Computer Science
This is the collection for the University of Waterloo's Cheriton School of Computer Science .
Research outputs are organized by type (eg. Master Thesis, Article, Conference Paper).
Waterloo faculty, students, and staff can contact us or visit the UWSpace guide to learn more about depositing their research.
Recent deposits
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Computing lower rank approximations of matrix polynomials
(Elsevier, 2020-05)Given an input matrix polynomial whose coefficients are floating point numbers, we consider the problem of finding the nearest matrix polynomial which has rank at most a specified value. This generalizes the problem of ... -
Incentivizing evaluation with peer prediction and limited access to ground truth
(Elsevier, 2019-10)In many settings, an effective way of evaluating objects of interest is to collect evaluations from dispersed individuals and to aggregate these evaluations together. Some examples are categorizing online content and ... -
The number of valid factorizations of Fibonacci prefixes
(Elsevier, 2019-07-05)We establish several recurrence relations and an explicit formula for V(n), the number of factorizations of the length-n prefix of the Fibonacci word into a (not necessarily strictly) decreasing sequence of standard Fibonacci ... -
Critical exponents of infinite balanced words
(Elsevier, 2019-07-19)Over an alphabet of size 3 we construct an infinite balanced word with critical exponent 2 + root2/2. Over an alphabet of size 4 we construct an infinite balanced word with critical exponent (5 + root5)/4. Over larger ... -
Subword complexity and power avoidance
(Elsevier, 2019-11-05)We begin a systematic study of the relations between subword complexity of infinite words and their power avoidance. Among other things, we show that –the Thue–Morse word has the minimum possible subword complexity over ... -
Complexity of proper prefix-convex regular languages
(Elsevier, 2019-10-01)A language L over an alphabet Σ is prefix-convex if, for any words x,y,z ∈ Σ*, whenever x and xyz are in L, then so is xy. Prefix-convex languages include right-ideal, prefix-closed, and prefix-free languages, which were ... -
Style Recognition in Music with Context Free Grammars and Kolmogorov Complexity
(University of Waterloo, 2020-03-11)The Kolmogorov Complexity of an object is incomputable. But built in its structure is a way to specify description methods of an object that is computable in some sense. Such a description method then can be exploited ... -
Constrained-CNN losses for weakly supervised segmentation
(Elsevier, 2019-05)Weakly-supervised learning based on, e.g., partially labelled images or image-tags, is currently attracting significant attention in CNN segmentation as it can mitigate the need for full and laborious pixel/voxel annotations. ... -
An Efficient Geometric Multigrid Solver for Viscous Liquids
(ACM, 2019-07)We present an efficient geometric Multigrid solver for simulating viscous liquids based on the variational approach of Batty and Bridson [2008]. Although the governing equations for viscosity are elliptic, the strong ... -
An adaptive variational finite difference framework for efficient symmetric octree viscosity
(ACM, 2019-07)While pressure forces are often the bottleneck in (near-)inviscid fluid simulations, viscosity can impose orders of magnitude greater computational costs at lower Reynolds numbers. We propose an implicit octree finite ... -
A Unified Simplicial Model for Mixed-Dimensional and Non-Manifold Deformable Elastic Objects
(ACM, 2019-07)We present a unified method to simulate deformable elastic bodies consisting of mixed-dimensional components represented with potentially non-manifold simplicial meshes. Building on well-known simplicial rod, shell, and ... -
A multi-scale model for simulating liquid-fabric interactions
(ACM, 2018-07)We propose a method for simulating the complex dynamics of partially and fully saturated woven and knit fabrics interacting with liquid, including the effects of buoyancy, nonlinear drag, pore (capillary) pressure, dripping, ... -
An Application of Out-of-Distribution Detection for Two-Stage Object Detection Networks
(University of Waterloo, 2020-02-14)Recently, much research has been published for detecting when a classification neural network is presented with data that does not fit into one of the class labels the network learned at train time. These so-called ... -
A multi-scale model for coupling strands with shear-dependent liquid
(ACM, 2019-11)We propose a framework for simulating the complex dynamics of strands interacting with compressible, shear-dependent liquids, such as oil paint, mud, cream, melted chocolate, and pasta sauce. Our framework contains three ... -
Mandoline: robust cut-cell generation for arbitrary triangle meshes
(ACM, 2019-11)Although geometry arising "in the wild" most often comes in the form of a surface representation, a plethora of geometrical and physical applications require the construction of volumetric embeddings either of the geometry ... -
Learning Filters for the 2D Wavelet Transform
(IEEE, 2018)We propose a new method for learning filters for the 2D discrete wavelet transform. We extend our previous work on the 1D wavelet transform in order to process images. We show that the 2D wavelet transform can be represented ... -
Training Reject-Classifiers for Out-of-distribution Detection via Explicit Boundary Sample Generation
(University of Waterloo, 2020-01-24)Discriminatively trained neural classifiers can be trusted only when the input data comes from the training distribution (in-distribution). Therefore, detecting out-of-distribution (OOD) samples is very important to avoid ... -
Optimizing MPI Collective Operations for Cloud Deployments
(University of Waterloo, 2020-01-24)Cloud infrastructures are increasingly being adopted as a platform for high performance computing (HPC) science and engineering applications. For HPC applications, the Message-Passing Interface (MPI) is widely-used. Among ... -
Safety-Oriented Stability Biases for Continual Learning
(University of Waterloo, 2020-01-24)Continual learning is often confounded by “catastrophic forgetting” that prevents neural networks from learning tasks sequentially. In the case of real world classification systems that are safety-validated prior to ... -
Closing the Modelling Gap: Transfer Learning from a Low-Fidelity Simulator for Autonomous Driving
(University of Waterloo, 2020-01-24)The behaviour planning subsystem, which is responsible for high-level decision making and planning, is an important aspect of an autonomous driving system. There are advantages to using a learned behaviour planning system ...
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