McGill University

∙ Montreal , Canada ∙ 0 followers

The Mining and Metallurgical Engineering department at McGill University has a wide range of research activities from mining, mineral, and metal processing to advanced materials. They solve problems for companies in return for financial support for research activities. Predominant research areas in the mineral processing group, led by three professors with 20 graduate students and post-doctoral fellows, include: Environmental control: application of mineral processing techniques to waste remediation, environmental restoration, secondary metal recovery and recycling. Powder technology: size reduction of rocks and ores, characterization of breakage behaviour. Particulate processing: solid/solid and solid/liquid separations based on physical and chemical properties such as size, density, wettability, magnetic and dielectric properties, etc. Surface chemistry: investigation and modification of surface properties of particulate systems for varied applications, such as fibre optics, biosensors and bioseparations. Process control: development of sensing techniques and control strategies for process optimization.

Detecting GAN generated errors

Despite an impressive performance from the latest GAN for generating hyp...
12/02/2019 ∙ by Xiru Zhu, et al. ∙ 71 ∙ share

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Instance Segmentation based Semantic Matting for Compositing Applications

Image compositing is a key step in film making and image editing that ai...
04/10/2019 ∙ by Guanqing Hu, et al. ∙ 48 ∙ share

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Boosting Image Recognition with Non-differentiable Constraints

In this paper, we study the problem of image recognition with non-differ...
10/02/2019 ∙ by Xuan Li, et al. ∙ 38 ∙ share

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Avoidance Learning Using Observational Reinforcement Learning

Imitation learning seeks to learn an expert policy from sampled demonstr...
09/24/2019 ∙ by David Venuto, et al. ∙ 29 ∙ share

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TarMAC: Targeted Multi-Agent Communication

We explore a collaborative multi-agent reinforcement learning setting wh...
10/26/2018 ∙ by Abhishek Das, et al. ∙ 22 ∙ share

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Uncertainty Evaluation Metric for Brain Tumour Segmentation

In this paper, we develop a metric designed to assess and rank uncertain...
05/28/2020 ∙ by Raghav Mehta, et al. ∙ 20 ∙ share

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Empirical confidence estimates for classification by deep neural networks

How well can we estimate the probability that the classification, C(f(x)...
03/21/2019 ∙ by Chris Finlay, et al. ∙ 18 ∙ share

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Improving Sample Efficiency in Model-Free Reinforcement Learning from Images

Training an agent to solve control tasks directly from high-dimensional ...
10/02/2019 ∙ by Denis Yarats, et al. ∙ 18 ∙ share

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Efficient Graph Generation with Graph Recurrent Attention Networks

We propose a new family of efficient and expressive deep generative mode...
10/02/2019 ∙ by Renjie Liao, et al. ∙ 16 ∙ share

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Marginalized State Distribution Entropy Regularization in Policy Optimization

Entropy regularization is used to get improved optimization performance ...
12/11/2019 ∙ by Riashat Islam, et al. ∙ 15 ∙ share

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FIGR: Few-shot Image Generation with Reptile

Generative Adversarial Networks (GAN) boast impressive capacity to gener...
01/08/2019 ∙ by Louis Clouâtre, et al. ∙ 14 ∙ share

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On the Pitfalls of Measuring Emergent Communication

How do we know if communication is emerging in a multi-agent system? The...
03/12/2019 ∙ by Ryan Lowe, et al. ∙ 14 ∙ share

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Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking

The ability to detect and track objects in the visual world is a crucial...
11/20/2019 ∙ by Eric Crawford, et al. ∙ 14 ∙ share

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Options of Interest: Temporal Abstraction with Interest Functions

Temporal abstraction refers to the ability of an agent to use behaviours...
01/01/2020 ∙ by Khimya Khetarpal, et al. ∙ 14 ∙ share

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Optimizing Through Learned Errors for Accurate Sports Field Registration

