Monash University

∙ Clayton , Australia ∙ 0 followers

Monash has achieved an enviable national and international reputation for research and teaching excellence in a short 50 years.

InceptionTime: Finding AlexNet for Time Series Classification

Time series classification (TSC) is the area of machine learning interes...
09/11/2019 ∙ by Hassan Ismail Fawaz, et al. ∙ 135 ∙ share

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A Bayesian-inspired, deep learning, semi-supervised domain adaptation technique for land cover mapping

Land cover maps are a vital input variable to many types of environmenta...
05/25/2020 ∙ by Benjamin Lucas, et al. ∙ 38 ∙ share

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Low radiation tomographic reconstruction with and without template information

Low-dose tomography is highly preferred in medical procedures for its re...
12/23/2019 ∙ by Preeti Gopal, et al. ∙ 33 ∙ share

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Hierarchical forecast reconciliation with machine learning

Hierarchical forecasting methods have been widely used to support aligne...
06/03/2020 ∙ by Evangelos Spiliotis, et al. ∙ 30 ∙ share

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Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions

Deep neural network image classifiers are reported to be susceptible to ...
10/03/2019 ∙ by He Zhao, et al. ∙ 22 ∙ share

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Blockwisely Supervised Neural Architecture Search with Knowledge Distillation

Neural Architecture Search (NAS), aiming at automatically designing netw...
11/29/2019 ∙ by Changlin Li, et al. ∙ 19 ∙ share

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Speak2Label: Using Domain Knowledge for Creating a Large Scale Driver Gaze Zone Estimation Dataset

Labelling of human behavior analysis data is a complex and time consumin...
04/13/2020 ∙ by Shreya Ghosh, et al. ∙ 19 ∙ share

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Active Preference Learning using Maximum Regret

We study active preference learning as a framework for intuitively speci...
05/08/2020 ∙ by Nils Wilde, et al. ∙ 19 ∙ share

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LSTM-MSNet: Leveraging Forecasts on Sets of Related Time Series with Multiple Seasonal Patterns

Generating forecasts for time series with multiple seasonal cycles is an...
09/10/2019 ∙ by Kasun Bandara, et al. ∙ 17 ∙ share

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Generating Semantic Adversarial Examples via Feature Manipulation

The vulnerability of deep neural networks to adversarial attacks has bee...
01/06/2020 ∙ by Shuo Wang, et al. ∙ 15 ∙ share

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Learning Coupled Policies for Simultaneous Machine Translation

In simultaneous machine translation, the system needs to incrementally g...
02/11/2020 ∙ by Philip Arthur, et al. ∙ 15 ∙ share

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A Survey on Knowledge Graphs: Representation, Acquisition and Applications

Human knowledge provides a formal understanding of the world. Knowledge ...
02/02/2020 ∙ by Shaoxiong Ji, et al. ∙ 13 ∙ share

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OIAD: One-for-all Image Anomaly Detection with Disentanglement Learning

Anomaly detection aims to recognize samples with anomalous and unusual p...
01/18/2020 ∙ by Shuo Wang, et al. ∙ 12 ∙ share

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ZSTAD: Zero-Shot Temporal Activity Detection

An integral part of video analysis and surveillance is temporal activity...
03/12/2020 ∙ by Lingling Zhang, et al. ∙ 12 ∙ share

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Adversarial Graph Embeddings for Fair Influence Maximization over Social Networks

Influence maximization is a widely studied topic in network science, whe...
05/08/2020 ∙ by Moein Khajehnejad, et al. ∙ 11 ∙ share

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Not made for each other- Audio-Visual Dissonance-based Deepfake Detection and Localization

We propose detection of deepfake videos based on the dissimilarity betwe...
05/29/2020 ∙ by Komal Chugh, et al. ∙ 11 ∙ share

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OpenGAN: Open Set Generative Adversarial Networks

Many existing conditional Generative Adversarial Networks (cGANs) are li...
03/18/2020 ∙ by Luke Ditria, et al. ∙ 10 ∙ share

