### 104 Papers in 2020

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In this paper, we consider both first- and second-order techniques to address continuous optimization problems arising in machine learning. In the first-orde...

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A small polygon is a polygon of unit diameter. The maximal area of a small polygon with $$n=2m$$ vertices is not known when $$m\ge 7$$. Finding the large...

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A small polygon is a polygon of unit diameter. The maximal perimeter and the maximal width of a convex small polygon with $$n=2^s$$ vertices are not known ...

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We introduce iterative methods named TriCG and TriMR for solving symmetric quasi-definite systems based on the orthogonal tridiagonalization process proposed...

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We consider computationally expensive blackbox optimization problems and present a method that employs surrogate models and concurrent computing at the searc...

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Given a set of predefined duties and groups of drivers, the duty assignment problem with group-based driver preferences (DAPGDP) aims at building rosters tha...

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We consider a two-stage game in a differentiated duopoly, where firms can pursue both a financial and an environmental objective. We assume that the maximu...

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We represent a closed-loop supply chain formed of one manufacturer and one retailer as a dynamic game played over an event tree, which naturally allows to ...

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We present ExaPF.jl, a solver for power flow on GPUs, entirely written in Julia. It implements a highly parallel Newton-Raphson solver for nonlinear equati...

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In this paper, we study the time consistency of cooperative agreements in dynamic games with nontransferable utility. An agreement designed at the outset of ...

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We consider the problem of a government that wishes to promote replacing old cars with new ones via a vehicle scrappage program. Since these programs incre...

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We study a class of deterministic two-player nonzero-sum differential games where one player uses piecewise-continuous controls to affect the continuously e...

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GenoGraphiX-Log 2.0 (abbreviation GGXLog) is a keystroke logging software that was developed as a collaboration between <a href="" title="https://www.h...

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We consider logistic collaborations where multiple carriers collaborate by consolidating demands, combining delivery routes, and serving new customers. Logis...

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The crew pairing problem (CPP) is solved in the first step of the crew scheduling process. It consists of creating a set of pairings (sequence of flights, co...

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The personalized crew rostering problem (CRP) consists of assigning pairings (sequences of flights, deadheads, connections, and rests, forming one or several...

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Energy generation has always been a major stake in our economy and is all the more so with the increase in energy demand all over the world. In that context,...

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This paper presents an algorithm for the identification of parameters for a stochastic hot water end-use process that drives a homogeneous population of ther...

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We present LatNet Builder, a software tool to find good parameters for lattice rules, polynomial lattice rules, and digital nets in base 2, for quasi-Monte...

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We study a solution approach for a staffing problem in multi-skill call centers. The objective is to find a minimal-cost staffing solution while meeting a ta...

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Based on data from real call centers, we develop, test, and compare forecasting methods to predict the waiting time of a call upon its arrival to the center,...

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We empirically test the prediction of Pastor, stambaugh, and Taylor (2020) that green firms outperform brown firms when concerns about climate change increas...

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Demand response (DR) has been increasingly growing in significance among the solutions to tackle climate change, along with the development of intermittent r...

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In this paper, we propose an exact branch-price-and-cut (BPC) algorithm for the two-echelon vehicle routing problem with time windows. This problem arises i...

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This paper proposes a way to combine the Mesh Adaptive Direct Search (MADS) algorithm with the Cross-Entropy (CE) method for non smooth constrained optimizat...

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This work introduces the StoMADS-PB algorithm for constrained stochastic blackbox optimization, which is an extension of the mesh adaptive direct-search (MAD...

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Generation expansion planning (GEP) is a classical problem that determines an optimal investment plan for existing and future electricity generation technolo...

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We consider the problem of designing vehicle routes in a distribution system that are at the same time cost-effective and visually attractive. In this pape...

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This work investigates lot-sizing with component substitution under demand uncertainty. The integration of component substitution with lot-sizing in an uncer...

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Scholars and practitioners have long recognised the importance of data-driven operations and supply chain management (OSCM), which typically centres on produ...

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Berth allocation and pilotage planning are the two most important decisions made by a seaport for serving incoming vessels. Traditionally, the berth allocati...

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We study a new variant of the well-studied Vehicle Routing Problem with Time Windows (VRPTW), called the fragility-constrained VRPTW, which assumes that ...

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This work reviews blackbox optimization applications over the last twenty years, addressed using direct search optimization methods. Emphasis is placed on...

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Two-stage stochastic programs are a class of stochastic problems where data uncertainty is often discretized into scenarios, making them amenable to solution...

