Search Results for author: Linbo Wang

Found 8 papers, 3 papers with code

In Search of Robust Measures of Generalization

1 code implementation NeurIPS 2020 Gintare Karolina Dziugaite, Alexandre Drouin, Brady Neal, Nitarshan Rajkumar, Ethan Caballero, Linbo Wang, Ioannis Mitliagkas, Daniel M. Roy

A large volume of work aims to close this gap, primarily by developing bounds on generalization error, optimization error, and excess risk.

Generalization Bounds

Scribble-Supervised RGB-T Salient Object Detection

1 code implementation17 Mar 2023 Zhengyi Liu, Xiaoshen Huang, Guanghui Zhang, Xianyong Fang, Linbo Wang, Bin Tang

To further polish the expanded labels, we propose a prediction module to alleviate the sharpness of boundary.

Object object-detection +3

Adaptively Exploiting d-Separators with Causal Bandits

1 code implementation10 Feb 2022 Blair Bilodeau, Linbo Wang, Daniel M. Roy

In this work, we formalize and study this notion of adaptivity, and provide a novel algorithm that simultaneously achieves (a) optimal regret when a d-separator is observed, improving on classical minimax algorithms, and (b) significantly smaller regret than recent causal bandit algorithms when the observed variables are not a d-separator.

Viewpoint Selection for Photographing Architectures

no code implementations6 Mar 2017 Jingwu He, Linbo Wang, Wenzhe Zhou, Hongjie Zhang, Xiufen Cui, Yanwen Guo

Unlike previous efforts devoted to photo quality assessment which mainly rely on 2D image features, we show in this paper combining 2D image features extracted from images with 3D geometric features computed on the 3D models can result in more reliable evaluation of viewpoint quality.

Clustering

Multi-cause causal inference with unmeasured confounding and binary outcome

no code implementations31 Jul 2019 Dehan Kong, Shu Yang, Linbo Wang

Unobserved confounding presents a major threat to causal inference in observational studies.

Methodology

The Promises of Parallel Outcomes

no code implementations10 Dec 2020 Ying Zhou, Dehan Kong, Linbo Wang

In contrast to existing proposals in the literature, the roles of multiple outcomes in our key identification assumption are symmetric, hence the name parallel outcomes.

Causal Inference Methodology

Causal Inference on Distribution Functions

no code implementations5 Jan 2021 Zhenhua Lin, Dehan Kong, Linbo Wang

Understanding causal relationships is one of the most important goals of modern science.

Causal Inference Methodology

Local Consensus Enhanced Siamese Network with Reciprocal Loss for Two-view Correspondence Learning

no code implementations6 Aug 2023 Linbo Wang, Jing Wu, Xianyong Fang, Zhengyi Liu, Chenjie Cao, Yanwei Fu

First, we propose a Local Feature Consensus (LFC) plugin block to augment the features of existing models.

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