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Skip to Search Results- 2Abdi Oskouie, Mina
- 2Birkbeck, Neil Aylon Charles
- 2Cai, Zhipeng
- 2Chen, Jiyang
- 2Chowdhury, Md Solimul
- 2Chubak, Pirooz
- 74Machine Learning
- 70Reinforcement Learning
- 41Artificial Intelligence
- 36Machine learning
- 22Natural Language Processing
- 22Reinforcement learning
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Spring 2012
Social networks are ubiquitous. They can be extracted from our purchase history at on-line retailers, our cellphone bills, and even our health records. Mining tech- niques that can accurately and efficiently identify interesting patterns in these net- works are sought after by researchers from a...
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Fall 2018
There is no shortage of community mining algorithms for discovering structure in complex information networks; most with unique advantages, however, all with drawbacks, including efficiency, correctness, resolution limit, and field of view limit. We introduce a novel efficient approach for...
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Spring 2023
Predicting a dense depth map from LiDAR scans and synced RGB images with a small deep neural network is a challenging task. Most top-accuracy methods boost precision by having a very large number of parameters and as a result huge memory consumption. Whereas, depth completion tasks are commonly...
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Comparing Parameterization Methods for Loss-Based Discrete-Time Individual Survival Prediction Models
DownloadFall 2023
Given a patient's description, a survival prediction model estimates that patient's survival time. We consider the challenge of learning an individual survival distribution (ISD) model from a dataset that includes censored training instances – i.e., data that provides only the lower bound of the...
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Fall 2011
XML, the Extensible Markup Language, is the standard exchange format for modern Information Systems, Service Oriented Architecture (SOA) and the Semantic Web. Hence, comparing XML documents has become a necessary task for tracking and merging changes between versions of the same document, or...
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Spring 2016
One of the key obstacles to the effective use of mass spectrometry (MS) in high throughput metabolomics is the difficulty in interpreting measured spectra to accurately and efficiently identify metabolites. Traditional methods for automated metabolite identification compare the target MS spectrum...
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Spring 2019
Modern parallel programming languages such as OpenMP provide simple, portable programming models that support offloading of computation to various accelerator devices. Coupled with the increasing prevalence of heterogeneous computing platforms and the battle for supremacy in the co-processor...
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Compiler-Only Code Generation for Performant and Modular Matrix-Multiplication Micro Kernels Using Matrix Engines
DownloadFall 2021
General Matrix-Matrix Multiplication (GEMM) is used widely in many high-performance application domains. In many cases, these applications repeatedly execute their matrix-multiplication subroutine, as is the case in the implementation of a particle-physics simulator or the repeated convolutions...
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Spring 2018
Many datasets can be represented as networks or graphs, where sets of nodes are joined together in pairs by links or edges. In the past, many works have been done on complex network analysis in deterministic graphs, graphs where the network structure is exactly and deterministically known....
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Spring 2016
Algorithmic decipherment is a prime example of a truly unsupervised problem. This thesis presents several algorithms developed for the purpose of decrypting unknown alphabetic scripts representing unknown languages. We assume that symbols in scripts which contain no more than a few dozen unique...