Search Results for author: Bo Pang

Found 41 papers, 17 papers with code

CGNN: Traffic Classification with Graph Neural Network

no code implementations19 Oct 2021 Bo Pang, Yongquan Fu, Siyuan Ren, Ye Wang, Qing Liao, Yan Jia

Extensive evaluation over real-world traffic data sets, including normal, encrypted and malicious labels, show that, CGNN improves the prediction accuracy by 23\% to 29\% for application classification, by 2\% to 37\% for malicious traffic classification, and reaches the same accuracy level for encrypted traffic classification.

Classification Traffic Classification

Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification

1 code implementation26 Aug 2021 Bo Pang, Ying Nian Wu

The energy term of the prior model couples a continuous latent vector and a symbolic one-hot vector, so that discrete category can be inferred from the observed example based on the continuous latent vector.

Text Generation

Robust Transfer Learning with Pretrained Language Models through Adapters

no code implementations ACL 2021 Wenjuan Han, Bo Pang, YingNian Wu

Transfer learning with large pretrained transformer-based language models like BERT has become a dominating approach for most NLP tasks.

Adversarial Attack Transfer Learning

Human Pose Regression with Residual Log-likelihood Estimation

2 code implementations ICCV 2021 Jiefeng Li, Siyuan Bian, Ailing Zeng, Can Wang, Bo Pang, Wentao Liu, Cewu Lu

In light of this, we propose a novel regression paradigm with Residual Log-likelihood Estimation (RLE) to capture the underlying output distribution.

Multi-Person Pose Estimation

Reinforcement Learning for Adaptive Optimal Stationary Control of Linear Stochastic Systems

no code implementations16 Jul 2021 Bo Pang, Zhong-Ping Jiang

This paper studies the adaptive optimal stationary control of continuous-time linear stochastic systems with both additive and multiplicative noises, using reinforcement learning techniques.

Generative Text Modeling through Short Run Inference

1 code implementation EACL 2021 Bo Pang, Erik Nijkamp, Tian Han, Ying Nian Wu

It is initialized from the prior distribution of the latent variable and then runs a small number (e. g., 20) of Langevin dynamics steps guided by its posterior distribution.

Language Modelling Latent Variable Models

Trajectory Prediction with Latent Belief Energy-Based Model

1 code implementation CVPR 2021 Bo Pang, Tianyang Zhao, Xu Xie, Ying Nian Wu

Sampling from or optimizing the learned LB-EBM yields a belief vector which is used to make a path plan, which then in turn helps to predict a long-range trajectory.

Self-Driving Cars Trajectory Prediction

PGT: A Progressive Method for Training Models on Long Videos

1 code implementation CVPR 2021 Bo Pang, Gao Peng, Yizhuo Li, Cewu Lu

This progressive training (PGT) method is able to train long videos end-to-end with limited resources and ensures the effective transmission of information.

TDAF: Top-Down Attention Framework for Vision Tasks

no code implementations14 Dec 2020 Bo Pang, Yizhuo Li, Jiefeng Li, Muchen Li, Hanwen Cao, Cewu Lu

Such spatial and attention features are nested deeply, therefore, the proposed framework works in a mixed top-down and bottom-up manner.

Action Recognition Object Detection +1

Understanding Guided Image Captioning Performance across Domains

1 code implementation4 Dec 2020 Edwin G. Ng, Bo Pang, Piyush Sharma, Radu Soricut

Image captioning models generally lack the capability to take into account user interest, and usually default to global descriptions that try to balance readability, informativeness, and information overload.

Image Captioning Visual Question Answering

Multimodal Pretraining for Dense Video Captioning

1 code implementation Asian Chapter of the Association for Computational Linguistics 2020 Gabriel Huang, Bo Pang, Zhenhai Zhu, Clara Rivera, Radu Soricut

First, we construct and release a new dense video captioning dataset, Video Timeline Tags (ViTT), featuring a variety of instructional videos together with time-stamped annotations.

 Ranked #1 on Dense Video Captioning on YouCook2 (ROUGE-L metric, using extra training data)

Dense Video Captioning

Learning Latent Space Energy-Based Prior Model for Molecule Generation

no code implementations19 Oct 2020 Bo Pang, Tian Han, Ying Nian Wu

Deep generative models have recently been applied to molecule design.

Semi-supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling

no code implementations19 Oct 2020 Bo Pang, Erik Nijkamp, Jiali Cui, Tian Han, Ying Nian Wu

This paper proposes a latent space energy-based prior model for semi-supervised learning.

Robust Reinforcement Learning: A Case Study in Linear Quadratic Regulation

no code implementations25 Aug 2020 Bo Pang, Zhong-Ping Jiang

This paper studies the robustness of reinforcement learning algorithms to errors in the learning process.

ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation

1 code implementation12 Aug 2020 Hanwen Cao, Yongyi Lu, Cewu Lu, Bo Pang, Gongshen Liu, Alan Yuille

In this paper, we further improve spatio-temporal point cloud feature learning with a flexible module called ASAP considering both attention and structure information across frames, which we find as two important factors for successful segmentation in dynamic point clouds.

Learning Latent Space Energy-Based Prior Model

1 code implementation NeurIPS 2020 Bo Pang, Tian Han, Erik Nijkamp, Song-Chun Zhu, Ying Nian Wu

Due to the low dimensionality of the latent space and the expressiveness of the top-down network, a simple EBM in latent space can capture regularities in the data effectively, and MCMC sampling in latent space is efficient and mixes well.

