Search Results for author: Tian Gao

Found 30 papers, 9 papers with code

Timeline Summarization based on Event Graph Compression via Time-Aware Optimal Transport

1 code implementation EMNLP 2021 Manling Li, Tengfei Ma, Mo Yu, Lingfei Wu, Tian Gao, Heng Ji, Kathleen McKeown

Timeline Summarization identifies major events from a news collection and describes them following temporal order, with key dates tagged.

Timeline Summarization

Nonlocal Kernel Network (NKN): a Stable and Resolution-Independent Deep Neural Network

no code implementations6 Jan 2022 Huaiqian You, Yue Yu, Marta D'Elia, Tian Gao, Stewart Silling

In this work, we propose a novel nonlocal neural operator, which we refer to as nonlocal kernel network (NKN), that is resolution independent, characterized by deep neural networks, and capable of handling a variety of tasks such as learning governing equations and classifying images.

Image Classification

Onsite Non-Line-of-Sight Imaging via Online Calibrations

no code implementations29 Dec 2021 Zhengqing Pan, Ruiqian Li, Tian Gao, Zi Wang, Ping Liu, Siyuan Shen, Tao Wu, Jingyi Yu, Shiying Li

There has been an increasing interest in deploying non-line-of-sight (NLOS) imaging systems for recovering objects behind an obstacle.

Logical Credal Networks

no code implementations25 Sep 2021 Haifeng Qian, Radu Marinescu, Alexander Gray, Debarun Bhattacharjya, Francisco Barahona, Tian Gao, Ryan Riegel, Pravinda Sahu

This paper introduces Logical Credal Networks, an expressive probabilistic logic that generalizes many prior models that combine logic and probability.

Image Feature Information Extraction for Interest Point Detection: A Comprehensive Review

no code implementations15 Jun 2021 Junfeng Jing, Tian Gao, Weichuan Zhang, Yongsheng Gao, Changming Sun

The existing popular datasets and evaluation standards are provided and the performances for eighteen state-of-the-art approaches are evaluated and discussed.

Interest Point Detection

DAGs with No Curl: An Efficient DAG Structure Learning Approach

1 code implementation14 Jun 2021 Yue Yu, Tian Gao, Naiyu Yin, Qiang Ji

To further improve efficiency, we propose a novel learning framework to model and learn the weighted adjacency matrices in the DAG space directly.

Integer Programming for Causal Structure Learning in the Presence of Latent Variables

1 code implementation5 Feb 2021 Rui Chen, Sanjeeb Dash, Tian Gao

The problem of finding an ancestral acyclic directed mixed graph (ADMG) that represents the causal relationships between a set of variables is an important area of research on causal inference.

Causal Inference

Non-line-of-Sight Imaging via Neural Transient Fields

1 code implementation2 Jan 2021 Siyuan Shen, Zi Wang, Ping Liu, Zhengqing Pan, Ruiqian Li, Tian Gao, Shiying Li, Jingyi Yu

We present a neural modeling framework for Non-Line-of-Sight (NLOS) imaging.

DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks

1 code implementation NeurIPS 2020 Dennis Wei, Tian Gao, Yue Yu

This paper re-examines a continuous optimization framework dubbed NOTEARS for learning Bayesian networks.

MCMH: Learning Multi-Chain Multi-Hop Rules for Knowledge Graph Reasoning

no code implementations Findings of the Association for Computational Linguistics 2020 Lu Zhang, Mo Yu, Tian Gao, Yue Yu

Multi-hop reasoning approaches over knowledge graphs infer a missing relationship between entities with a multi-hop rule, which corresponds to a chain of relationships.

Knowledge Graphs

Type-augmented Relation Prediction in Knowledge Graphs

no code implementations16 Sep 2020 Zijun Cui, Pavan Kapanipathi, Kartik Talamadupula, Tian Gao, Qiang Ji

Knowledge graph completion (also known as relation prediction) is the task of inferring missing facts given existing ones.

Knowledge Graph Completion

"And the Winner Is...": Dynamic Lotteries for Multi-group Fairness-Aware Recommendation

no code implementations5 Sep 2020 Nasim Sonboli, Robin Burke, Nicholas Mattei, Farzad Eskandanian, Tian Gao

As recommender systems are being designed and deployed for an increasing number of socially-consequential applications, it has become important to consider what properties of fairness these systems exhibit.

