Search Results for author: Yingfei Wang

Found 15 papers, 1 papers with code

DDI-CoCo: A Dataset For Understanding The Effect Of Color Contrast In Machine-Assisted Skin Disease Detection

1 code implementation24 Jan 2024 Ming-Chang Chiu, Yingfei Wang, Yen-Ju Kuo, Pin-Yu Chen

We take another angle to investigate color contrast's impact, beyond skin tones, on malignancy detection in skin disease datasets: We hypothesize that in addition to skin tones, the color difference between the lesion area and skin also plays a role in malignancy detection performance of dermatology AI models.

Image Classification

CSDR-BERT: a pre-trained scientific dataset match model for Chinese Scientific Dataset Retrieval

no code implementations30 Jan 2023 Xintao Chu, Jianping Liu, Jian Wang, XiaoFeng Wang, Yingfei Wang, Meng Wang, Xunxun Gu

As the number of open and shared scientific datasets on the Internet increases under the open science movement, efficiently retrieving these datasets is a crucial task in information retrieval (IR) research.

Information Retrieval Retrieval +2

FE-TCM: Filter-Enhanced Transformer Click Model for Web Search

no code implementations19 Jan 2023 Yingfei Wang, Jianping Liu, Jian Wang, XiaoFeng Wang, Meng Wang, Xintao Chu

In this paper, We use Transformer as the backbone network of feature extraction, add filter layer innovatively, and propose a new Filter-Enhanced Transformer Click Model (FE-TCM) for web search.

On Human Visual Contrast Sensitivity and Machine Vision Robustness: A Comparative Study

no code implementations16 Dec 2022 Ming-Chang Chiu, Yingfei Wang, Derrick Eui Gyu Kim, Pin-Yu Chen, Xuezhe Ma

It is well established in neuroscience that color vision plays an essential part in the human visual perception system.

Data Augmentation

No-Regret Learning in Two-Echelon Supply Chain with Unknown Demand Distribution

no code implementations23 Oct 2022 Mengxiao Zhang, Shi Chen, Haipeng Luo, Yingfei Wang

Supply chain management (SCM) has been recognized as an important discipline with applications to many industries, where the two-echelon stochastic inventory model, involving one downstream retailer and one upstream supplier, plays a fundamental role for developing firms' SCM strategies.


Whom to Test? Active Sampling Strategies for Managing COVID-19

no code implementations25 Dec 2020 Yingfei Wang, Inbal Yahav, Balaji Padmanabhan

This paper presents methods to choose individuals to test for infection during a pandemic such as COVID-19, characterized by high contagion and presence of asymptomatic carriers.

Active Learning Test

Spoiled for Choice? Personalized Recommendation for Healthcare Decisions: A Multi-Armed Bandit Approach

no code implementations13 Sep 2020 Tongxin Zhou, Yingfei Wang, Lu, Yan, Yong Tan

In this study, we take a design-science perspective to propose a recommendation framework that helps users to select healthcare interventions.

Feature Engineering Management +1

Reinforcement Learning for Dynamic Bidding in Truckload Markets: an Application to Large-Scale Fleet Management with Advance Commitments

no code implementations25 Feb 2018 Yingfei Wang, Juliana Martins Do Nascimento, Warren Powell

Truckload brokerages, a $100 billion/year industry in the U. S., plays the critical role of matching shippers with carriers, often to move loads several days into the future.


MOLTE: a Modular Optimal Learning Testing Environment

no code implementations13 Sep 2017 Yingfei Wang, Warren Powell

The Matlab-based simulator allows the comparison of a number of learning policies (represented as a series of . m modules) in the context of a wide range of problems (each represented in its own . m module) which makes it easy to add new algorithms and new test problems.

Experimental Design Test

An optimal learning method for developing personalized treatment regimes

no code implementations6 Jul 2016 Yingfei Wang, Warren Powell

A treatment regime is a function that maps individual patient information to a recommended treatment, hence explicitly incorporating the heterogeneity in need for treatment across individuals.

Clustering Multi-Armed Bandits

Finite-time Analysis for the Knowledge-Gradient Policy

no code implementations15 Jun 2016 Yingfei Wang, Warren Powell

We consider sequential decision problems in which we adaptively choose one of finitely many alternatives and observe a stochastic reward.

Functional Frank-Wolfe Boosting for General Loss Functions

no code implementations9 Oct 2015 Chu Wang, Yingfei Wang, Weinan E, Robert Schapire

Yet, as the number of base hypotheses becomes larger, boosting can lead to a deterioration of test performance.

Binary Classification General Classification +2

The Knowledge Gradient with Logistic Belief Models for Binary Classification

no code implementations8 Oct 2015 Yingfei Wang, Chu Wang, Warren Powell

We consider sequential decision making problems for binary classification scenario in which the learner takes an active role in repeatedly selecting samples from the action pool and receives the binary label of the selected alternatives.

Binary Classification Classification +2

A Knowledge Gradient Policy for Sequencing Experiments to Identify the Structure of RNA Molecules Using a Sparse Additive Belief Model

no code implementations6 Aug 2015 Yan Li, Kristofer G. Reyes, Jorge Vazquez-Anderson, Yingfei Wang, Lydia M. Contreras, Warren B. Powell

We present a sparse knowledge gradient (SpKG) algorithm for adaptively selecting the targeted regions within a large RNA molecule to identify which regions are most amenable to interactions with other molecules.


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