National University of Singapore

research

∙ 09/09/2021

DAN: Decentralized Attention-based Neural Network to Solve the MinMax Multiple Traveling Salesman Problem

The multiple traveling salesman problem (mTSP) is a well-known NP-hard p...

Yuhong Cao, et al. ∙

research

∙ 07/09/2020

Learning to Prune Deep Neural Networks via Reinforcement Learning

This paper proposes PuRL - a deep reinforcement learning (RL) based algo...

Manas Gupta, et al. ∙

research

∙ 03/02/2020

Differential Privacy at Risk: Bridging Randomness and Privacy Budget

The calibration of noise for a privacy-preserving mechanism depends on t...

Ashish Dandekar, et al. ∙

research

∙ 04/12/2020

Toward Hierarchical Self-Supervised Monocular Absolute Depth Estimation for Autonomous Driving Applications

In recent years, self-supervised methods for monocular depth estimation ...

Feng Xue, et al. ∙

research

∙ 05/17/2021

Differentiable SLAM-net: Learning Particle SLAM for Visual Navigation

Simultaneous localization and mapping (SLAM) remains challenging for a n...

Peter Karkus, et al. ∙

research

∙ 01/12/2020

Multi-source Domain Adaptation for Visual Sentiment Classification

Existing domain adaptation methods on visual sentiment classification ty...

Chuang Lin, et al. ∙

research

∙ 09/25/2019

Revisit Knowledge Distillation: a Teacher-free Framework

Knowledge Distillation (KD) aims to distill the knowledge of a cumbersom...

Li Yuan, et al. ∙

research

∙ 05/13/2020

Converting Anyone's Emotion: Towards Speaker-Independent Emotional Voice Conversion

Emotional voice conversion aims to convert the emotion of the speech fro...

Kun Zhou, et al. ∙

research

∙ 07/19/2021

Face.evoLVe: A High-Performance Face Recognition Library

In this paper, we develop face.evoLVe – a comprehensive library that col...

Qingzhong Wang, et al. ∙

research

∙ 12/05/2019

Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression

This paper presents a variational Bayesian kernel selection (VBKS) algor...

Tong Teng, et al. ∙

research

∙ 12/13/2019

Bonn Activity Maps: Dataset Description

The key prerequisite for accessing the huge potential of current machine...

Julian Tanke, et al. ∙

research

∙ 11/16/2019

Inverse Reinforcement Learning with Missing Data

We consider the problem of recovering an expert's reward function with i...

Tien Mai, et al. ∙

research

∙ 03/04/2020

Threats to Federated Learning: A Survey

With the emergence of data silos and popular privacy awareness, the trad...

Lingjuan Lyu, et al. ∙

research

∙ 12/11/2018

Loss Guided Activation for Action Recognition in Still Images

One significant problem of deep-learning based human action recognition ...

Lu Liu, et al. ∙

research

∙ 03/22/2019

Few-shot Adaptive Faster R-CNN

To mitigate the detection performance drop caused by domain shift, we ai...

PetsTime, et al. ∙

research

∙ 11/27/2019

Large-Scale Noun Compound Interpretation Using Bootstrapping and the Web as a Corpus

Responding to the need for semantic lexical resources in natural languag...

Su Nam Kim, et al. ∙

research

∙ 11/21/2021

TraVLR: Now You See It, Now You Don't! Evaluating Cross-Modal Transfer of Visio-Linguistic Reasoning

Numerous visio-linguistic (V+L) representation learning methods have bee...

Keng Ji Chow, et al. ∙

research

∙ 03/03/2022

TCTrack: Temporal Contexts for Aerial Tracking

Temporal contexts among consecutive frames are far from being fully util...

Ziang Cao, et al. ∙

research

∙ 08/24/2019

Single-Stage Multi-Person Pose Machines

Multi-person pose estimation is a challenging problem. Existing methods ...

Xuecheng Nie, et al. ∙

research

∙ 09/16/2019

PSGAN: Pose-Robust Spatial-Aware GAN for Customizable Makeup Transfer

We propose a novel Pose-robust Spatial-aware GAN (PSGAN) for transferrin...

Wentao Jiang, et al. ∙

research

∙ 02/11/2020

ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning

Recent powerful pre-trained language models have achieved remarkable per...

Weihao Yu, et al. ∙

research

∙ 03/03/2022

CAFE: Learning to Condense Dataset by Aligning Features

Dataset condensation aims at reducing the network training effort throug...

Kai Wang, et al. ∙

research

∙ 04/16/2019

CloudSegNet: A Deep Network for Nychthemeron Cloud Image Segmentation

We analyze clouds in the earth's atmosphere using ground-based sky camer...

Soumyabrata Dev, et al. ∙

research

∙ 04/21/2022

The Risks of Machine Learning Systems

The speed and scale at which machine learning (ML) systems are deployed ...

Samson Tan, et al. ∙

research

∙ 06/06/2021

Technical Report: Temporal Aggregate Representations

This technical report extends our work presented in [9] with more experi...

