MIDL 2019 Yichi Zhang, Lin Yuan, Yujia Wang, Jicong Zhang

Accurate segmentation of spine Magnetic Resonance Imaging (MRI) is highly demanded in morphological research, quantitative analysis, and diseases identification, such as spinal canal stenosis, disc herniation and degeneration.

MRI segmentation

Task-Oriented Dialog Systems that Consider Multiple Appropriate Responses under the Same Context

5 code implementations24 Nov 2019 Yichi Zhang, Zhijian Ou, Zhou Yu

Conversations have an intrinsic one-to-many property, which means that multiple responses can be appropriate for the same dialog context.

Data Augmentation End-To-End Dialogue Modelling

Meta-Learning with Dynamic-Memory-Based Prototypical Network for Few-Shot Event Detection

1 code implementation25 Oct 2019 Shumin Deng, Ningyu Zhang, Jiaojian Kang, Yichi Zhang, Wei zhang, Huajun Chen

Differing from vanilla prototypical networks simply computing event prototypes by averaging, which only consume event mentions once, our model is more robust and is capable of distilling contextual information from event mentions for multiple times due to the multi-hop mechanism of DMNs.

Event Detection Event Extraction +1

Alternating Recurrent Dialog Model with Large-scale Pre-trained Language Models

1 code implementation EACL 2021 Qingyang Wu, Yichi Zhang, Yu Li, Zhou Yu

Existing dialog system models require extensive human annotations and are difficult to generalize to different tasks.

Language Modelling Response Generation

Bayesian Optimization for Materials Design with Mixed Quantitative and Qualitative Variables

no code implementations3 Oct 2019 Yichi Zhang, Daniel Apley, Wei Chen

We present in this paper the integration of a novel latent-variable (LV) approach for mixed-variable GP modeling with the BO framework for materials design.

Data-Centric Mixed-Variable Bayesian Optimization For Materials Design

no code implementations4 Jul 2019 Akshay Iyer, Yichi Zhang, Aditya Prasad, Siyu Tao, Yixing Wang, Linda Schadler, L Catherine Brinson, Wei Chen

To this end, we present a data-centric, mixed-variable Bayesian Optimization framework that integrates data from literature, experiments, and simulations for knowledge discovery and computational materials design.

Elastic CRFs for Open-ontology Slot Filling

no code implementations4 Nov 2018 Yinpei Dai, Yichi Zhang, Zhijian Ou, Yanmeng Wang, Junlan Feng

Second, the one-hot encoding of slot labels ignores the semantic meanings and relations for slots, which are implicit in their natural language descriptions.

Slot Filling

Learning Sparse Structured Ensembles with SG-MCMC and Network Pruning

no code implementations ICLR 2018 Yichi Zhang, Zhijian Ou

An ensemble of neural networks is known to be more robust and accurate than an individual network, however usually with linearly-increased cost in both training and testing.

Language Modelling Network Pruning

Face Alignment Assisted by Head Pose Estimation

1 code implementation11 Jul 2015 Heng Yang, Wenxuan Mou, Yichi Zhang, Ioannis Patras, Hatice Gunes, Peter Robinson

In this paper we propose a supervised initialization scheme for cascaded face alignment based on explicit head pose estimation.

Face Alignment Head Pose Estimation

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