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

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

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

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

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

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

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

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

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

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

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

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

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

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...

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

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

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...

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...

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

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