Singapore University of Technology and Design

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SUTD advances knowledge and nurtures technically-grounded leaders and innovators, with a focus on design, through multi-disciplinary education in engineering and architecture and research.

Biologically Plausible Sequence Learning with Spiking Neural Networks

Motivated by the celebrated discrete-time model of nervous activity outl...
11/25/2019 ∙ by Zuozhu Liu, et al. ∙ 38 ∙ share

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Factorized Multimodal Transformer for Multimodal Sequential Learning

The complex world around us is inherently multimodal and sequential (con...
11/22/2019 ∙ by Amir Zadeh, et al. ∙ 31 ∙ share

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Disentangling Representations using Gaussian Processes in Variational Autoencoders for Video Prediction

We introduce MGP-VAE, a variational autoencoder which uses Gaussian proc...
01/08/2020 ∙ by Sarthak Bhagat, et al. ∙ 26 ∙ share

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Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification

Anomaly detection algorithms find extensive use in various fields. This ...
01/24/2020 ∙ by Penny Chong, et al. ∙ 22 ∙ share

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Representation Similarity Analysis for Efficient Task taxonomy & Transfer Learning

Transfer learning is widely used in deep neural network models when ther...
04/26/2019 ∙ by Kshitij Dwivedi, et al. ∙ 20 ∙ share

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DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN

Recently, the introduction of the generative adversarial network (GAN) a...
08/23/2018 ∙ by Swee Kiat Lim, et al. ∙ 16 ∙ share

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Deep Semi-Supervised Anomaly Detection

Deep approaches to anomaly detection have recently shown promising resul...
06/06/2019 ∙ by Lukas Ruff, et al. ∙ 12 ∙ share

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Lymphocyte counting – Error Analysis of Regression versus Bounding Box Detection Approaches

We consider the problem of counting cell nuclei from celltype-agnostic h...
07/21/2020 ∙ by Lin Geng Foo, et al. ∙ 10 ∙ share

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Training Classifiers that are Universally Robust to All Label Noise Levels

For classification tasks, deep neural networks are prone to overfitting ...
05/27/2021 ∙ by Jingyi Xu, et al. ∙ 10 ∙ share

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Dual-Refinement: Joint Label and Feature Refinement for Unsupervised Domain Adaptive Person Re-Identification

Unsupervised domain adaptive (UDA) person re-identification (re-ID) is a...
12/26/2020 ∙ by Yongxing Dai, et al. ∙ 9 ∙ share

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A*3D Dataset: Towards Autonomous Driving in Challenging Environments

With the increasing global popularity of self-driving cars, there is an ...
09/17/2019 ∙ by Quang-Hieu Pham, et al. ∙ 7 ∙ share

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Generalizable Person Re-identification with Relevance-aware Mixture of Experts

Domain generalizable (DG) person re-identification (ReID) is a challengi...
05/19/2021 ∙ by Yongxing Dai, et al. ∙ 6 ∙ share

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WildMix Dataset and Spectro-Temporal Transformer Model for Monoaural Audio Source Separation

Monoaural audio source separation is a challenging research area in mach...
11/21/2019 ∙ by Amir Zadeh, et al. ∙ 5 ∙ share

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Understanding Integrated Gradients with SmoothTaylor for Deep Neural Network Attribution

Integrated gradients as an attribution method for deep neural network mo...
04/22/2020 ∙ by Gary S. W. Goh, et al. ∙ 5 ∙ share

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Generative Adversarial Autoencoder Networks

We introduce an effective model to overcome the problem of mode collapse...
03/23/2018 ∙ by Ngoc-Trung Tran, et al. ∙ 4 ∙ share

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Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)

Sarcasm is often expressed through several verbal and non-verbal cues, e...
06/05/2019 ∙ by Santiago Castro, et al. ∙ 4 ∙ share

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Duality Diagram Similarity: a generic framework for initialization selection in task transfer learning

In this paper, we tackle an open research question in transfer learning,...
08/05/2020 ∙ by Kshitij Dwivedi, et al. ∙ 4 ∙ share

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Learning Disentangled Representations of Timbre and Pitch for Musical Instrument Sounds Using Gaussian Mixture Variational Autoencoders

In this paper, we learn disentangled representations of timbre and pitch...
06/19/2019 ∙ by Yin-Jyun Luo, et al. ∙ 2 ∙ share

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Evaluating Cascading Effects of Attacks on Resilience of Industrial Control Systems: A Design-Centric Modeling Approach

A design-centric modeling approach was proposed to model the behavior of...
05/08/2019 ∙ by Zhongyuan Hau, et al. ∙ 1 ∙ share

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The Algonauts Project: A Platform for Communication between the Sciences of Biological and Artificial Intelligence

In the last decade, artificial intelligence (AI) models inspired by the ...
05/14/2019 ∙ by Radoslaw Martin Cichy, et al. ∙ 1 ∙ share

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The Disruptions of 5G on Data-driven Technologies and Applications

With 5G on the verge of being adopted as the next mobile network, there ...
09/06/2019 ∙ by Dumitrel Loghin, et al. ∙ 1 ∙ share

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Sensor Fusion for Public Space Utilization Monitoring in a Smart City

Public space utilization is crucial for urban developers to understand h...
09/15/2017 ∙ by Billy Pik Lik Lau, et al. ∙ 0 ∙ share

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SenseFlow: An Experimental Study for Tracking People

The main challenges in large-scale people tracking are the recognition o...
06/12/2016 ∙ by Kai Li, et al. ∙ 0 ∙ share

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Variational Probability Flow for Biologically Plausible Training of Deep Neural Networks

The quest for biologically plausible deep learning is driven, not just b...
11/21/2017 ∙ by Zuozhu Liu, et al. ∙ 0 ∙ share