Anomaly Detection Text Generation

Learning Energy-based Model with Flow-based Backbone by Neural Transport MCMC

no code implementations12 Jun 2020 Erik Nijkamp, Ruiqi Gao, Pavel Sountsov, Srinivas Vasudevan, Bo Pang, Song-Chun Zhu, Ying Nian Wu

We show that the model has a particularly simple form in the space of the latent variables of the flow-based model, and MCMC sampling of the EBM in the latent space, which is a simple special case of neural transport MCMC, mixes well and traverses modes in the data space.

TubeTK: Adopting Tubes to Track Multi-Object in a One-Step Training Model

1 code implementation CVPR 2020 Bo Pang, Yizhuo Li, Yifan Zhang, Muchen Li, Cewu Lu

As deep learning brings excellent performances to object detection algorithms, Tracking by Detection (TBD) has become the mainstream tracking framework.

Multi-Object Tracking Object Detection

Joint Training of Variational Auto-Encoder and Latent Energy-Based Model

no code implementations CVPR 2020 Tian Han, Erik Nijkamp, Linqi Zhou, Bo Pang, Song-Chun Zhu, Ying Nian Wu

This paper proposes a joint training method to learn both the variational auto-encoder (VAE) and the latent energy-based model (EBM).

Anomaly Detection

Single Image Deraining via Scale-space Invariant Attention Neural Network

no code implementations9 Jun 2020 Bo Pang, Deming Zhai, Junjun Jiang, Xian-Ming Liu

Image enhancement from degradation of rainy artifacts plays a critical role in outdoor visual computing systems.

Image Enhancement Single Image Deraining

Robust Policy Iteration for Continuous-time Linear Quadratic Regulation

no code implementations19 May 2020 Bo Pang, Tao Bian, Zhong-Ping Jiang

This paper studies the robustness of policy iteration in the context of continuous-time infinite-horizon linear quadratic regulation (LQR) problem.

Systems and Control Numerical Analysis Systems and Control Numerical Analysis Optimization and Control

Beyond Instructional Videos: Probing for More Diverse Visual-Textual Grounding on YouTube

1 code implementation EMNLP 2020 Jack Hessel, Zhenhai Zhu, Bo Pang, Radu Soricut

Pretraining from unlabelled web videos has quickly become the de-facto means of achieving high performance on many video understanding tasks.

automatic-speech-recognition Speech Recognition +1

Asynchronous Interaction Aggregation for Action Detection

2 code implementations ECCV 2020 Jiajun Tang, Jin Xia, Xinzhi Mu, Bo Pang, Cewu Lu

We propose the Asynchronous Interaction Aggregation network (AIA) that leverages different interactions to boost action detection.

Action Detection

Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference

no code implementations ECCV 2020 Erik Nijkamp, Bo Pang, Tian Han, Linqi Zhou, Song-Chun Zhu, Ying Nian Wu

Learning such a generative model requires inferring the latent variables for each training example based on the posterior distribution of these latent variables.

A Case Study on Combining ASR and Visual Features for Generating Instructional Video Captions

no code implementations CONLL 2019 Jack Hessel, Bo Pang, Zhenhai Zhu, Radu Soricut

Instructional videos get high-traffic on video sharing platforms, and prior work suggests that providing time-stamped, subtask annotations (e. g., "heat the oil in the pan") improves user experiences.

automatic-speech-recognition Speech Recognition

Neural-based Chinese Idiom Recommendation for Enhancing Elegance in Essay Writing

no code implementations ACL 2019 Yuanchao Liu, Bo Pang, Bingquan Liu

Although the proper use of idioms can enhance the elegance of writing, the active use of various expressions is a challenge because remembering idioms is difficult.

Machine Translation Translation

SParC: Cross-Domain Semantic Parsing in Context

5 code implementations ACL 2019 Tao Yu, Rui Zhang, Michihiro Yasunaga, Yi Chern Tan, Xi Victoria Lin, Suyi Li, Heyang Er, Irene Li, Bo Pang, Tao Chen, Emily Ji, Shreya Dixit, David Proctor, Sungrok Shim, Jonathan Kraft, Vincent Zhang, Caiming Xiong, Richard Socher, Dragomir Radev

The best model obtains an exact match accuracy of 20. 2% over all questions and less than10% over all interaction sequences, indicating that the cross-domain setting and the con-textual phenomena of the dataset present significant challenges for future research.

Semantic Parsing Text-To-Sql

Deep RNN Framework for Visual Sequential Applications

1 code implementation CVPR 2019 Bo Pang, Kaiwen Zha, Hanwen Cao, Chen Shi, Cewu Lu

There are mainly two novel designs in our deep RNN framework: one is a new RNN module called Context Bridge Module (CBM) which splits the information flowing along the sequence (temporal direction) and along depth (spatial representation direction), making it easier to train when building deep by balancing these two directions; the other is the Overlap Coherence Training Scheme that reduces the training complexity for long visual sequential tasks on account of the limitation of computing resources.

Future prediction SSIM +1

Human Action Adverb Recognition: ADHA Dataset and A Three-Stream Hybrid Model

no code implementations4 Feb 2018 Bo Pang, Kaiwen Zha, Cewu Lu

We introduce the first benchmark for a new problem --- recognizing human action adverbs (HAA): "Adverbs Describing Human Actions" (ADHA).

Action Recognition Image Captioning

Thumbs up? Sentiment Classification using Machine Learning Techniques

4 code implementations28 May 2002 Bo Pang, Lillian Lee, Shivakumar Vaithyanathan

We consider the problem of classifying documents not by topic, but by overall sentiment, e. g., determining whether a review is positive or negative.

Classification General Classification +1

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