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Data acquisition and recording in the form of databases are routine operations. The process of collecting data, however, may experience irregularities, res...

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This paper studies disjunctive cutting planes in Mixed-Integer Conic Programming. Building on conic duality, we formulate a cut-generating conic program for...

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We propose a new stochastic variance-reduced damped L-BFGS algorithm, where we leverage estimates of bounds on the largest and smallest eigenvalues of the He...

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The Ninth Montreal IPSW took place on August 19-23, 2019, and was jointly organized by the CRM and IVADO (Institute for Data Valorization). The workshop welc...

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We consider a deterministic two-player linear-state differential game, where Player 1 uses piecewise continuous controls, while Player 2 implements impulse...

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Conditional estimation given specific covariate values (i.e., local conditional estimation or functional estimation) is ubiquitously useful with applications...

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In this paper, we consider the problem of equal risk pricing and hedging in which the fair price of an option is the price that exposes both sides of the con...

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In this paper, we propose a simple oligopoly game model to represent the interactions between coalitions of countries in deploying Carbon Dioxide Removal ...

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In recent years, we have witnessed a mini-revolution around early-stage financing. In some places, like the UK, more money is raised on Equity Crowdfunding...

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We study a distributionally robust version of the classical capacitated facility location problem with a distributional ambiguity set defined as a Wasserst...

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We study a new variant of the vehicle routing problem, which arises in hospital-wide scheduling of physical therapists. Multiple service locations exist for...

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Aggregator is an open-source python package which aims to facilitate the exploitation of relational datasets by automating feature aggregation.

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The design of key nonlinear systems often requires the use of expensive blackbox simulations presenting inherent discontinuities whose positions in the varia...

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We present a modeling of bundle adjustment problems in Julia, as well as a solver for non-linear least square problems (including bundle adjustment problems)...

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In several countries, electricity systems are under strong decarbonization pressure. In particular, the Canadian provinces of Quebec and Ontario as well as t...

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We consider the iterative solution of regularized saddle-point systems. When the leading block is symmetric and positive semi-definite on an appropriate sub...

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In this paper, we introduce a framework for new product dfiffusion that integrates consumer heterogeneity and strategic interactions at individual level. For...

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Let $$G=(V,E)$$ be a graph and let $$S\subseteq V$$ be a subset of its vertices. If the subgraph of $$G$$ induced by $$V\setminus S$$ is acyclic, the...

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A new business opportunity is emerging with the combination of three key market trends: (1) Increased penetration of residential solar PV; (2) Rapid reductio...

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Restless bandits are a class of sequential resource allocation problems concerned with allocating one or more resources among several alternative processes...

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We consider an integrated optimization problem including the production, inventory, and outbound transportation decisions where a central plant fulfills the ...

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Column generation (CG) algorithms are well known to suffer from convergence issues due, mainly, to the degenerate structure of their master problem and the ...

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The Mars Curiosity rover is frequently sending back engineering and science data that goes through a pipeline of systems before reaching its final destinati...

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In this paper, we apply a flexibility based operational planning paradigm to microgrid (MG) energy dispatch. The classic energy dispatch problem with energ...

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We provide eigenvalues bounds for a new formulation of the step equations in interior methods for convex quadratic optimization. The matrix of our formulati...

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Utility-based shortfall risk measure (SR) effectively captures decision maker’s risk attitude on tail losses by an increasing convex loss function. In this ...

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Column generation (CG) is widely used for solving large-scale optimization problems. This article presents a new approach based on a machine learning (ML) t...

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Deep learning has redefined modern standards and performance in several areas such as computer vision and natural language processing. With increasing amou...

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Artificial Intelligence (AI) is the next society transformation builder. Massive AI-based applications include cloud servers, cell phones, cars, and pandemic...

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The accessibility and reducing cost of distributed renewable energy sources are stimulating the emergence of small-scale residential prosumers who can produc...

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The monthly crew pairing problem (CPP) consists of determining a least-cost set of feasible crew pairings (sequences of flights starting and ending at a crew...

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Maintenance planning for hydropower plants is a crucial problem. In this paper, we evaluate the impact of the Hydropower Production Function (HPF) formulatio...

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Cities worldwide struggle with overloaded transportation systems and their externalities, such as traffic congestion and emissions. The emerging technology o...

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Traditionally, the design of supply chains for humanitarian operations has been developed distinctly for the different disaster management phases, with littl...

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The context of this research is multiobjective optimization where conflicting objectives are present. In this work, these objectives are only available as th...