Fadime Sener, et al. ∙

research

∙ 10/15/2021

Graph Neural Networks with Learnable Structural and Positional Representations

Graph neural networks (GNNs) have become the standard learning architect...

Vijay Prakash Dwivedi, et al. ∙

research

∙ 07/20/2021

Learning ULMFiT and Self-Distillation with Calibration for Medical Dialogue System

A medical dialogue system is essential for healthcare service as providi...

Shuang Ao, et al. ∙

research

∙ 11/01/2021

Learning Iterative Robust Transformation Synchronization

Transformation Synchronization is the problem of recovering absolute tra...

Zi Jian Yew, et al. ∙

research

∙ 11/22/2021

MetaFormer is Actually What You Need for Vision

Transformers have shown great potential in computer vision tasks. A comm...

Weihao Yu, et al. ∙

research

∙ 08/28/2019

Explainable Video Action Reasoning via Prior Knowledge and State Transitions

Human action analysis and understanding in videos is an important and ch...

Tao Zhuo, et al. ∙

research

∙ 11/15/2019

Human Annotations Improve GAN Performances

Generative Adversarial Networks (GANs) have shown great success in many ...

Juanyong Duan, et al. ∙

research

∙ 02/07/2020

Off-policy Maximum Entropy Reinforcement Learning : Soft Actor-Critic with Advantage Weighted Mixture Policy(SAC-AWMP)

The optimal policy of a reinforcement learning problem is often disconti...

Zhimin Hou, et al. ∙

research

∙ 05/20/2022

Cross Reconstruction Transformer for Self-Supervised Time Series Representation Learning

Unsupervised/self-supervised representation learning in time series is c...

Wenrui Zhang, et al. ∙

research

∙ 10/03/2020

Beyond Tabula-Rasa: a Modular Reinforcement Learning Approach for Physically Embedded 3D Sokoban

Intelligent robots need to achieve abstract objectives using concrete, s...

Peter Karkus, et al. ∙

research

∙ 03/21/2021

The Discovery of Dynamics via Linear Multistep Methods and Deep Learning: Error Estimation

Identifying hidden dynamics from observed data is a significant and chal...

Qiang Du, et al. ∙

research

∙ 11/15/2021

Weakly-Supervised Dense Action Anticipation

Dense anticipation aims to forecast future actions and their durations f...

Haotong Zhang, et al. ∙

research

∙ 12/02/2021

Probabilistic Contrastive Loss for Self-Supervised Learning

This paper proposes a probabilistic contrastive loss function for self-s...

Shen Li, et al. ∙

research

∙ 04/17/2019

Cycle-SUM: Cycle-consistent Adversarial LSTM Networks for Unsupervised Video Summarization

In this paper, we present a novel unsupervised video summarization model...

Li Yuan, et al. ∙

research

∙ 07/21/2020

Balanced Meta-Softmax for Long-Tailed Visual Recognition

Deep classifiers have achieved great success in visual recognition. Howe...

Jiawei Ren, et al. ∙

research

∙ 05/23/2022

FaceMAE: Privacy-Preserving Face Recognition via Masked Autoencoders

Face recognition, as one of the most successful applications in artifici...

Kai Wang, et al. ∙

research

∙ 09/30/2019

Manifold Fitting in Ambient Space

Modern data sets in many applications no longer comprise samples of real...

Zhigang Yao, et al. ∙

research

∙ 03/24/2020

TRACER: A Framework for Facilitating Accurate and Interpretable Analytics for High Stakes Applications

In high stakes applications such as healthcare and finance analytics, th...

Kaiping Zheng, et al. ∙

research

∙ 12/19/2018

Shallow Cue Guided Deep Visual Tracking via Mixed Models

In this paper, a robust visual tracking approach via mixed model based c...

Fangwen Tu, et al. ∙

research

∙ 04/11/2019

Generating Multiple Hypotheses for 3D Human Pose Estimation with Mixture Density Network

3D human pose estimation from a monocular image or 2D joints is an ill-p...

Chen Li, et al. ∙

research

∙ 02/10/2020

Bilinear Graph Neural Network with Node Interactions

Graph Neural Network (GNN) is a powerful model to learn representations ...

Hongmin Zhu, et al. ∙

research

∙ 07/25/2021

Distributional Shifts in Automated Diabetic Retinopathy Screening

Deep learning-based models are developed to automatically detect if a re...

Jay Nandy, et al. ∙

research

∙ 05/04/2022

Are All the Datasets in Benchmark Necessary? A Pilot Study of Dataset Evaluation for Text Classification

In this paper, we ask the research question of whether all the datasets ...

Yang Xiao, et al. ∙

research

∙ 08/18/2019

PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment

Despite the great progress made by deep CNNs in image semantic segmentat...

Kaixin Wang, et al. ∙

research

∙ 11/11/2019

MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams

Given a stream of graph edges from a dynamic graph, how can we assign an...

Siddharth Bhatia, et al. ∙

research

∙ 09/16/2019

A Characteristic Function Approach to Deep Implicit Generative Modeling

In this paper, we formulate the problem of learning an Implicit Generati...

Abdul Fatir Ansari, et al. ∙

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