Association for Computing Machinery

research

∙ 09/16/2021

Efficient Scaling of Dynamic Graph Neural Networks

We present distributed algorithms for training dynamic Graph Neural Netw...

Venkatesan T. Chakaravarthy, et al. ∙

research

∙ 03/30/2021

Generalized Organ Segmentation by Imitating One-shot Reasoning using Anatomical Correlation

Learning by imitation is one of the most significant abilities of human ...

Hong-Yu Zhou, et al. ∙

research

∙ 10/04/2019

Predicting the Role of Political Trolls in Social Media

We investigate the political roles of "Internet trolls" in social media....

Atanas Atanasov, et al. ∙

research

∙ 11/04/2021

Generalized Radiograph Representation Learning via Cross-supervision between Images and Free-text Radiology Reports

Pre-training lays the foundation for recent successes in radiograph anal...

Hong-Yu Zhou, et al. ∙

research

∙ 01/17/2020

GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks

Graph structured data has wide applicability in various domains such as ...

Qiang Huang, et al. ∙

research

∙ 12/04/2019

EmbedMask: Embedding Coupling for One-stage Instance Segmentation

Current instance segmentation methods can be categorized into segmentati...

Hui Ying, et al. ∙

research

∙ 11/23/2019

Self-Enhanced Convolutional Network for Facial Video Hallucination

As a domain-specific super-resolution problem, facial image hallucinatio...

Chaowei Fang, et al. ∙

research

∙ 08/18/2021

Table Caption Generation in Scholarly Documents Leveraging Pre-trained Language Models

This paper addresses the problem of generating table captions for schola...

Junjie H. Xu, et al. ∙

research

∙ 09/07/2021

nnFormer: Interleaved Transformer for Volumetric Segmentation

Transformers, the default model of choices in natural language processin...

Hong-Yu Zhou, et al. ∙

research

∙ 10/25/2021

SciClops: Detecting and Contextualizing Scientific Claims for Assisting Manual Fact-Checking

This paper describes SciClops, a method to help combat online scientific...

Panayiotis Smeros, et al. ∙

research

∙ 11/27/2019

Information-Geometric Set Embeddings (IGSE): From Sets to Probability Distributions

This letter introduces an abstract learning problem called the “set embe...

Ke Sun, et al. ∙

research

∙ 03/25/2021

I^3Net: Implicit Instance-Invariant Network for Adapting One-Stage Object Detectors

Recent works on two-stage cross-domain detection have widely explored th...

Chaoqi Chen, et al. ∙

research

∙ 03/28/2019

FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation

Modern approaches for semantic segmentation usually employ dilated convo...

Huikai Wu, et al. ∙

research

∙ 08/02/2021

GraphFPN: Graph Feature Pyramid Network for Object Detection

Feature pyramids have been proven powerful in image understanding tasks ...

Gangming Zhao, et al. ∙

research

∙ 05/21/2021

Act Like a Radiologist: Towards Reliable Multi-view Correspondence Reasoning for Mammogram Mass Detection

Mammogram mass detection is crucial for diagnosing and preventing the br...

Yuhang Liu, et al. ∙

research

∙ 12/04/2021

SHAPr: An Efficient and Versatile Membership Privacy Risk Metric for Machine Learning

Data used to train machine learning (ML) models can be sensitive. Member...

Vasisht Duddu, et al. ∙

research

∙ 05/03/2022

Predicting Loose-Fitting Garment Deformations Using Bone-Driven Motion Networks

We present a learning algorithm that uses bone-driven motion networks to...

Xiaoyu Pan, et al. ∙

research

∙ 09/10/2021

Per Garment Capture and Synthesis for Real-time Virtual Try-on

Virtual try-on is a promising application of computer graphics and human...

Toby Chong, et al. ∙

research

∙ 01/07/2022

Cross-Modality Deep Feature Learning for Brain Tumor Segmentation

Recent advances in machine learning and prevalence of digital medical im...

Dingwen Zhang, 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

∙ 01/22/2020

Depthwise Non-local Module for Fast Salient Object Detection Using a Single Thread

Recently deep convolutional neural networks have achieved significant su...

Haofeng Li, et al. ∙

research

∙ 04/19/2021

Cross-Domain Adaptive Clustering for Semi-Supervised Domain Adaptation

In semi-supervised domain adaptation, a few labeled samples per class in...

Jichang Li, et al. ∙

research

∙ 01/05/2022

Towards Understanding Quality Challenges of the Federated Learning: A First Look from the Lens of Robustness

Federated learning (FL) is a widely adopted distributed learning paradig...

Amin Eslami Abyane, et al. ∙

research

∙ 02/17/2022

The Gene of Scientific Success

This paper elaborates how to identify and evaluate causal factors to imp...

Xiangjie Kong, et al. ∙

research

∙ 04/21/2022

Domain Invariant Model with Graph Convolutional Network for Mammogram Classification

Due to its safety-critical property, the image-based diagnosis is desire...

Churan Wang, et al. ∙

research

∙ 09/16/2019

Motion Guided Attention for Video Salient Object Detection

Video salient object detection aims at discovering the most visually dis...

