Association for Computing Machinery

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ACM, the world's largest educational and scientific computing society, delivers resources that advance computing as a science and a profession. ACM provides the computing field's premier Digital Library and serves its members and the computing profession with leading-edge publications, conferences, and career resources.

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

Learning by imitation is one of the most significant abilities of human ...
03/30/2021 ∙ by Hong-Yu Zhou, et al. ∙ 26 ∙ share

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Predicting the Role of Political Trolls in Social Media

We investigate the political roles of "Internet trolls" in social media....
10/04/2019 ∙ by Atanas Atanasov, et al. ∙ 25 ∙ share

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GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks

Graph structured data has wide applicability in various domains such as ...
01/17/2020 ∙ by Qiang Huang, et al. ∙ 22 ∙ share

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EmbedMask: Embedding Coupling for One-stage Instance Segmentation

Current instance segmentation methods can be categorized into segmentati...
12/04/2019 ∙ by Hui Ying, et al. ∙ 20 ∙ share

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Self-Enhanced Convolutional Network for Facial Video Hallucination

As a domain-specific super-resolution problem, facial image hallucinatio...
11/23/2019 ∙ by Chaowei Fang, et al. ∙ 19 ∙ share

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

This letter introduces an abstract learning problem called the “set embe...
11/27/2019 ∙ by Ke Sun, et al. ∙ 16 ∙ share

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

Recent works on two-stage cross-domain detection have widely explored th...
03/25/2021 ∙ by Chaoqi Chen, et al. ∙ 14 ∙ share

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FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation

Modern approaches for semantic segmentation usually employ dilated convo...
03/28/2019 ∙ by Huikai Wu, et al. ∙ 12 ∙ share

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

To support human decision making with machine learning models, we often ...
01/14/2020 ∙ by Vivian Lai, et al. ∙ 8 ∙ share

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

Recently deep convolutional neural networks have achieved significant su...
01/22/2020 ∙ by Haofeng Li, et al. ∙ 8 ∙ share

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Cross-Domain Adaptive Clustering for Semi-Supervised Domain Adaptation

In semi-supervised domain adaptation, a few labeled samples per class in...
04/19/2021 ∙ by Jichang Li, et al. ∙ 8 ∙ share

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Motion Guided Attention for Video Salient Object Detection

Video salient object detection aims at discovering the most visually dis...
09/16/2019 ∙ by Haofeng Li, et al. ∙ 7 ∙ share

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Geometry and clustering with metrics derived from separable Bregman divergences

Separable Bregman divergences induce Riemannian metric spaces that are i...
10/25/2018 ∙ by Erika Gomes-Gonçalves, et al. ∙ 6 ∙ share

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Grassmannian Learning: Embedding Geometry Awareness in Shallow and Deep Learning

Modern machine learning algorithms have been adopted in a range of signa...
08/07/2018 ∙ by Jiayao Zhang, et al. ∙ 4 ∙ share

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The Bregman chord divergence

Distances are fundamental primitives whose choice significantly impacts ...
10/22/2018 ∙ by Frank Nielsen, et al. ∙ 4 ∙ share

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

This paper presents FSNet, a deep generative model for image-based face ...
11/30/2018 ∙ by Ryota Natsume, et al. ∙ 4 ∙ share

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

We present MoVNect, a lightweight deep neural network to capture 3D huma...
01/15/2020 ∙ by Dong-Hyun Hwang, et al. ∙ 4 ∙ share

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Crowdsourcing the Perception of Machine Teaching

Teachable interfaces can empower end-users to attune machine learning sy...
02/05/2020 ∙ by Jonggi Hong, et al. ∙ 4 ∙ share

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

Despite deep convolutional neural networks achieved impressive progress ...
12/10/2020 ∙ by Liyan Sun, et al. ∙ 4 ∙ share

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

Current advances in Artificial Intelligence and machine learning in gene...
05/15/2019 ∙ by Artur d'Avila Garcez, et al. ∙ 3 ∙ share

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Lightlike Neuromanifolds, Occam's Razor and Deep Learning

Why do deep neural networks generalize with a very high dimensional para...
05/27/2019 ∙ by Ke Sun, et al. ∙ 3 ∙ share

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

In this paper, we present an integrated system for automatically generat...
04/10/2018 ∙ by Ryota Natsume, et al. ∙ 2 ∙ share

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Moiré Photo Restoration Using Multiresolution Convolutional Neural Networks

Digital cameras and mobile phones enable us to conveniently record preci...
05/08/2018 ∙ by Yujing Sun, et al. ∙ 2 ∙ share

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

Unsupervised domain adaptation (UDA) in semantic segmentation is a funda...
03/24/2021 ∙ by Haoyu Ma, et al. ∙ 2 ∙ share

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Online Alternate Generator against Adversarial Attacks

The field of computer vision has witnessed phenomenal progress in recent...
09/17/2020 ∙ by Haofeng Li, et al. ∙ 1 ∙ share

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Safe and Stabilizing Distributed Multi-Path Cellular Flows

We study the problem of distributed traffic control in the partitioned p...
09/10/2012 ∙ by Taylor T. Johnson, et al. ∙ 0 ∙ share

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Neural Signatures for Licence Plate Re-identification

The problem of vehicle licence plate re-identification is generally cons...
12/01/2017 ∙ by Abhinav Kumar, et al. ∙ 0 ∙ share

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An Epistemic Foundation for Authentication Logics (Extended Abstract)

