School of Mathematics and Statistics - Research Publications
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ItemNo Preview AvailableKnowledge Distillation for Feature Extraction in Underwater VSLAM(IEEE, 2023-01-01)
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ItemNo Preview AvailableBenchmarking algorithm portfolio construction methods(Association for Computing Machinery, 2022-07-09)A portfolio is a set of algorithms, which run concurrently or interchangeably, whose aim is to improve performance by avoiding a bad selection of a single algorithm. Despite its high error tolerance, a carefully constructed portfolio, i.e., the smallest set of complementary algorithms, is expected to perform better than an arbitrarily constructed one. In this paper, we benchmark five algorithm portfolio construction methods, using as benchmark problems the ASLib scenarios, under a cross-validation regime. We examine the performance of each portfolio in terms of its riskiness, i.e., the existence of unsolved problems on the test set, and its robustness, i.e., the existence of an algorithm that solves most instances. The results demonstrate that two of these methods produce portfolios with the lowest risk, albeit with different levels of robustness.
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ItemNo Preview AvailableProgressive Video Summarization via Multimodal Self-supervised Learning(IEEE, 2023-01-01)
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ItemNo Preview AvailableMaximum Spatial Perturbation Consistency for Unpaired Image-to-Image Translation(IEEE COMPUTER SOC, 2022-01-01)
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ItemNo Preview AvailableAlleviating Semantics Distortion in Unsupervised Low-Level Image-to-Image Translation via Structure Consistency Constraint(IEEE COMPUTER SOC, 2022-01-01)
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ItemNo Preview AvailableOff-lattice and parallel implementations of the pivot algorithm(IOP Publishing, 2021-12-09)Abstract The pivot algorithm is the most efficient known method for sampling polymer configurations for self-avoiding walks and related models. Here we introduce two recent improvements to an efficient binary tree implementation of the pivot algorithm: an extension to an off-lattice model, and a parallel implementation.
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ItemSemiglobal Practical Stability of a Class of Parameterized Networked Control Systems(IEEE, 2012-01-01)This paper studies a class of parameterized networked control systems that are designed via an emulation procedure. In the first step, a controller is designed ignoring network so that semiglobal practical stability is achieved for the closed-loop. In the second step, it is shown that if the same controller is emulated and implemented over a large class of networks, then the networked control system is also semiglobally practically asymptotically stable; in this case, the controller parameter needs to be sufficiently small and communication bandwidth sufficiently high.
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ItemDifferential operators on modular forms mod p(RIMS, 2019)We give a survey of recent work on the construction of differential operators on various types of modular forms (mod p) . We also discuss a framework for determining the effect of such operators on the mod p Galois representations attached to Hecke eigenforms.