Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 42 for “"Randomized Algorithms"”.
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Randomized algorithms for reliable broadcast
In this thesis, we design randomized algorithms for classical problems in fault tolerant distributed computing in the full-information model. The full-information model is a strong adversarial model which imposes no restrictions on the computational power of the faulty players nor on the …
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Randomized Algorithms for Mega-AI Models
… an accuracy-efficiency trade-off in current ML algorithms and systems, where reducing computation and memory usage results in accuracy losses during both training and inference. This thesis aims to demonstrate algorithmic advancements in improving this trade-off in training Mega-AI models. …
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Cut structures and randomized algorithms in edge-connectivity problems
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 1997.
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Essays in Problems in Sequential Decisions and Large-Scale Randomized Algorithms
… dissertation, we put forward two large-scale randomized algorithms. We propose a two-step sensing scheme for the low-rank matrix recovery problem which requires far less storage space and has much lower computational complexity than other state-of-art methods based on nuclear norm …
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The power of randomized algorithms : from numerical linear algebra to biological systems
In this thesis we study simple, randomized algorithms from a dual perspective. The first part of the work considers how randomized methods can be used to accelerate the solution of core problems in numerical linear algebra. In particular, we give a randomized low-rank approximation algorithm for …
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On randomized algorithms and their applications in robust optimization: Algoritmos aleatorios y aplicaciones en optimización robusta
Las aéreas que han sido abordadas en la tesis y q se pueden considerar para trabajo futuro son: * Aplicación a CUDA * Aplicaciones de identificación (por ejemplo, a la bolsa de valores) * Aplicación a MPC * Aplicación a las energías renovables * Apli
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Better Hardness via Algorithms, and New Forms of Hardness versus Randomness
… pseudorandomness (the procedure that converts randomized algorithms into equivalent deterministic algorithms). In one direction, from the classic works of Nisan-Widgerson and Impagliazzo-Widgerson, we know certain hardness hypothesis (circuit lower bounds) implies that all randomized algorithms …
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Algorithms on Clustering, Orienteering, and Conflict -Free Coloring
In the last part, we present randomized algorithms for online conflict-free coloring of points in the plane, with respect to intervals, halfplanes, congruent disks, and nearly-equal axis-parallel rectangles. In all these cases, the coloring algorithms use O(log n) colors, with high probability. We …
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Pseudo-determinism
A curious property of randomized algorithms for search problems is that on different executions on the same input, the algorithm may return different outputs due to differences in the internal randomness used by the algorithm. We would like to understand how we can construct randomized algorithms …
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Algorithmic issues in queueing systems and combinatorial counting problems
(cont.) However, these randomized algorithms can never provide proven upper or lower bounds on the number of objects they are counting, but can only give probabilistic estimates. We propose a set of deterministic algorithms for counting such objects for three classes of counting problems. They are …
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Fast approximations for combinatorial optimization via multiplicative weight updates
… two frameworks, ""lazy MWU"" for deterministic algorithms and ""randomized MWU"" for randomized algorithms, that algorithm designers can use to obtain nearly linear running times for their own problems of interest. This thesis has been organized as a user friendly guide, where we include basic …
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Quantum Algorithms and Complexity for Numerical Problems
… physics and computer science. Quantum algorithms can solve certain problems significantly faster than classical algorithms. There are many numerical problems, especially those arising from quantum systems, which are notoriously difficult to solve using classical computers, since the …
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Dimensionality reduction for sparse and structured matrices
… can make it impossible to apply standard algorithms efficiently. To address this issue, it is often possible to distill data to a much smaller set of informative features or examples, which can be used to obtain provably accurate approximate solutions to a variety of problems In this …
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Quantum signal processing
… new or modifying existing signal processing algorithms by drawing a parallel between quantum mechanical measurements and signal processing algorithms, and by exploiting the rich mathematical structure of quantum mechanics, but not requiring a physical implementation based on quantum …
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Principled Approaches for Latency Reduction in Networking Systems
… in datacenter environments. By employing randomized algorithms and considering both network and compute constraints, Nona demonstrates multiple orders of magnitude improvements in job completion times while maintaining implementation simplicity. Nona proposes stochastic scheduling, in …
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Computational geometry through the information lens
… with O(n) space, and 0( ... )query time. * randomized algorithms with running time 9 ... ) for 3-d convex hull, 2-d Voronoi diagram, 2-d line segment intersection, and a variety of related problems. * a data structure for 2-d dynamic convex hull, with O ( ... )query time, and O ( ... ) …
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Quantum speedups in query complexity
In this thesis, we study randomized and quantum algorithms in the query complexity model. We investigate when and by how much quantum algorithms provide a speedup over the best possible classical algorithm in the query complexity setting. We introduce a total Boolean function that exhibits a power …
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Resource-Efficient Machine Learning via Count-Sketches and Locality-Sensitive Hashing (LSH)
… resources, how do we scale machine learning algorithms to gain meaningful insights? Randomized algorithms are an essential tool in our algorithmic toolbox for solving these challenges. These algorithms achieve significant improvements in terms of computational cost or memory usage by …
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Control and collective intelligence of multi-agent system
… desired gathering and drifting group behaviors. Randomized algorithms are used to localize the agents and generate stationary distributions of the swarm. In the last part of the thesis, topological configuration space is implemented to assist the design of hybrid controls for a multi-agent …
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Propositional proof systems : efficiency and automatizability
… problems is fixed-parameter tractable by randomized algorithms with one-sided error.
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