We propose an optimization-based framework to register sports field temp...
09/17/2019 ∙ by Wei Jiang, et al. ∙ 13 ∙ share

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DeepURL: Deep Pose Estimation Framework for Underwater Relative Localization

In this paper, we propose a real-time deep-learning approach for determi...
03/11/2020 ∙ by Bharat Joshi, et al. ∙ 13 ∙ share

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Using Machine Learning to Automate Mammogram Images Analysis

Breast cancer is the second leading cause of cancer-related death after ...
12/06/2020 ∙ by Xuejiao Tang, et al. ∙ 13 ∙ share

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Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods

Recent analyses of certain gradient descent optimization methods have sh...
10/05/2018 ∙ by Peter Henderson, et al. ∙ 12 ∙ share

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On the Evaluation of Common-Sense Reasoning in Natural Language Understanding

The NLP and ML communities have long been interested in developing model...
11/05/2018 ∙ by Paul Trichelair, et al. ∙ 10 ∙ share

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Learning normalizing flows from Entropy-Kantorovich potentials

We approach the problem of learning continuous normalizing flows from a ...
06/10/2020 ∙ by Chris Finlay, et al. ∙ 9 ∙ share

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Natural Environment Benchmarks for Reinforcement Learning

While current benchmark reinforcement learning (RL) tasks have been usef...
11/14/2018 ∙ by Amy Zhang, et al. ∙ 6 ∙ share

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CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning

Despite recent successes of reinforcement learning (RL), it remains a ch...
10/08/2020 ∙ by Ossama Ahmed, et al. ∙ 5 ∙ share

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Weakly Supervised Object Localization using Min-Max Entropy: an Interpretable Framework

Weakly supervised object localization (WSOL) models aim to locate object...
07/25/2019 ∙ by Soufiane Belharbi, et al. ∙ 4 ∙ share

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No Press Diplomacy: Modeling Multi-Agent Gameplay

Diplomacy is a seven-player non-stochastic, non-cooperative game, where ...
09/04/2019 ∙ by Philip Paquette, et al. ∙ 4 ∙ share

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Deterministic Gaussian Averaged Neural Networks

We present a deterministic method to compute the Gaussian average of neu...
06/10/2020 ∙ by Ryan Campbell, et al. ∙ 4 ∙ share

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Algorithmic Improvements for Deep Reinforcement Learning applied to Interactive Fiction

Text-based games are a natural challenge domain for deep reinforcement l...
11/28/2019 ∙ by Vishal Jain, et al. ∙ 3 ∙ share

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Local semi-supervised approach to brain tissue classification in child brain MRI

Most segmentation methods in child brain MRI are supervised and are base...
05/20/2020 ∙ by Nataliya Portman, et al. ∙ 3 ∙ share

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Locally Persistent Exploration in Continuous Control Tasks with Sparse Rewards

A major challenge in reinforcement learning is the design of exploration...
12/26/2020 ∙ by Susan Amin, et al. ∙ 3 ∙ share

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Quaternion Convolutional Neural Networks for End-to-End Automatic Speech Recognition

Recently, the connectionist temporal classification (CTC) model coupled ...
06/20/2018 ∙ by Titouan Parcollet, et al. ∙ 2 ∙ share

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The relativistic discriminator: a key element missing from standard GAN

In standard generative adversarial network (SGAN), the discriminator est...
07/02/2018 ∙ by Alexia Jolicoeur-Martineau, et al. ∙ 2 ∙ share

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Adversarial Geometry and Lighting using a Differentiable Renderer

Many machine learning classifiers are vulnerable to adversarial attacks,...
08/08/2018 ∙ by Hsueh-Ti Derek Liu, et al. ∙ 2 ∙ share

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Sequence Level Semantics Aggregation for Video Object Detection

Video objection detection (VID) has been a rising research direction in ...
07/15/2019 ∙ by Haiping Wu, et al. ∙ 2 ∙ share

