b'Tong Wang'

research

∙ 09/07/2023

DropPos: Pre-Training Vision Transformers by Reconstructing Dropped Positions

As it is empirically observed that Vision Transformers (ViTs) are quite ...

0 Haochen Wang, et al. ∙

research

∙ 06/27/2023

Wasserstein Generative Regression

In this paper, we propose a new and unified approach for nonparametric r...

0 Shanshan Song, et al. ∙

research

∙ 01/04/2023

Fragment-based t-SMILES for de novo molecular generation

At present, sequence-based and graph-based models are two of popular use...

0 Juan-Ni Wu, et al. ∙

research

∙ 12/13/2022

Semantics-Consistent Feature Search for Self-Supervised Visual Representation Learning

In contrastive self-supervised learning, the common way to learn discrim...

0 Kaiyou Song, et al. ∙

research

∙ 11/25/2022

GPT-3-driven pedagogical agents for training children's curious question-asking skills

Students' ability to ask curious questions is a crucial skill that impro...

0 Rania Abdelghani, et al. ∙

research

∙ 11/23/2022

An ensemble of VisNet, Transformer-M, and pretraining models for molecular property prediction in OGB Large-Scale Challenge @ NeurIPS 2022

In the technical report, we provide our solution for OGB-LSC 2022 Graph ...

0 Yusong Wang, et al. ∙

research

∙ 11/06/2022

ProtoX: Explaining a Reinforcement Learning Agent via Prototyping

While deep reinforcement learning has proven to be successful in solving...

0 Ronilo J. Ragodos, et al. ∙

research

∙ 10/23/2022

Learning to Advise Humans By Leveraging Algorithm Discretion

Expert decision-makers (DMs) in high-stakes AI-advised (AIDeT) settings ...

0 Nicholas Wolczynski, et al. ∙

research

∙ 10/20/2022

Low-Latency Hybrid NOMA-TDMA: QoS-Driven Design Framework

Enabling ultra-reliable and low-latency communication services while pro...

0 Yao Zhu, et al. ∙

research

∙ 09/22/2022

Selecting Better Samples from Pre-trained LLMs: A Case Study on Question Generation

Large Language Models (LLMs) have in recent years demonstrated impressiv...

2 Xingdi Yuan, et al. ∙

research

∙ 08/20/2022

General-to-Specific Transfer Labeling for Domain Adaptable Keyphrase Generation

Training keyphrase generation (KPG) models requires a large amount of an...

3 Rui Meng, et al. ∙

research

∙ 08/13/2022

Confidence Matters: Inspecting Backdoors in Deep Neural Networks via Distribution Transfer

Backdoor attacks have been shown to be a serious security threat against...

2 Tong Wang, et al. ∙

research

∙ 06/16/2022

Dual Contrastive Attributed Graph Clustering Network

Attributed graph clustering is one of the most important tasks in graph ...

13 Tong Wang, et al. ∙

research

∙ 04/27/2022

Towards Exploring the Code Reuse from Stack Overflow during Software Development

As one of the most well-known programmer Q A websites, Stack Overflow ...

0 Yuan Huang, et al. ∙

research

∙ 03/28/2022

Multi-View Substructure Learning for Drug-Drug Interaction Prediction

Drug-drug interaction (DDI) prediction provides a drug combination strat...

13 Zimeng Li, et al. ∙

research

∙ 03/21/2022

Better Language Model with Hypernym Class Prediction

Class-based language models (LMs) have been long devised to address cont...

10 He Bai, et al. ∙

research

∙ 03/18/2022

Efficient Estimation of the Additive Risks Model for Interval-Censored Data

In contrast to the popular Cox model which presents a multiplicative cov...

0 Tong Wang, et al. ∙

research

∙ 02/03/2022

Direct Molecular Conformation Generation

Molecular conformation generation aims to generate three-dimensional coo...

9 Jinhua Zhu, et al. ∙

research

∙ 12/13/2021

DenseGAP: Graph-Structured Dense Correspondence Learning with Anchor Points

Establishing dense correspondence between two images is a fundamental co...

6 Zhengfei Kuang, et al. ∙

research

∙ 11/22/2021

Backdoor Attack through Frequency Domain

Backdoor attacks have been shown to be a serious threat against deep lea...

32 Tong Wang, et al. ∙

research

∙ 11/02/2021

Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP

Meta-learning considers the problem of learning an efficient learning pr...

7 Trapit Bansal, et al. ∙

research

∙ 10/14/2021

Improved Drug-target Interaction Prediction with Intermolecular Graph Transformer

The identification of active binding drugs for target proteins (termed a...

12 Siyuan Liu, et al. ∙

research

∙ 10/09/2021

Towards Lifelong Learning of Multilingual Text-To-Speech Synthesis

This work presents a lifelong learning approach to train a multilingual ...

12 Mu Yang, et al. ∙

research

∙ 09/14/2021

Incentivizing Mobile Edge Caching and Sharing: An Evolutionary Game Approach

Mobile Edge Caching is a promising technique to enhance the content deli...

0 Mingyu Li, et al. ∙

research

∙ 06/04/2021

A Holistic Approach to Interpretability in Financial Lending: Models, Visualizations, and Summary-Explanations

Lending decisions are usually made with proprietary models that provide ...

