Search Results for author: Shixia Liu

Found 22 papers, 2 papers with code

Foundation Models Meet Visualizations: Challenges and Opportunities

no code implementations9 Oct 2023 Weikai Yang, Mengchen Liu, Zheng Wang, Shixia Liu

Recent studies have indicated that foundation models, such as BERT and GPT, excel in adapting to a variety of downstream tasks.

Fairness

Visual Analytics For Machine Learning: A Data Perspective Survey

no code implementations15 Jul 2023 Junpeng Wang, Shixia Liu, Wei zhang

The past decade has witnessed a plethora of works that leverage the power of visualization (VIS) to interpret machine learning (ML) models.

Visual Analysis of Neural Architecture Spaces for Summarizing Design Principles

no code implementations20 Aug 2022 Jun Yuan, Mengchen Liu, Fengyuan Tian, Shixia Liu

To ease this process, we develop ArchExplorer, a visual analysis method for understanding a neural architecture space and summarizing design principles.

A Unified Understanding of Deep NLP Models for Text Classification

no code implementations19 Jun 2022 Zhen Li, Xiting Wang, Weikai Yang, Jing Wu, Zhengyan Zhang, Zhiyuan Liu, Maosong Sun, HUI ZHANG, Shixia Liu

The rapid development of deep natural language processing (NLP) models for text classification has led to an urgent need for a unified understanding of these models proposed individually.

text-classification Text Classification

Diagnosing Ensemble Few-Shot Classifiers

no code implementations9 Jun 2022 Weikai Yang, Xi Ye, Xingxing Zhang, Lanxi Xiao, Jiazhi Xia, Zhongyuan Wang, Jun Zhu, Hanspeter Pfister, Shixia Liu

The base learners and labeled samples (shots) in an ensemble few-shot classifier greatly affect the model performance.

Real-Time Visual Analysis of High-Volume Social Media Posts

no code implementations6 Aug 2021 Johannes Knittel, Steffen Koch, Tan Tang, Wei Chen, Yingcai Wu, Shixia Liu, Thomas Ertl

In contrast to previous work, our system also works with non-geolocated posts and avoids extensive preprocessing such as detecting events.

Clustering Vocal Bursts Intensity Prediction

Interactive Steering of Hierarchical Clustering

no code implementations21 Sep 2020 Weikai Yang, Xiting Wang, Jie Lu, Wenwen Dou, Shixia Liu

The novelty of our approach includes 1) automatically constructing constraints for hierarchical clustering using knowledge (knowledge-driven) and intrinsic data distribution (data-driven), and 2) enabling the interactive steering of clustering through a visual interface (user-driven).

Clustering

Visual Analysis of Discrimination in Machine Learning

no code implementations30 Jul 2020 Qianwen Wang, Zhenhua Xu, Zhutian Chen, Yong Wang, Shixia Liu, Huamin Qu

The growing use of automated decision-making in critical applications, such as crime prediction and college admission, has raised questions about fairness in machine learning.

BIG-bench Machine Learning Crime Prediction +2

Diagnosing Concept Drift with Visual Analytics

no code implementations28 Jul 2020 Weikai Yang, Zhen Li, Mengchen Liu, Yafeng Lu, Kelei Cao, Ross Maciejewski, Shixia Liu

Concept drift is a phenomenon in which the distribution of a data stream changes over time in unforeseen ways, causing prediction models built on historical data to become inaccurate.

text-classification Text Classification

OoDAnalyzer: Interactive Analysis of Out-of-Distribution Samples

no code implementations8 Feb 2020 Changjian Chen, Jun Yuan, Yafeng Lu, Yang Liu, Hang Su, Songtao Yuan, Shixia Liu

To better analyze and understand the OoD samples in context, we have developed a novel kNN-based grid layout algorithm motivated by Hall's theorem.

Out of Distribution (OOD) Detection Test

Analyzing the Noise Robustness of Deep Neural Networks

no code implementations26 Jan 2020 Kelei Cao, Mengchen Liu, Hang Su, Jing Wu, Jun Zhu, Shixia Liu

The key is to compare and analyze the datapaths of both the adversarial and normal examples.

Adversarial Attack

Recent Research Advances on Interactive Machine Learning

no code implementations12 Nov 2018 Liu Jiang, Shixia Liu, Changjian Chen

Interactive Machine Learning (IML) is an iterative learning process that tightly couples a human with a machine learner, which is widely used by researchers and practitioners to effectively solve a wide variety of real-world application problems.

BIG-bench Machine Learning

Analyzing the Noise Robustness of Deep Neural Networks

no code implementations9 Oct 2018 Mengchen Liu, Shixia Liu, Hang Su, Kelei Cao, Jun Zhu

Deep neural networks (DNNs) are vulnerable to maliciously generated adversarial examples.

Visual Analytics for Explainable Deep Learning

no code implementations7 Apr 2018 Jaegul Choo, Shixia Liu

Recently, deep learning has been advancing the state of the art in artificial intelligence to a new level, and humans rely on artificial intelligence techniques more than ever.

BIG-bench Machine Learning Decision Making

Scalable Inference for Nested Chinese Restaurant Process Topic Models

no code implementations23 Feb 2017 Jianfei Chen, Jun Zhu, Jie Lu, Shixia Liu

Finally, we propose an efficient distributed implementation of PCGS through vectorization, pre-processing, and a careful design of the concurrent data structures and communication strategy.

Topic Models Variational Inference

Towards Better Analysis of Machine Learning Models: A Visual Analytics Perspective

no code implementations4 Feb 2017 Shixia Liu, Xiting Wang, Mengchen Liu, Jun Zhu

Interactive model analysis, the process of understanding, diagnosing, and refining a machine learning model with the help of interactive visualization, is very important for users to efficiently solve real-world artificial intelligence and data mining problems.

BIG-bench Machine Learning

Towards Better Analysis of Deep Convolutional Neural Networks

no code implementations24 Apr 2016 Mengchen Liu, Jiaxin Shi, Zhen Li, Chongxuan Li, Jun Zhu, Shixia Liu

Deep convolutional neural networks (CNNs) have achieved breakthrough performance in many pattern recognition tasks such as image classification.

Image Classification

Scaling up Dynamic Topic Models

1 code implementation19 Feb 2016 Arnab Bhadury, Jianfei Chen, Jun Zhu, Shixia Liu

Dynamic topic models (DTMs) are very effective in discovering topics and capturing their evolution trends in time series data.

Time Series Time Series Analysis +1

Online Visual Analytics of Text Streams

1 code implementation13 Dec 2015 Shixia Liu, Jialun Yin, Xiting Wang, Weiwei Cui, Kelei Cao, Jian Pei

To this end, we learn a set of streaming tree cuts from topic trees based on user-selected focus nodes.

Tracking Idea Flows between Social Groups

no code implementations13 Dec 2015 Yangxin Zhong, Shixia Liu, Xiting Wang, Jiannan Xiao, Yangqiu Song

To facilitate users in analyzing the flow, we present a method to model the flow behaviors that aims at identifying the lead-lag relationships between word clusters of different user groups.

Clustering Dynamic Time Warping

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