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Intervention Design for Effective Sim2Real Transfer

The goal of this work is to address the recent success of domain randomi...
12/03/2020 ∙ by Melissa Mozifian, et al. ∙ 2 ∙ share

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The Causal Frame Problem: An Algorithmic Perspective

The Frame Problem (FP) is a puzzle in philosophy of mind and epistemolog...
01/26/2017 ∙ by Ardavan Salehi Nobandegani, et al. ∙ 1 ∙ share

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Language GANs Falling Short

Generating high-quality text with sufficient diversity is essential for ...
11/06/2018 ∙ by Massimo Caccia, et al. ∙ 1 ∙ share

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Adversarial Boot Camp: label free certified robustness in one epoch

Machine learning models are vulnerable to adversarial attacks. One appro...
10/05/2020 ∙ by Ryan Campbell, et al. ∙ 1 ∙ share

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A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues

Sequential data often possesses a hierarchical structure with complex de...
05/19/2016 ∙ by Iulian Vlad Serban, et al. ∙ 0 ∙ share

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Modeling User Exposure in Recommendation

Collaborative filtering analyzes user preferences for items (e.g., books...
10/23/2015 ∙ by Dawen Liang, et al. ∙ 0 ∙ share

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A Low-Power Content-Addressable-Memory Based on Clustered-Sparse-Networks

A low-power Content-Addressable-Memory (CAM) is introduced employing a n...
02/18/2013 ∙ by Hooman Jarollahi, et al. ∙ 0 ∙ share

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Learnings Options End-to-End for Continuous Action Tasks

We present new results on learning temporally extended actions for conti...
11/30/2017 ∙ by Martin Klissarov, et al. ∙ 0 ∙ share

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Exploration in NetHack with Secret Discovery

Roguelike games generally feature exploration problems as a critical, ye...
11/08/2017 ∙ by Jonathan C. Campbell, et al. ∙ 0 ∙ share

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SIMILARnet: Simultaneous Intelligent Localization and Recognition Network

Global Average Pooling (GAP) [4] has been used previously to generate cl...
11/08/2017 ∙ by Arna Ghosh, et al. ∙ 0 ∙ share

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Adaptive coordination of working-memory and reinforcement learning in non-human primates performing a trial-and-error problem solving task

Accumulating evidence suggest that human behavior in trial-and-error lea...
11/02/2017 ∙ by Guillaume Viejo, et al. ∙ 0 ∙ share

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Long-Distance Loop Closure Using General Object Landmarks

Visual localization under large changes in scale is an important capabil...
10/28/2017 ∙ by Andrew Holliday, et al. ∙ 0 ∙ share

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Ubenwa: Cry-based Diagnosis of Birth Asphyxia

Every year, 3 million newborns die within the first month of life. Birth...
11/17/2017 ∙ by Charles C Onu, et al. ∙ 0 ∙ share

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Personalization of Saliency Estimation

Most existing saliency models use low-level features or task description...
11/21/2017 ∙ by Bingqing Yu, et al. ∙ 0 ∙ share

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WAYLA - Generating Images from Eye Movements

We present a method for reconstructing images viewed by observers based ...
11/21/2017 ∙ by Bingqing Yu, et al. ∙ 0 ∙ share

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Bayesian Hypernetworks

We propose Bayesian hypernetworks: a framework for approximate Bayesian ...
10/13/2017 ∙ by David Krueger, et al. ∙ 0 ∙ share

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Alpha-Divergences in Variational Dropout

We investigate the use of alternative divergences to Kullback-Leibler (K...
11/12/2017 ∙ by Bogdan Mazoure, et al. ∙ 0 ∙ share

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ASR error management for improving spoken language understanding

This paper addresses the problem of automatic speech recognition (ASR) e...
05/26/2017 ∙ by Edwin Simonnet, et al. ∙ 0 ∙ share

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