Browsing by Subject "Machine Learning"
Now showing items 41-49 of 49
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Representing Networks: Centrality, Node Embeddings, Community Outliers and Graph Representation
Networks are ubiquitous. We start our technical work in this thesis by exploring the classical concept of node centrality (also known as influence measure) in information networks. Like clustering, node centrality is also ... -
Robust Distribution-Free Learning Of Logic Expressions
(2012-05-24) -
Search for Long-Lived Particles at High Luminosity Large Hadron Collider and Beyond
Despite extensive searches, clear indications of new physics beyond the Standard Model (BSM) remain elusive. Traditionally, experimental searches at the Large Hadron Collider (LHC) during Phase I and phenomenological studies ... -
Sparse Bayesian Learning For Joint Channel Estimation Data Detection In OFDM Systems
(2018-08-30)Bayesian approaches for sparse signal recovery have enjoyed a long-standing history in signal processing and machine learning literature. Among the Bayesian techniques, the expectation maximization based Sparse Bayesian ... -
Sparse Multiclass And Multi-Label Classifier Design For Faster Inference
(2013-06-20)Many real-world problems like hand-written digit recognition or semantic scene classification are treated as multiclass or multi-label classification prob-lems. Solutions to these problems using support vector machines (SVMs) ... -
Studies In Automatic Management Of Storage Systems
(2015-11-16)Autonomic management is important in storage systems and the space of autonomics in storage systems is vast. Such autonomic management systems can employ a variety of techniques depending upon the specific problem. In this ... -
Temporal Point Processes for Forecasting Events in Higher-Order Networks
Real-world systems consisting of interacting entities can be effectively represented as time-evolving networks or graphs, where the entities are depicted as nodes, and the interactions between them are represented as ...