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The popularity of drones is rapidly increasing across the different sectors of the economy. Aerial capabilities and relatively low costs make drones the perf...

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In the area of hydraulic power generation, there is a great deal of interest in two interdependent domains: operation and maintenance. This interdependence...

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Implementation of quantized neural networks on computing hardware leads to considerable speed up and memory saving. However, quantized deep networks are diff...

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Convolutional Neural Networks (CNNs) are state-of-the-art in numerous computer vision tasks such as object classification and detection. However, the large ...

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We introduce a novel ensemble learning approach which combines random partitions models through Potts clustering with a non-parametric predictor such as sha...

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Deep neural networks usually have unnecessarily high complexities and possibly many features of low utility, especially for tasks that they are not designed ...

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The determinantal point process (DPP) provides a promising and attractive alternative to simple random sampling in cluster analysis or classification, for th...

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Min-max formulations have attracted great attention in the ML community due to the rise of deep generative models and adversarial methods, while understandin...

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Binary neural networks improve computationally efficiency of deep models with a large margin. However, there is still a performance gap between a successful...

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Training large-scale deep neural networks is a long, time-consuming operation, often requiring many GPUs to accelerate. In large models, the time spent loadi...

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In time-to-event data analysis, the main object of interest is the time elapsed between the occurrence of two ordered events, say $$E_1, E_2$$. Sampling fr...

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Knowledge distillation is a technique that consists in training a student network, usually of a low capacity, to mimic the representation space and the perfo...

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The design of compact deep neural networks is a crucial task to enable widespread adoption of deep neural networks in the real-world, particularly for edge a...

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The past few years have seen the ability of cooperative Malware Detection Systems (MDS) to detect complex and unknown malware. In a cooperative setting, an M...

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Pruning methods for deep neural networks based on weight magnitude have shown promise in recent research. We propose a new, highly flexible approach to neura...

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One of the major challenges in large-scale distributed machine learning involving stochastic gradient methods is the high cost of gradient communication ove...

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The smooth operation of largely deployed Internet of Things (IoT) applications will depend on, among other things, effective infrastructure failure detectio...

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This work presents the convergence rate analysis of stochastic variants of the broad class of direct-search methods of directional type. It introduces an alg...

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Conditional Value at Risk (CVaR) is widely used to account for the preferences of a risk-averse agent in the extreme loss scenarios. To study the effectiven...

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This paper proposes a detailed analysis of the evolution of Canadian energy systems under some selected EMF (Energy Modeling Forum) 34 scenarios. Our analysi...

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Quebec and Canada at large face difficult challenges to adapt and compete in the upcoming data driven economy. Many analysts already consider the game to be ...

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The crew pairing problem is generally modelled as a set partitioning problem where the flights have to be partitioned in pairings. A pairing is a sequence of...

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It is well known that the integrated optimization of multiple and inter-related decisions in a supply chain can bring important benefits to companies. In thi...

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Given a set $$\mathcal{R}$$ of m disjoint finite regions in the 2-dimensional plane, all regions having polygonal boundaries, and given a set (\mathc...

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This work considers the graph partitioning problem known as maximum k-cut. It focuses on investigating features of a branch-and-bound method to efficiently...

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While one can exploit the storage properties and thus the deferability or anticipation potential of many classes of power system loads (such as thermal loads...

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In this paper, we introduce, model and solve the pickup and delivery problem with time windows, multiple stacks, and handling operations (PDPTWMS-H). % In...

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Column generation algorithms for solving vehicle routing problems often rely on a relaxed pricing subproblem where routes may be non-elementary and which is ...

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The energy of a graph $$G$$, denoted by $${\cal E}(G)$$, is defined as the sum of the absolute values of all eigenvalues of $$G$$`. In this paper we stu...

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The solution to a biobjective optimization problem is composed of a collection of trade-off solution called the Pareto set. The present work studies the que...

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Free-Floating Carsharing (FFCS) systems are a promising concept to reduce the traffic volume in cities. However, spatial and temporal mismatches of supply an...

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In this paper we consider a differentiated oligopoly with two product varieties that are supplied by two groups of firms. We assume that firms can change t...

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In this paper we study the spectral properties of the threshold graphs. In particular, we give lower and upper bounds for the largest and smallest eigenvalue...

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Wireless communications can facilitate transfer of synchrophasor data between spatially separated phasor measurement units (PMUs) and phasor data concentrato...

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Networked protection systems use information, communication and computation technologies to collect and process sensor data from spatially distributed sensor...

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