Haofeng Li, et al. ∙

research

∙ 01/05/2022

Advancing 3D Medical Image Analysis with Variable Dimension Transform based Supervised 3D Pre-training

The difficulties in both data acquisition and annotation substantially r...

Shu Zhang, et al. ∙

research

∙ 10/25/2018

Geometry and clustering with metrics derived from separable Bregman divergences

Separable Bregman divergences induce Riemannian metric spaces that are i...

Erika Gomes-Gonçalves, et al. ∙

research

∙ 04/20/2022

Who Is Missing? Characterizing the Participation of Different Demographic Groups in a Korean Nationwide Daily Conversation Corpus

A conversation corpus is essential to build interactive AI applications....

Haewoon Kwak, et al. ∙

research

∙ 08/07/2018

Grassmannian Learning: Embedding Geometry Awareness in Shallow and Deep Learning

Modern machine learning algorithms have been adopted in a range of signa...

Jiayao Zhang, et al. ∙

research

∙ 10/22/2018

The Bregman chord divergence

Distances are fundamental primitives whose choice significantly impacts ...

Frank Nielsen, et al. ∙

research

∙ 11/30/2018

FSNet: An Identity-Aware Generative Model for Image-based Face Swapping

This paper presents FSNet, a deep generative model for image-based face ...

Ryota Natsume, et al. ∙

research

∙ 01/15/2020

Lightweight 3D Human Pose Estimation Network Training Using Teacher-Student Learning

We present MoVNect, a lightweight deep neural network to capture 3D huma...

Dong-Hyun Hwang, et al. ∙

research

∙ 02/05/2020

Crowdsourcing the Perception of Machine Teaching

Teachable interfaces can empower end-users to attune machine learning sy...

Jonggi Hong, et al. ∙

research

∙ 12/10/2020

Few-shot Medical Image Segmentation using a Global Correlation Network with Discriminative Embedding

Despite deep convolutional neural networks achieved impressive progress ...

Liyan Sun, et al. ∙

research

∙ 05/15/2019

Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning

Current advances in Artificial Intelligence and machine learning in gene...

Artur d'Avila Garcez, et al. ∙

research

∙ 05/27/2019

Lightlike Neuromanifolds, Occam's Razor and Deep Learning

Why do deep neural networks generalize with a very high dimensional para...

Ke Sun, et al. ∙

research

∙ 02/22/2022

PointMatch: A Consistency Training Framework for Weakly SupervisedSemantic Segmentation of 3D Point Clouds

Semantic segmentation of point cloud usually relies on dense annotation ...

Yushuang Wu, et al. ∙

research

∙ 05/01/2022

A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Prediction

More and more investors and machine learning models rely on social media...

Yong Xie, et al. ∙

research

∙ 04/10/2018

RSGAN: Face Swapping and Editing using Face and Hair Representation in Latent Spaces

In this paper, we present an integrated system for automatically generat...

Ryota Natsume, et al. ∙

research

∙ 05/08/2018

Moiré Photo Restoration Using Multiresolution Convolutional Neural Networks

Digital cameras and mobile phones enable us to conveniently record preci...

Yujing Sun, et al. ∙

research

∙ 03/24/2021

Coarse-to-Fine Domain Adaptive Semantic Segmentation with Photometric Alignment and Category-Center Regularization

Unsupervised domain adaptation (UDA) in semantic segmentation is a funda...

Xiangru Lin, et al. ∙

research

∙ 10/08/2021

Context-LGM: Leveraging Object-Context Relation for Context-Aware Object Recognition

Context, as referred to situational factors related to the object of int...

Mingzhou Liu, et al. ∙

research

∙ 03/24/2022

Compound Domain Generalization via Meta-Knowledge Encoding

Domain generalization (DG) aims to improve the generalization performanc...

Chaoqi Chen, et al. ∙

research

∙ 04/24/2022

Dictionary Attacks on Speaker Verification

In this paper, we propose dictionary attacks against speaker verificatio...

Mirko Marras, et al. ∙

research

∙ 09/17/2020

Online Alternate Generator against Adversarial Attacks

The field of computer vision has witnessed phenomenal progress in recent...

Haofeng Li, et al. ∙

research

∙ 09/10/2012

Safe and Stabilizing Distributed Multi-Path Cellular Flows

We study the problem of distributed traffic control in the partitioned p...

Taylor T. Johnson, et al. ∙

research

∙ 12/01/2017

Neural Signatures for Licence Plate Re-identification

The problem of vehicle licence plate re-identification is generally cons...

Abhinav Kumar, et al. ∙

research

∙ 07/27/2017

An Epistemic Foundation for Authentication Logics (Extended Abstract)

While there have been many attempts, going back to BAN logic, to base re...

Joseph Y. Halpern, et al. ∙

research

∙ 04/25/2016

Protein Secondary Structure Prediction Using Cascaded Convolutional and Recurrent Neural Networks

Protein secondary structure prediction is an important problem in bioinf...

Zhen Li, et al. ∙

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