Fairness Recommendation Systems

A Multi-Channel Neural Graphical Event Model with Negative Evidence

no code implementations21 Feb 2020 Tian Gao, Dharmashankar Subramanian, Karthikeyan Shanmugam, Debarun Bhattacharjya, Nicholas Mattei

Event datasets are sequences of events of various types occurring irregularly over the time-line, and they are increasingly prevalent in numerous domains.

Do Multi-hop Readers Dream of Reasoning Chains?

1 code implementation WS 2019 Haoyu Wang, Mo Yu, Xiaoxiao Guo, Rajarshi Das, Wenhan Xiong, Tian Gao

General Question Answering (QA) systems over texts require the multi-hop reasoning capability, i. e. the ability to reason with information collected from multiple passages to derive the answer.

Question Answering

Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering

no code implementations WS 2019 Ameya Godbole, Dilip Kavarthapu, Rajarshi Das, Zhiyu Gong, Abhishek Singhal, Hamed Zamani, Mo Yu, Tian Gao, Xiaoxiao Guo, Manzil Zaheer, Andrew McCallum

Multi-hop question answering (QA) requires an information retrieval (IR) system that can find \emph{multiple} supporting evidence needed to answer the question, making the retrieval process very challenging.

Information Retrieval Multi-hop Question Answering +1

Characterization of Overlap in Observational Studies

1 code implementation9 Jul 2019 Michael Oberst, Fredrik D. Johansson, Dennis Wei, Tian Gao, Gabriel Brat, David Sontag, Kush R. Varshney

Overlap between treatment groups is required for non-parametric estimation of causal effects.

Generalized Linear Rule Models

no code implementations5 Jun 2019 Dennis Wei, Sanjeeb Dash, Tian Gao, Oktay Günlük

Column generation is used to optimize over an exponentially large space of rules without pre-generating a large subset of candidates or greedily boosting rules one by one.

General Classification

DAG-GNN: DAG Structure Learning with Graph Neural Networks

3 code implementations22 Apr 2019 Yue Yu, Jie Chen, Tian Gao, Mo Yu

Learning a faithful directed acyclic graph (DAG) from samples of a joint distribution is a challenging combinatorial problem, owing to the intractable search space superexponential in the number of graph nodes.

A Sequential Set Generation Method for Predicting Set-Valued Outputs

no code implementations12 Mar 2019 Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock

Though SSG is sequential in nature, it does not penalize the ordering of the appearance of the set elements and can be applied to a variety of set output problems, such as a set of classification labels or sequences.

General Classification Multi-Label Classification

Proximal Graphical Event Models

no code implementations NeurIPS 2018 Debarun Bhattacharjya, Dharmashankar Subramanian, Tian Gao

Event datasets include events that occur irregularly over the timeline and are prevalent in numerous domains.

Identifying the Discourse Function of News Article Paragraphs

no code implementations COLING 2018 W. Victor Yarlott, Cristina Cornelio, Tian Gao, Mark Finlayson

We test two hypotheses: first, that people can reliably annotate news articles with van Dijk{'}s theory; second, that we can reliably predict these labels using machine learning.

Parallel Bayesian Network Structure Learning

no code implementations ICML 2018 Tian Gao, Dennis Wei

Recent advances in Bayesian Network (BN) structure learning have focused on local-to-global learning, where the graph structure is learned via one local subgraph at a time.

e-QRAQ: A Multi-turn Reasoning Dataset and Simulator with Explanations

no code implementations5 Aug 2017 Clemens Rosenbaum, Tian Gao, Tim Klinger

In this paper we present a new dataset and user simulator e-QRAQ (explainable Query, Reason, and Answer Question) which tests an Agent's ability to read an ambiguous text; ask questions until it can answer a challenge question; and explain the reasoning behind its questions and answer.

Local-to-Global Bayesian Network Structure Learning

no code implementations ICML 2017 Tian Gao, Kshitij Fadnis, Murray Campbell

We introduce a new local-to-global structure learning algorithm, called graph growing structure learning (GGSL), to learn Bayesian network (BN) structures.

Local Causal Discovery of Direct Causes and Effects

no code implementations NeurIPS 2015 Tian Gao, Qiang Ji

We focus on the discovery and identification of direct causes and effects of a target variable in a causal network.

Causal Discovery

Structured Feature Selection

no code implementations ICCV 2015 Tian Gao, Ziheng Wang, Qiang Ji

Then we apply structured feature selection to two applications: 1) We introduce a new method that enables STMB to scale up and show the competitive performance of our algorithms on large-scale image classification tasks.

Dimensionality Reduction General Classification +1

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