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Understanding Aesthetic Evaluation using Deep Learning

A bottleneck in any evolutionary art system is aesthetic evaluation. Man...
04/15/2020 ∙ by Jon McCormack, et al. ∙ 9 ∙ share

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Towards effective AI-powered agile project management

The rise of Artificial intelligence (AI) has the potential to significan...
12/27/2018 ∙ by Hoa Khanh Dam, et al. ∙ 8 ∙ share

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Auxiliary Signal-Guided Knowledge Encoder-Decoder for Medical Report Generation

Beyond the common difficulties faced in the natural image captioning, me...
06/06/2020 ∙ by Mingjie Li, et al. ∙ 8 ∙ share

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LoRMIkA: Local Rule-based Model Interpretability with k-optimal Associations

As we rely more and more on machine learning models for real-life decisi...
08/11/2019 ∙ by Dilini Rajapaksha, et al. ∙ 7 ∙ share

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Real-time Fruit Recognition and Grasp Estimation for Autonomous Apple harvesting

In this research, a fully neural network based visual perception framewo...
03/30/2020 ∙ by Hanwen Kang, et al. ∙ 7 ∙ share

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Improving Adversarial Robustness by Enforcing Local and Global Compactness

The fact that deep neural networks are susceptible to crafted perturbati...
07/10/2020 ∙ by Anh Bui, et al. ∙ 7 ∙ share

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ENG: End-to-end Neural Geometry for Robust Depth and Pose Estimation using CNNs

Recovering structure and motion parameters given a image pair or a seque...
07/16/2018 ∙ by Thanuja Dharmasiri, et al. ∙ 6 ∙ share

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Searching with Consistent Prioritization for Multi-Agent Path Finding

We study prioritized planning for Multi-Agent Path Finding (MAPF). Exist...
12/15/2018 ∙ by Hang Ma, et al. ∙ 6 ∙ share

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Adversarial Graph Embeddings for Fair Influence Maximization over SocialNetworks

Influence maximization is a widely studied topic in network science, whe...
05/08/2020 ∙ by Moein Khajehnejad, et al. ∙ 5 ∙ share

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Seasonal Averaged One-Dependence Estimators: A Novel Algorithm to Address Seasonal Concept Drift in High-Dimensional Stream Classification

Stream classification methods classify a continuous stream of data as ne...
06/27/2020 ∙ by Rakshitha Wathsadini Godahewa, et al. ∙ 5 ∙ share

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Expert Training: Task Hardness Aware Meta-Learning for Few-Shot Classification

Deep neural networks are highly effective when a large number of labeled...
07/13/2020 ∙ by Yucan Zhou, et al. ∙ 5 ∙ share

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Faster and More Robust Mesh-based Algorithms for Obstacle k-Nearest Neighbour

We are interested in the problem of finding k nearest neighbours in the ...
08/13/2018 ∙ by Shizhe Zhao, et al. ∙ 4 ∙ share

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Position Paper: From Multi-Agent Pathfinding to Pipe Routing

The 2D Multi-Agent Path Finding (MAPF) problem aims at finding collision...
05/21/2019 ∙ by Gleb Belov, et al. ∙ 4 ∙ share

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Bridge the Domain Gap Between Ultra-wide-field and Traditional Fundus Images via Adversarial Domain Adaptation

For decades, advances in retinal imaging technology have enabled effecti...
03/23/2020 ∙ by Lie Ju, et al. ∙ 3 ∙ share

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Differentially Private Representation for NLP: Formal Guarantee and An Empirical Study on Privacy and Fairness

It has been demonstrated that hidden representation learned by a deep mo...
10/03/2020 ∙ by Lingjuan Lyu, et al. ∙ 3 ∙ share

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Traversing Latent Space using Decision Ferns

The practice of transforming raw data to a feature space so that inferen...
12/06/2018 ∙ by Yan Zuo, et al. ∙ 2 ∙ share