13 Chaofan Chen, et al. ∙

research

∙ 05/31/2021

Bringing Structure into Summaries: a Faceted Summarization Dataset for Long Scientific Documents

Faceted summarization provides briefings of a document from different pe...

9 Rui Meng, et al. ∙

research

∙ 05/06/2021

Partially Interpretable Estimators (PIE): Black-Box-Refined Interpretable Machine Learning

We propose Partially Interpretable Estimators (PIE) which attribute a pr...

18 Tong Wang, et al. ∙

research

∙ 04/02/2021

Adaptive Class Suppression Loss for Long-Tail Object Detection

To address the problem of long-tail distribution for the large vocabular...

45 Tong Wang, et al. ∙

research

∙ 01/12/2021

A SOM-based Gradient-Free Deep Learning Method with Convergence Analysis

As gradient descent method in deep learning causes a series of questions...

6 Shaosheng Xu, et al. ∙

research

∙ 11/17/2020

Augmented Fairness: An Interpretable Model Augmenting Decision-Makers' Fairness

We propose a model-agnostic approach for mitigating the prediction bias ...

8 Tong Wang, et al. ∙

research

∙ 09/22/2020

An Empirical Study on Neural Keyphrase Generation

Recent years have seen a flourishing of neural keyphrase generation work...

0 Rui Meng, et al. ∙

research

∙ 09/16/2020

Monetizing Edge Service in Mobile Internet Ecosystem

In mobile Internet ecosystem, Mobile Users (MUs) purchase wireless data ...

0 Zhiyuan Wang, et al. ∙

research

∙ 07/19/2020

Same-Day Delivery with Fairness

The demand for same-day delivery (SDD) has increased rapidly in the last...

0 Xinwei Chen, et al. ∙

research

∙ 07/03/2020

Interpretable Sequence Classification Via Prototype Trajectory

We propose a novel interpretable recurrent neural network (RNN) model, c...

0 Dat Hong, et al. ∙

research

∙ 05/02/2020

Exploring and Predicting Transferability across NLP Tasks

Recent advances in NLP demonstrate the effectiveness of training large-s...

0 Tu Vu, et al. ∙

research

∙ 04/01/2020

Task-adaptive Asymmetric Deep Cross-modal Hashing

Supervised cross-modal hashing aims to embed the semantic correlations o...

0 Tong Wang, et al. ∙

research

∙ 03/10/2020

Crowd-MECS: A Novel Crowdsourcing Framework for Mobile Edge Caching and Sharing

Crowdsourced mobile edge caching and sharing (Crowd-MECS) is emerging as...

0 Changkun Jiang, et al. ∙

research

∙ 02/23/2020

Optimizing Traffic Lights with Multi-agent Deep Reinforcement Learning and V2X communication

We consider a system to optimize duration of traffic signals using multi...

0 Azhar Hussain, et al. ∙

research

∙ 02/10/2020

Interpretable Companions for Black-Box Models

We present an interpretable companion model for any pre-trained black-bo...

0 Danqing Pan, et al. ∙

research

∙ 12/01/2019

Efficient Estimation of Mixture Cure Frailty Model for Clustered Current Status Data

Current status data abounds in the field of epidemiology and public heal...

0 Tong Wang, et al. ∙

research

∙ 09/23/2019

Model-Agnostic Linear Competitors – When Interpretable Models Compete and Collaborate with Black-Box Models

Driven by an increasing need for model interpretability, interpretable m...

0 Hassan Rafique, et al. ∙

research

∙ 09/09/2019

Does Order Matter? An Empirical Study on Generating Multiple Keyphrases as a Sequence

Recently, concatenating multiple keyphrases as a target sequence has bee...

0 Rui Meng, et al. ∙

research

∙ 07/23/2019

Metalearned Neural Memory

We augment recurrent neural networks with an external memory mechanism t...

10 Tsendsuren Munkhdalai, et al. ∙

research

∙ 05/10/2019

Hybrid Predictive Model: When an Interpretable Model Collaborates with a Black-box Model

Interpretable machine learning has become a strong competitor for tradit...

0 Tong Wang, et al. ∙

research

∙ 12/13/2018

Next Hit Predictor - Self-exciting Risk Modeling for Predicting Next Locations of Serial Crimes

Our goal is to predict the location of the next crime in a crime series,...

0 Yunyi Li, et al. ∙

research

∙ 11/30/2018

An Interpretable Model with Globally Consistent Explanations for Credit Risk

We propose a possible solution to a public challenge posed by the Fair I...

0 Chaofan Chen, et al. ∙

research

∙ 10/11/2018

Generating Diverse Numbers of Diverse Keyphrases

Existing keyphrase generation studies suffer from the problems of genera...

0 Xingdi Yuan, et al. ∙

research

∙ 07/06/2018

Interpretable Patient Mortality Prediction with Multi-value Rule Sets

We propose a Multi-vAlue Rule Set (MRS) model for in-hospital predicting...

0 Tong Wang, et al. ∙

research

∙ 02/12/2018

Hybrid Decision Making: When Interpretable Models Collaborate With Black-Box Models

Interpretable machine learning models have received increasing interest ...

0 Tong Wang, et al. ∙

research

∙ 12/28/2017

Learning Rapid-Temporal Adaptations

A hallmark of human intelligence and cognition is its flexibility. One o...

0 Tsendsuren Munkhdalai, et al. ∙

Tong Wang

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