Dalhousie University

∙ Halifax , Canada ∙ 0 followers

59167 Dalhousie University is a public research university in Nova Scotia, Canada, with three campuses in Halifax, a fourth in Bible Hill, and medical teaching facilities in Saint John, New Brunswick.

Representational Rényi heterogeneity

A discrete system's heterogeneity is measured by the Rényi heterogeneity...
12/10/2019 ∙ by Abraham Nunes, et al. ∙ 30 ∙ share

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Visual Feature Fusion and its Application to Support Unsupervised Clustering Tasks

On visual analytics applications, the concept of putting the user on the...
01/16/2019 ∙ by Gladys Hilasaca, et al. ∙ 14 ∙ share

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Marine Mammal Species Classification using Convolutional Neural Networks and a Novel Acoustic Representation

Research into automated systems for detecting and classifying marine mam...
07/30/2019 ∙ by Mark Thomas, et al. ∙ 2 ∙ share

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A Novel Model for Arbitration between Planning and Habitual Control Systems

It is well established that humans decision making and instrumental cont...
12/06/2017 ∙ by Farzaneh S. Fard, et al. ∙ 0 ∙ share

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TrajectoryNet: An Embedded GPS Trajectory Representation for Point-based Classification Using Recurrent Neural Networks

Understanding and discovering knowledge from GPS (Global Positioning Sys...
05/07/2017 ∙ by Xiang Jiang, et al. ∙ 0 ∙ share

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Reflexive Regular Equivalence for Bipartite Data

Bipartite data is common in data engineering and brings unique challenge...
02/16/2017 ∙ by Aaron Gerow, et al. ∙ 0 ∙ share

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Statistical Learning for OCR Text Correction

The accuracy of Optical Character Recognition (OCR) is crucial to the su...
11/21/2016 ∙ by Jie Mei, et al. ∙ 0 ∙ share

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Avoiding Confusion between Predictors and Inhibitors in Value Function Approximation

In reinforcement learning, the goal is to seek rewards and avoid punishm...
12/19/2013 ∙ by Patrick C. Connor, et al. ∙ 0 ∙ share

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A Characterization of the Combined Effects of Overlap and Imbalance on the SVM Classifier

In this paper we demonstrate that two common problems in Machine Learnin...
09/16/2011 ∙ by Misha Denil, et al. ∙ 0 ∙ share

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Using a Dynamic Neural Field Model to Explore a Direct Collicular Inhibition Account of Inhibition of Return

When the interval between a transient ash of light (a "cue") and a secon...
07/22/2013 ∙ by Jason Satel, et al. ∙ 0 ∙ share

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Vector Embedding of Wikipedia Concepts and Entities

Using deep learning for different machine learning tasks such as image c...
02/12/2017 ∙ by Ehsan Sherkat, et al. ∙ 0 ∙ share

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Interpretable Deep Convolutional Neural Networks via Meta-learning

Model interpretability is a requirement in many applications in which cr...
02/02/2018 ∙ by Xuan Liu, et al. ∙ 0 ∙ share

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One Single Deep Bidirectional LSTM Network for Word Sense Disambiguation of Text Data

Due to recent technical and scientific advances, we have a wealth of inf...
02/25/2018 ∙ by Ahmad Pesaranghader, et al. ∙ 0 ∙ share

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The Importance of Constraint Smoothness for Parameter Estimation in Computational Cognitive Modeling

Psychiatric neuroscience is increasingly aware of the need to define psy...
03/24/2018 ∙ by Abraham Nunes, et al. ∙ 0 ∙ share

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On the Importance of Attention in Meta-Learning for Few-Shot Text Classification

Current deep learning based text classification methods are limited by t...
06/03/2018 ∙ by Xiang Jiang, et al. ∙ 0 ∙ share

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Dependently Typed Folds for Nested Data Types

We present an approach to develop folds for nested data types using depe...
06/13/2018 ∙ by Peng Fu, et al. ∙ 0 ∙ share

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On feature selection and evaluation of transportation mode prediction strategies

Transportation modes prediction is a fundamental task for decision makin...
08/09/2018 ∙ by Mohammad Etemad, et al. ∙ 0 ∙ share

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Recovery guarantees for polynomial approximation from dependent data with outliers

Learning non-linear systems from noisy, limited, and/or dependent data i...
11/25/2018 ∙ by Lam Si Tung Ho, et al. ∙ 0 ∙ share

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Improving the Interpretability of Deep Neural Networks with Knowledge Distillation

Deep Neural Networks have achieved huge success at a wide spectrum of ap...
12/28/2018 ∙ by Xuan Liu, et al. ∙ 0 ∙ share

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2-D Embedding of Large and High-dimensional Data with Minimal Memory and Computational Time Requirements

In the advent of big data era, interactive visualization of large data s...
02/04/2019 ∙ by Witold Dzwinel, et al. ∙ 0 ∙ share

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EL Embeddings: Geometric construction of models for the Description Logic EL ++

An embedding is a function that maps entities from one algebraic structu...
02/27/2019 ∙ by Maxat Kulmanov, et al. ∙ 0 ∙ share

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The conditionally autoregressive hidden Markov model (CarHMM): Inferring behavioural states from animal tracking data exhibiting conditional autocorrelation

One of the central interests of animal movement ecology is relating move...
03/12/2019 ∙ by Ethan Lawler, et al. ∙ 0 ∙ share

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Efficient Neural Task Adaptation by Maximum Entropy Initialization

Transferring knowledge from one neural network to another has been shown...
05/25/2019 ∙ by Farshid Varno, et al. ∙ 0 ∙ share

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(A) Data in the Life: Authorship Attribution of Lennon-McCartney Songs

The songwriting duo of John Lennon and Paul McCartney, the two founding ...
06/12/2019 ∙ by Mark E. Glickman, et al. ∙ 0 ∙ share

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Exploring Conditioning for Generative Music Systems with Human-Interpretable Controls

Performance RNN is a machine-learning system designed primarily for the ...
07/09/2019 ∙ by Nicholas Meade, et al. ∙ 0 ∙ share

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Unsupervised Behavior Change Detection in Multidimensional Data Streams for Maritime Traffic Monitoring

The worldwide growth of maritime traffic and the development of the Auto...
08/14/2019 ∙ by Lucas May Petry, et al. ∙ 0 ∙ share

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Multimodal Deep Learning for Mental Disorders Prediction from Audio Speech Samples

Key features of mental illnesses are reflected in speech. Our research f...
09/03/2019 ∙ by Habibeh Naderi, et al. ∙ 0 ∙ share

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Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters

Time series forecasting is one of the most active research topics. Machi...
09/29/2019 ∙ by Vítor Cerqueira, et al. ∙ 0 ∙ share

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Path and Ancestor Queries on Trees with Multidimensional Weight Vectors

We consider an ordinal tree T on n nodes, with each node assigned a d-...
10/02/2019 ∙ by Meng He, et al. ∙ 0 ∙ share

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Vector Autoregressive Models with Spatially Structured Coefficients for Time Series on a Spatial Grid

We propose a parsimonious spatiotemporal model for time series data on a...
01/07/2020 ∙ by Yuan Yan, et al. ∙ 0 ∙ share

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