b'Han Liu'

research

∙ 01/26/2022

A Multi-rater Comparative Study of Automatic Target Localization Methods for Epilepsy Deep Brain Stimulation Procedures

Epilepsy is the fourth most common neurological disorder and affects peo...

Han Liu, et al. ∙

research

∙ 01/25/2022

Unsupervised Domain Adaptation for Vestibular Schwannoma and Cochlea Segmentation via Semi-supervised Learning and Label Fusion

Automatic methods to segment the vestibular schwannoma (VS) tumors and t...

Han Liu, et al. ∙

research

∙ 01/08/2022

CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwnannoma and Cochlea Segmentation

Domain Adaptation (DA) has recently raised strong interests in the medic...

Reuben Dorent, et al. ∙

research

∙ 12/01/2021

Trusted And Confidential Program Analysis

We develop the concept of Trusted and Confidential Program Analysis (TCP...

Han Liu, et al. ∙

research

∙ 11/03/2021

A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applications

Quantifying the uncertainty of supervised learning models plays an impor...

Xinlei Zhou, et al. ∙

research

∙ 10/26/2021

An Explicit-Joint and Supervised-Contrastive Learning Framework for Few-Shot Intent Classification and Slot Filling

Intent classification (IC) and slot filling (SF) are critical building b...

Han Liu, et al. ∙

research

∙ 09/13/2021

Cross-Modality Domain Adaptation for Vestibular Schwannoma and Cochlea Segmentation

Automatic methods to segment the vestibular schwannoma (VS) tumors and t...

Han Liu, et al. ∙

research

∙ 08/03/2021

Optimal Covariate Balancing Conditions in Propensity Score Estimation

Inverse probability of treatment weighting (IPTW) is a popular method fo...

Jianqing Fan, et al. ∙

research

∙ 06/25/2021

CLOAK: A Framework For Development of Confidential Blockchain Smart Contracts

In recent years, as blockchain adoption has been expanding across a wide...

Qian Ren, et al. ∙

research

∙ 06/08/2021

Review Polarity-wise Recommender

Utilizing review information to enhance recommendation, the de facto rev...

Han Liu, et al. ∙

research

∙ 05/26/2021

Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading

In this paper, we introduce an event-driven trading strategy that predic...

Zhihan Zhou, et al. ∙

research

∙ 03/04/2021

BLOCKEYE: Hunting For DeFi Attacks on Blockchain

Decentralized finance, i.e., DeFi, has become the most popular type of a...

Bin Wang, et al. ∙

research

∙ 02/04/2021

Converse, Focus and Guess – Towards Multi-Document Driven Dialogue

We propose a novel task, Multi-Document Driven Dialogue (MD3), in which ...

Han Liu, et al. ∙

research

∙ 01/13/2021

Understanding the Effect of Out-of-distribution Examples and Interactive Explanations on Human-AI Decision Making

Although AI holds promise for improving human decision making in societa...

Han Liu, et al. ∙

research

∙ 12/11/2020

Morphology Matters: A Multilingual Language Modeling Analysis

Prior studies in multilingual language modeling (e.g., Cotterell et al.,...

Hyunji Hayley Park, et al. ∙

research

∙ 11/03/2020

Uncertainty Estimation in Medical Image Localization: Towards Robust Anterior Thalamus Targeting for Deep Brain Stimulation

Atlas-based methods are the standard approaches for automatic targeting ...

Han Liu, et al. ∙

research

∙ 08/15/2020

Label-Wise Document Pre-Training for Multi-Label Text Classification

A major challenge of multi-label text classification (MLTC) is to stimul...

Han Liu, et al. ∙

research

∙ 06/27/2020

The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R

This paper describes an R package named flare, which implements a family...

Xingguo Li, et al. ∙

research

∙ 06/26/2020

The huge Package for High-dimensional Undirected Graph Estimation in R

We describe an R package named huge which provides easy-to-use functions...

Tuo Zhao, et al. ∙

research

∙ 06/10/2020

Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network

In this paper, we explore the slot tagging with only a few labeled suppo...

Yutai Hou, et al. ∙

research

∙ 05/16/2020

A Deep Learning based Wearable Healthcare IoT Device for AI-enabled Hearing Assistance Automation

With the recent booming of artificial intelligence (AI), particularly de...

Fraser Young, et al. ∙

research

∙ 05/11/2020

Neural Polysynthetic Language Modelling

Research in natural language processing commonly assumes that approaches...

Lane Schwartz, et al. ∙

research

∙ 03/19/2020

EQL – an extremely easy to learn knowledge graph query language, achieving highspeed and precise search

EQL, also named as Extremely Simple Query Language, can be widely used i...

Han Liu, et al. ∙

research

∙ 01/14/2020

"Why is 'Chicago' deceptive?" Towards Building Model-Driven Tutorials for Humans

To support human decision making with machine learning models, we often ...

Vivian Lai, et al. ∙

research

∙ 12/22/2019

AdvCodec: Towards A Unified Framework for Adversarial Text Generation

While there has been great interest in generating imperceptible adversar...