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Adaptive Quantization for Deep Neural Network

In recent years Deep Neural Networks (DNNs) have been rapidly developed ...
12/04/2017 ∙ by Yiren Zhou, et al. ∙ 0 ∙ share

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Vprop: Variational Inference using RMSprop

Many computationally-efficient methods for Bayesian deep learning rely o...
12/04/2017 ∙ by Mohammad Emtiyaz Khan, et al. ∙ 0 ∙ share

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Accessible Melanoma Detection using Smartphones and Mobile Image Analysis

We investigate the design of an entire mobile imaging system for early d...
11/27/2017 ∙ by T. -T. Do, et al. ∙ 0 ∙ share

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First-order Methods Almost Always Avoid Saddle Points

We establish that first-order methods avoid saddle points for almost all...
10/20/2017 ∙ by Jason D. Lee, et al. ∙ 0 ∙ share

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Understanding and Comparing Deep Neural Networks for Age and Gender Classification

Recently, deep neural networks have demonstrated excellent performances ...
08/25/2017 ∙ by Sebastian Lapuschkin, et al. ∙ 0 ∙ share

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Detection of Unauthorized IoT Devices Using Machine Learning Techniques

Security experts have demonstrated numerous risks imposed by Internet of...
09/14/2017 ∙ by Yair Meidan, et al. ∙ 0 ∙ share

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Experience Replay Using Transition Sequences

Experience replay is one of the most commonly used approaches to improve...
05/30/2017 ∙ by Thommen George Karimpanal, et al. ∙ 0 ∙ share

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Mobile Big Data Analytics Using Deep Learning and Apache Spark

The proliferation of mobile devices, such as smartphones and Internet of...
02/23/2016 ∙ by Mohammad Abu Alsheikh, et al. ∙ 0 ∙ share

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Cross-Domain Image Retrieval with Attention Modeling

With the proliferation of e-commerce websites and the ubiquitousness of ...
09/06/2017 ∙ by Xin Ji, et al. ∙ 0 ∙ share

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Identification and Off-Policy Learning of Multiple Objectives Using Adaptive Clustering

In this work, we present a methodology that enables an agent to make eff...
05/17/2017 ∙ by Thommen George Karimpanal, et al. ∙ 0 ∙ share

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Selective Deep Convolutional Features for Image Retrieval

Convolutional Neural Network (CNN) is a very powerful approach to extrac...
07/04/2017 ∙ by Tuan Hoang, et al. ∙ 0 ∙ share

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Truly Multi-modal YouTube-8M Video Classification with Video, Audio, and Text

The YouTube-8M video classification challenge requires teams to classify...
06/17/2017 ∙ by Zhe Wang, et al. ∙ 0 ∙ share

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Simultaneous Feature Aggregating and Hashing for Large-scale Image Search

In most state-of-the-art hashing-based visual search systems, local imag...
04/04/2017 ∙ by Thanh-Toan Do, et al. ∙ 0 ∙ share

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A Robust 3D-2D Interactive Tool for Scene Segmentation and Annotation

Recent advances of 3D acquisition devices have enabled large-scale acqui...
10/19/2016 ∙ by Duc Thanh Nguyen, et al. ∙ 0 ∙ share

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Quantum assisted Gaussian process regression

Gaussian processes (GP) are a widely used model for regression problems ...
12/12/2015 ∙ by Zhikuan Zhao, et al. ∙ 0 ∙ share

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Embedding based on function approximation for large scale image search

The objective of this paper is to design an embedding method that maps l...
05/23/2016 ∙ by Thanh-Toan Do, et al. ∙ 0 ∙ share

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Towards Building an RGBD-M Scanner

We present a portable device to capture both shape and reflectance of an...
03/12/2016 ∙ by Zhe Wu, et al. ∙ 0 ∙ share

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Segmentation Rectification for Video Cutout via One-Class Structured Learning

Recent works on interactive video object cutout mainly focus on designin...
02/16/2016 ∙ by Junyan Wang, et al. ∙ 0 ∙ share

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Image-based Vehicle Analysis using Deep Neural Network: A Systematic Study

We address the vehicle detection and classification problems using Deep ...
01/06/2016 ∙ by Yiren Zhou, et al. ∙ 0 ∙ share

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Analyzing Classifiers: Fisher Vectors and Deep Neural Networks

Fisher Vector classifiers and Deep Neural Networks (DNNs) are popular an...
12/01/2015 ∙ by Sebastian Bach, et al. ∙ 0 ∙ share

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Superpixelizing Binary MRF for Image Labeling Problems

Superpixels have become prevalent in computer vision. They have been use...
03/23/2015 ∙ by Junyan Wang, et al. ∙ 0 ∙ share

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YEDDA: A Lightweight Collaborative Text Span Annotation Tool

In this paper, we introduce YEDDA, a lightweight but efficient open-sour...
11/10/2017 ∙ by Jie Yang, et al. ∙ 0 ∙ share

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Combining Discrete and Neural Features for Sequence Labeling

Neural network models have recently received heated research attention i...
08/24/2017 ∙ by Jie Yang, et al. ∙ 0 ∙ share

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Measuring Thematic Fit with Distributional Feature Overlap

In this paper, we introduce a new distributional method for modeling pre...
07/19/2017 ∙ by Enrico Santus, et al. ∙ 0 ∙ share

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Neural Reranking for Named Entity Recognition

We propose a neural reranking system for named entity recognition (NER)....
07/17/2017 ∙ by Jie Yang, et al. ∙ 0 ∙ share

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Universal Dependencies Parsing for Colloquial Singaporean English

Singlish can be interesting to the ACL community both linguistically as ...
05/18/2017 ∙ by Hongmin Wang, et al. ∙ 0 ∙ share

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