Search Results for author: Chao Shang

Found 14 papers, 6 papers with code

Diable: Efficient Dialogue State Tracking as Operations on Tables

1 code implementation26 May 2023 Pietro Lesci, Yoshinari Fujinuma, Momchil Hardalov, Chao Shang, Lluis Marquez

Sequence-to-sequence state-of-the-art systems for dialogue state tracking (DST) use the full dialogue history as input, represent the current state as a list with all the slots, and generate the entire state from scratch at each dialogue turn.

Dialogue State Tracking

Data-Driven Safe Controller Synthesis for Deterministic Systems: A Posteriori Method With Validation Tests

no code implementations3 Apr 2023 Yu Chen, Chao Shang, Xiaolin Huang, Xiang Yin

We first formulate the safety synthesis problem as a robust convex program (RCP) based on notion of control barrier function.

Incrementer: Transformer for Class-Incremental Semantic Segmentation With Knowledge Distillation Focusing on Old Class

no code implementations CVPR 2023 Chao Shang, Hongliang Li, Fanman Meng, Qingbo Wu, Heqian Qiu, Lanxiao Wang

Most existing methods are based on convolutional networks and prevent forgetting through knowledge distillation, which (1) need to add additional convolutional layers to predict new classes, and (2) ignore to distinguish different regions corresponding to old and new classes during knowledge distillation and roughly distill all the features, thus limiting the learning of new classes.

Class-Incremental Semantic Segmentation Knowledge Distillation

Dimension Reduction for Efficient Data-Enabled Predictive Control

no code implementations7 Nov 2022 Kaixiang Zhang, Yang Zheng, Chao Shang, Zhaojian Li

In this letter, we propose a simple yet effective singular value decomposition (SVD) based strategy to reduce the optimization problem dimension in data-enabled predictive control (DeePC).

Dimensionality Reduction

Improving Time Sensitivity for Question Answering over Temporal Knowledge Graphs

no code implementations ACL 2022 Chao Shang, Guangtao Wang, Peng Qi, Jing Huang

These questions often involve three time-related challenges that previous work fail to adequately address: 1) questions often do not specify exact timestamps of interest (e. g., "Obama" instead of 2000); 2) subtle lexical differences in time relations (e. g., "before" vs "after"); 3) off-the-shelf temporal KG embeddings that previous work builds on ignore the temporal order of timestamps, which is crucial for answering temporal-order related questions.

Knowledge Graphs Question Answering

Open Temporal Relation Extraction for Question Answering

no code implementations AKBC 2021 Chao Shang, Peng Qi, Guangtao Wang, Jing Huang, Youzheng Wu, BoWen Zhou

Understanding the temporal relations among events in text is a critical aspect of reading comprehension, which can be evaluated in the form of temporal question answering (TQA).

Question Answering Reading Comprehension +1

TAG: Gradient Attack on Transformer-based Language Models

1 code implementation Findings (EMNLP) 2021 Jieren Deng, Yijue Wang, Ji Li, Chao Shang, Cao Qin, Hang Liu, Sanguthevar Rajasekaran, Caiwen Ding

In this paper, as the first attempt, we formulate the gradient attack problem on the Transformer-based language models and propose a gradient attack algorithm, TAG, to reconstruct the local training data.

Federated Learning Cryptography and Security

Discrete Graph Structure Learning for Forecasting Multiple Time Series

1 code implementation ICLR 2021 Chao Shang, Jie Chen, Jinbo Bi

Exploration of the correlation and causation among the variables in a multivariate time series shows promise in enhancing the performance of a time series model.

Graph structure learning Time Series +1

A Posteriori Probabilistic Bounds of Convex Scenario Programs with Validation Tests

no code implementations27 Mar 2019 Chao Shang, Fengqi You

By synthesizing comprehensive information about support constraints and validation tests, improved risk evaluation can be achieved for randomized solutions in comparison with existing a posteriori bounds.

Decision Making Decision Making Under Uncertainty

End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion

1 code implementation11 Nov 2018 Chao Shang, Yun Tang, Jing Huang, Jinbo Bi, Xiaodong He, Bo-Wen Zhou

The recent graph convolutional network (GCN) provides another way of learning graph node embedding by successfully utilizing graph connectivity structure.

Knowledge Base Completion Knowledge Graph Embedding +2

Robust Model Predictive Control of Irrigation Systems with Active Uncertainty Learning and Data Analytics

no code implementations14 Oct 2018 Chao Shang, Wei-Han Chen, Abraham Duncan Stroock, Fengqi You

For evapotranspiration forecast error, the support vector clustering-based uncertainty set is adopted, which can be conveniently built from historical data.


Edge Attention-based Multi-Relational Graph Convolutional Networks

1 code implementation14 Feb 2018 Chao Shang, Qinqing Liu, Ko-Shin Chen, Jiangwen Sun, Jin Lu, Jin-Feng Yi, Jinbo Bi

The proposed GCN model, which we call edge attention-based multi-relational GCN (EAGCN), jointly learns attention weights and node features in graph convolution.

VIGAN: Missing View Imputation with Generative Adversarial Networks

1 code implementation22 Aug 2017 Chao Shang, Aaron Palmer, Jiangwen Sun, Ko-Shin Chen, Jin Lu, Jinbo Bi

Especially, when certain samples miss an entire view of data, it creates the missing view problem.

Denoising Imputation +1

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