Boxin Wang, et al. ∙

research

∙ 12/11/2019

Automatic quality assessment for 2D fetal sonographic standard plane based on multi-task learning

The quality control of fetal sonographic (FS) images is essential for th...

Hong Luo, et al. ∙

research

∙ 09/27/2019

Clustering Uncertain Data via Representative Possible Worlds with Consistency Learning

Clustering uncertain data is an essential task in data mining for the in...

Han Liu, et al. ∙

research

∙ 09/26/2019

Attributed Graph Learning with 2-D Graph Convolution

Graph convolutional neural networks have demonstrated promising performa...

Qimai Li, et al. ∙

research

∙ 09/16/2019

MVDLite: A Light-weight Model View Definition Representation with Fast Validation for Building Information Model

Model View Definition (MVD) is the standard methodology to define the ex...

Han Liu, et al. ∙

research

∙ 09/16/2019

MVDLite: A Light-weight Representation of Model View Definition with Fast Validation for BIM Applications

Model View Definition (MVD) is the standard methodology to define the pa...

Han Liu, et al. ∙

research

∙ 09/13/2019

Fast Low-rank Metric Learning for Large-scale and High-dimensional Data

Low-rank metric learning aims to learn better discrimination of data sub...

Han Liu, et al. ∙

research

∙ 07/14/2019

More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning

We consider the weakly supervised binary classification problem where th...

Xinyang Yi, et al. ∙

research

∙ 06/20/2019

Few-Shot Sequence Labeling with Label Dependency Transfer

Few-shot sequence labeling faces a unique challenge compared with the ot...

Yutai Hou, et al. ∙

research

∙ 06/04/2019

Attributed Graph Clustering via Adaptive Graph Convolution

Attributed graph clustering is challenging as it requires joint modellin...

Xiaotong Zhang, et al. ∙

research

∙ 05/28/2019

Estimating and Inferring the Maximum Degree of Stimulus-Locked Time-Varying Brain Connectivity Networks

Neuroscientists have enjoyed much success in understanding brain functio...

Kean Ming Tan, et al. ∙

research

∙ 12/19/2018

Covariance-based sample selection for heterogenous data: Applications to gene expression and autism risk gene detection

Risk for autism can be influenced by genetic mutations in hundreds of ge...

Kevin Lin, et al. ∙

research

∙ 12/06/2018

Finite-Sample Analyses for Fully Decentralized Multi-Agent Reinforcement Learning

Despite the increasing interest in multi-agent reinforcement learning (M...

Kaiqing Zhang, et al. ∙

research

∙ 11/09/2018

EASYFLOW: Keep Ethereum Away From Overflow

While Ethereum smart contracts enabled a wide range of blockchain applic...

Jianbo Gao, et al. ∙

research

∙ 10/31/2018

Performance assessment of the deep learning technologies in grading glaucoma severity

Objective: To validate and compare the performance of eight available de...

Yi Zhen, et al. ∙

research

∙ 10/30/2018

SDFN: Segmentation-based Deep Fusion Network for Thoracic Disease Classification in Chest X-ray Images

This study aims to automatically diagnose thoracic diseases depicted on ...

Han Liu, et al. ∙

research

∙ 10/19/2018

Super-pixel cloud detection using Hierarchical Fusion CNN

Cloud detection plays a very important role in the process of remote sen...

Han Liu, et al. ∙

research

∙ 10/10/2018

Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space

Most existing deep reinforcement learning (DRL) frameworks consider eith...

Jiechao Xiong, et al. ∙

research

∙ 09/25/2018

Fully Implicit Online Learning

Regularized online learning is widely used in machine learning. In this ...

Chaobing Song, et al. ∙

research

∙ 09/21/2018

High Temperature Structure Detection in Ferromagnets

This paper studies structure detection problems in high temperature ferr...

Yuan Cao, et al. ∙

research

∙ 09/19/2018

TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full Game

Starcraft II (SCII) is widely considered as the most challenging Real Ti...

Peng Sun, et al. ∙

research

∙ 09/17/2018

A convex formulation for high-dimensional sparse sliced inverse regression

Sliced inverse regression is a popular tool for sufficient dimension red...

Kean Ming Tan, et al. ∙

research

∙ 09/11/2018

Factorized Q-Learning for Large-Scale Multi-Agent Systems

Deep Q-learning has achieved a significant success in single-agent decis...

Yong Chen, et al. ∙

research

∙ 08/29/2018

Diffusion Approximations for Online Principal Component Estimation and Global Convergence

In this paper, we propose to adopt the diffusion approximation tools to ...

Chris Junchi Li, et al. ∙

research

∙ 08/29/2018

Online ICA: Understanding Global Dynamics of Nonconvex Optimization via Diffusion Processes

Solving statistical learning problems often involves nonconvex optimizat...

Chris Junchi Li, et al. ∙

research

∙ 08/21/2018

Curse of Heterogeneity: Computational Barriers in Sparse Mixture Models and Phase Retrieval

We study the fundamental tradeoffs between statistical accuracy and comp...

Jianqing Fan, et al. ∙

Han Liu

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