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EMPNet: Neural Localisation and Mapping using Embedded Memory Points

Continuously estimating an agent's state space and a representation of i...
07/31/2019 ∙ by Gil Avraham, et al. ∙ 2 ∙ share

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Exploring Bottom-up and Top-down Cues with Attentive Learning for Webly Supervised Object Detection

Fully supervised object detection has achieved great success in recent y...
03/22/2020 ∙ by Zhonghua Wu, et al. ∙ 2 ∙ share

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Losing Confidence in Quality: Unspoken Evolution of Computer Vision Services

Recent advances in artificial intelligence (AI) and machine learning (ML...
06/18/2019 ∙ by Alex Cummaudo, et al. ∙ 1 ∙ share

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Predicting proximity with ambient mobile sensors for non-invasive health diagnostics

Modern smart phones are becoming helpful in the areas of Internet-Of-Thi...
12/10/2015 ∙ by Sylvester Olubolu Orimaye, et al. ∙ 0 ∙ share

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Tomographic Reconstruction using Global Statistical Prior

Recent research in tomographic reconstruction is motivated by the need t...
12/06/2017 ∙ by Preeti Gopal, et al. ∙ 0 ∙ share

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Specious rules: an efficient and effective unifying method for removing misleading and uninformative patterns in association rule mining

We present theoretical analysis and a suite of tests and procedures for ...
09/12/2017 ∙ by Wilhelmiina Hämäläinen, et al. ∙ 0 ∙ share

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Word Representation Models for Morphologically Rich Languages in Neural Machine Translation

Dealing with the complex word forms in morphologically rich languages is...
06/14/2016 ∙ by Ekaterina Vylomova, et al. ∙ 0 ∙ share

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Accurate parameter estimation for Bayesian Network Classifiers using Hierarchical Dirichlet Processes

This paper introduces a novel parameter estimation method for the probab...
08/25/2017 ∙ by Francois Petitjean, et al. ∙ 0 ∙ share

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RKL: a general, invariant Bayes solution for Neyman-Scott

Neyman-Scott is a classic example of an estimation problem with a partia...
07/20/2017 ∙ by Michael Brand, et al. ∙ 0 ∙ share

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Towards Decoding as Continuous Optimization in Neural Machine Translation

We propose a novel decoding approach for neural machine translation (NMT...
01/11/2017 ∙ by Cong Duy Vu Hoang, et al. ∙ 0 ∙ share

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A Fast Method For Computing Principal Curvatures From Range Images

Estimation of surface curvature from range data is important for a range...
07/03/2017 ∙ by Andrew Spek, et al. ∙ 0 ∙ share

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Joint Pose and Principal Curvature Refinement Using Quadrics

In this paper we present a novel joint approach for optimising surface c...
07/03/2017 ∙ by Andrew Spek, et al. ∙ 0 ∙ share

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Nearest Neighbour Radial Basis Function Solvers for Deep Neural Networks

We present a radial basis function solver for convolutional neural netwo...
05/27/2017 ∙ by Benjamin J. Meyer, et al. ∙ 0 ∙ share

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Latent Variable Discovery Using Dependency Patterns

The causal discovery of Bayesian networks is an active and important res...
07/22/2016 ∙ by Xuhui Zhang, et al. ∙ 0 ∙ share

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Smart Mining for Deep Metric Learning

To solve deep metric learning problems and producing feature embeddings,...
04/05/2017 ∙ by Ben Harwood, et al. ∙ 0 ∙ share

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The IMP game: Learnability, approximability and adversarial learning beyond Σ^0_1

We introduce a problem set-up we call the Iterated Matching Pennies (IMP...
02/07/2016 ∙ by Michael Brand, et al. ∙ 0 ∙ share

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GeoTextTagger: High-Precision Location Tagging of Textual Documents using a Natural Language Processing Approach

Location tagging, also known as geotagging or geolocation, is the proces...
01/22/2016 ∙ by Shawn Brunsting, et al. ∙ 0 ∙ share

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