While there have been many attempts, going back to BAN logic, to base re...
07/27/2017 ∙ by Joseph Y. Halpern, et al. ∙ 0 ∙ share

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Protein Secondary Structure Prediction Using Cascaded Convolutional and Recurrent Neural Networks

Protein secondary structure prediction is an important problem in bioinf...
04/25/2016 ∙ by Zhen Li, et al. ∙ 0 ∙ share

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Towards balanced clustering - part 1 (preliminaries)

The article contains a preliminary glance at balanced clustering problem...
06/09/2017 ∙ by Mark Sh. Levin, et al. ∙ 0 ∙ share

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LSTM-CF: Unifying Context Modeling and Fusion with LSTMs for RGB-D Scene Labeling

Semantic labeling of RGB-D scenes is crucial to many intelligent applica...
04/18/2016 ∙ by Zhen Li, et al. ∙ 0 ∙ share

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A Survey of Calibration Methods for Optical See-Through Head-Mounted Displays

Optical see-through head-mounted displays (OST HMDs) are a major output ...
09/13/2017 ∙ by Jens Grubert, et al. ∙ 0 ∙ share

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Note on Evolution and Forecasting of Requirements: Communications Example

Combinatorial evolution and forecasting of system requirements is examin...
05/22/2017 ∙ by Mark Sh. Levin, et al. ∙ 0 ∙ share

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Barankin Vector Locally Best Unbiased Estimates

The Barankin bound is generalized to the vector case in the mean square ...
06/30/2017 ∙ by Bruno Cernuschi-Frias, et al. ∙ 0 ∙ share

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Fast Algorithms for Convolutional Neural Networks

Deep convolutional neural networks take GPU days of compute time to trai...
09/30/2015 ∙ by Andrew Lavin, et al. ∙ 0 ∙ share

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On Sampling Strategies for Neural Network-based Collaborative Filtering

Recent advances in neural networks have inspired people to design hybrid...
06/23/2017 ∙ by Ting Chen, et al. ∙ 0 ∙ share

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Interpretable Predictions of Tree-based Ensembles via Actionable Feature Tweaking

Machine-learned models are often described as "black boxes". In many rea...
06/20/2017 ∙ by Gabriele Tolomei, et al. ∙ 0 ∙ share

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Attributed Network Embedding for Learning in a Dynamic Environment

Network embedding leverages the node proximity manifested to learn a low...
06/06/2017 ∙ by Jundong Li, et al. ∙ 0 ∙ share

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maxDNN: An Efficient Convolution Kernel for Deep Learning with Maxwell GPUs

This paper describes maxDNN, a computationally efficient convolution ker...
01/27/2015 ∙ by Andrew Lavin, et al. ∙ 0 ∙ share

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Comparing Dataset Characteristics that Favor the Apriori, Eclat or FP-Growth Frequent Itemset Mining Algorithms

Frequent itemset mining is a popular data mining technique. Apriori, Ecl...
01/30/2017 ∙ by Jeff Heaton, et al. ∙ 0 ∙ share

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Representation of Evolutionary Algorithms in FPGA Cluster for Project of Large-Scale Networks

Many problems are related to network projects, such as electric distribu...
12/17/2014 ∙ by Andre B. Perina, et al. ∙ 0 ∙ share

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Learning Edge Representations via Low-Rank Asymmetric Projections

We propose a new method for embedding graphs while preserving directed e...
05/16/2017 ∙ by Sami Abu-El-Haija, et al. ∙ 0 ∙ share

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Contextualizing Geometric Data Analysis and Related Data Analytics: A Virtual Microscope for Big Data Analytics

The relevance and importance of contextualizing data analytics is descri...
11/30/2016 ∙ by Fionn Murtagh, et al. ∙ 0 ∙ share

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Learning Concept Hierarchies through Probabilistic Topic Modeling

With the advent of semantic web, various tools and techniques have been ...
11/29/2016 ∙ by V. S. Anoop, et al. ∙ 0 ∙ share

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The NOESIS Network-Oriented Exploration, Simulation, and Induction System

Network data mining has become an important area of study due to the lar...
11/15/2016 ∙ by Víctor Martínez, et al. ∙ 0 ∙ share

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Massive Data Clustering in Moderate Dimensions from the Dual Spaces of Observation and Attribute Data Clouds

Cluster analysis of very high dimensional data can benefit from the prop...
04/06/2017 ∙ by Fionn Murtagh, et al. ∙ 0 ∙ share

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Show me the material evidence: Initial experiments on evaluating hypotheses from user-generated multimedia data

Subjective questions such as `does neymar dive', or `is clinton lying', ...
11/11/2016 ∙ by Bernardo Gonçalves, et al. ∙ 0 ∙ share

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X-CNN: Cross-modal Convolutional Neural Networks for Sparse Datasets

In this paper we propose cross-modal convolutional neural networks (X-CN...
10/01/2016 ∙ by Petar Veličković, et al. ∙ 0 ∙ share

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VHT: Vertical Hoeffding Tree

IoT Big Data requires new machine learning methods able to scale to larg...
07/28/2016 ∙ by Nicolas Kourtellis, et al. ∙ 0 ∙ share

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Ant Colony Optimization and Hypergraph Covering Problems

Ant Colony Optimization (ACO) is a very popular metaheuristic for solvin...
05/14/2011 ∙ by Ankit Pat, et al. ∙ 0 ∙ share

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